DE102022127792A1 - COMPUTER-IMPLEMENTED METHOD FOR USE IN A COMPUTER-AID PRODUCTION SYSTEM AND PRODUCTION SYSTEM - Google Patents

Abstract

The present invention relates to a computer-implemented method for use in a computer-aided production system (100), in particular for controlling an operation of the computer-aided production system (100), and a production system (100), wherein the method comprises at least the following steps: a) providing data that are assigned to one or more components (101), wherein the data contain information on two or more feature groups (106) that are assigned to one or more components, wherein each component for which data is provided is assigned at least one feature group, wherein a feature group each comprises a group of features that at least partially define the component to which the feature group is assigned, and wherein feature group data is assigned to each feature group, b) selecting at least one feature group, c) providing at least part of the feature group data that are assigned to the at least one selected feature group, d) evaluating the provided feature group data and determining a value of at least one variable characteristic of the selected feature group, and e) storing, outputting and/or further processing the data obtained in step d) at least one determined value.

Description

TECHNICAL AREA

The present invention relates to a computer-implemented method for use in a computer-aided production system, in particular for controlling an operation of the computer-aided production system. The invention further relates to a production system, a computer program, a computer-readable storage medium and a data processing device.

BACKGROUND OF THE INVENTION

Computer-aided production systems are generally known from the state of the art. In particular, CAx-supported systems are known (computer-aided X systems), where the "X" stands for various workstations or process sections within production. In particular, for example, computer-aided or computer-assisted systems are known that include at least one CAD station (computer-aided design), i.e. computer-aided construction, a CAM station (computer-aided manufacturing), i.e. computer-aided production, and/or a CAQ station (computer-aided quality), i.e. computer-aided quality assurance/testing. In addition, CAE (Computer-Aided Engineering), i.e. computer-aided development, CAP (Computer-Aided Planning), i.e. computer-aided work planning, CNC (Computerized Numerical Control), i.e. computer-controlled manufacturing, computer-aided production planning and control (PPS) and computer-aided production data acquisition (BDE) are also known. Computer-aided or computer-supported production systems that have one or more of the aforementioned computer-aided stations are generally referred to as so-called CIM production systems, i.e. so-called computer-integrated manufacturing production systems.

According to https://de.wikipedia.org/wiki/Computer-integrated_manufacturing, last accessed on October 3, 2022 According to the definition of the AWF (Committee for Economical Manufacturing, 1985), "CIM" describes the integrated use of IT in all operational areas related to production and includes the information technology interaction between CAD, CAP, CAM, CAQ and PPS. The aim here is to achieve the integration of the technical and organizational functions for product creation.

Computer-aided production systems, in particular so-called CIM production systems, as well as corresponding methods for use in these, in particular for the operation and control of such production systems, are basically known from the state of the art.

An overview of this is provided, for example, by A. Agovic, T. Trautner, F. Bleicher, Digital Transformation - Implementation of Drawingless Manufacturing: A Case Study, Procedia CIRP, Volume 107, 2022, Pages 1479-1484, ISSN 2212-8271, https://doi.org/10.1016/j.procir.2022.05.178 .

Furthermore, for example, WO 2020/204915 A1 a design and manufacturing system is known which includes a multi-axis machine tool with a cutting head capable of supporting a plurality of available tools and a part holder, the cutting head and/or the part holder being fully controllable in at least two axes, a design system operable using a computer to generate a 3D model of a part to be manufactured, and a machine learning model operable using the computer to analyze the part to be manufactured to identify features and develop a manufacturing plan based at least in part on the multi-axis machine tool and the plurality of available tools, the manufacturing plan including a tool type used for each feature, a feed rate for each tool type for each feature, and a tool speed for each tool type for each feature.

Out of WO 2019/226167 A1 a method for CAD operations and corresponding systems and computer readable media is further known. A method includes receiving 3D solid model data of a part to be manufactured, receiving at least one rule from a rule database, applying the rule to the 3D solid model data using a rule engine, and generating an output according to the rule applied to the 3D solid model data. The rule may include an extraction section that identifies elements or features of the 3D solid model data, a logic section that applies a condition to the identified elements or features, and an action section that defines an action to be performed on identified elements or features that satisfy the condition. The output may include an annotation of product manufacturing information about elements or features of the 3D solid model data that match the rule.

Out of WO 2018/083512 A1 are systems and a process for providing a processing method for manufacturing a feature of a part by receiving data of a set of features, each feature data describing a feature to be manufactured and comprising a type of the feature and a set of attributes of the feature. Each machining method is assigned a set of rank values to rank machining methods applicable to the same range of feature attributes. Data of an additional feature to be manufactured is received, the type of the additional feature being the predetermined type and the set of attributes of the additional feature being a specific set of attributes. At least one machining method of the selected methods is provided based on its associated rank value to be associated with the additional feature as a machining method for manufacturing the additional feature.

In WO 2016/178107 A1 describes a method for identifying geometric clones in a modeling system or for simulating design changes of a multi-part product and corresponding data processing systems and computer readable media. The described method includes selecting a template of a geometric shape and generating and storing an image of the template, identifying a candidate geometric shape in the system and exploring the identified candidate geometric shape from a starting point until returning to the starting point or reaching a junction. The method includes generating a map of the examined candidate geometric shape, comparing the map of the examined candidate geometric shape with the map of the template, and marking the candidate geometric shape as a clone if it matches a predefined portion of the template.

The objectives to be achieved with such processes and production systems are usually to achieve a higher degree of automation, reduce the error rate, avoid method, media and/or system breaks, improve process reliability, reduce data redundancy, improve data consistency, timeliness and quality, increase the standardization rate, increase audit security or improve version control of the data, reduce costs, increase transparency about costs and required capacities, and/or generally optimize the production system and its operation.

SUMMARY OF THE INVENTION

Against this background, it is an object of the present invention to provide an alternative method for use in a production system, i.e. for a production system, wherein it is a particular object of the present invention to provide an improved method which in particular enables improved operation of a production system, preferably optimized operation of a production system, in particular improved control of a production system.

Furthermore, it is an object of the present invention to provide an alternative production system, in particular an improved production system, which in particular enables improved operation, preferably optimized operation, in particular improved control.

Furthermore, it is an object of the present invention to provide an alternative, in particular improved computer program, an alternative, in particular improved computer-readable storage medium and an alternative, in particular improved data processing device, which in particular enable the provision of an alternative, in particular improved production system.

This object is achieved according to the invention by a method according to the invention, by a production system according to the invention, by a computer program according to the invention, by a storage medium according to the invention and by a data processing device according to the invention with the features according to the respective independent patent claims. Advantageous embodiments of the invention are the subject of the dependent patent claims, the description and the figures. The wording of the claims is made part of the content of the description by express reference.

1. a) Bereitstellen von Daten, die einem oder mehreren Bauteilen zugeordnet sein können, wobei die Daten Informationen enthalten können zu zwei oder mehr Merkmalsgruppen, die einem oder mehreren Bauteilen zugeordnet sein können, wobei jedem Bauteil, zu dem Daten bereitgestellt werden, wenigstens eine Merkmalsgruppe zugeordnet sein kann, wobei eine Merkmalsgruppe jeweils eine Gruppe von Merkmalen umfassen kann, welche das Bauteil, dem die Merkmalsgruppe zugeordnet sein kann, zumindest teilweise definieren können, und wobei jeder Merkmalsgruppe Merkmalsgruppendaten zugeordnet sein können,
2. b) Auswählen wenigstens einer Merkmalsgruppe,
3. c) Bereitstellen von zumindest einem Teil der Merkmalsgruppendaten, die der wenigstens einen ausgewählten Merkmalsgruppe zugeordnet sein können,
4. d) Auswerten von Merkmalsgruppendaten, insbesondere der bereitgestellten Merkmalsgruppendaten, und Bestimmen eines Wertes wenigstens einer charakteristischen Größe, insbesondere wenigstens einer für die Merkmalsgruppe charakteristischen Größe, und
5. e) Speichern, Ausgeben und/oder Weiterverarbeiten eines ermittelten Wertes, insbesondere des in Schritt d) wenigstens einen ermittelten Werts.

A computer-implemented method according to the present invention can be designed in particular for use in a computer-aided production system, that is to say for a computer-aided production system, in particular for use in a production system, wherein the method can comprise one or more of the following steps:

1. (a) providing data that can be associated with one or more components, where the data can contain information on two or more groups of features that can be associated with one or more components, where each component for which data is provided at least one feature group can be assigned to each feature group, wherein a feature group can each comprise a group of features which can at least partially define the component to which the feature group can be assigned, and wherein each feature group can be assigned feature group data,
2. b) selecting at least one group of characteristics,
3. c) providing at least part of the feature group data that can be associated with the at least one selected feature group,
4. d) evaluating feature group data, in particular the provided feature group data, and determining a value of at least one characteristic variable, in particular at least one variable characteristic of the feature group, and
5. e) storing, outputting and/or further processing a determined value, in particular the at least one determined value in step d).

A “production system” in the sense of the present invention is in particular a system which is designed for processing and/or manufacturing at least one component, wherein the production system does not have to be designed for complete manufacture or for complete processing of the component, but only for carrying out at least one processing step within the process chain for processing and/or manufacturing the component.

A “computer-aided or computer-assisted or computer-aided production system” is in particular a production system which comprises at least one workstation which has a computer or a comparable device and/or is connected or connectable to such a device for data exchange, wherein the computer or the comparable device is in particular set up to at least partially perform a required task in the process chain of machining the component.

A production system in the sense of the present invention has in particular at least one workstation, wherein a workstation in the sense of the present invention is in particular a station which is set up to process at least part of the data assigned to a component.

A "workstation" in the sense of the present invention can in particular be a production station, i.e. in particular a station with at least one machine tool. In particular, a workstation can be or comprise, for example, a cutting device, for example a milling machine, in particular a CNC milling machine, a lathe, in particular a CNC lathe, a forming machine, such as a press, or any other type of machine tool for production. A workstation can in particular be a boring machine, a machining center or a turning and milling machining center.

The term “production” can be understood in particular in the sense of DIN 8580. A production station can accordingly be a station at which in particular at least one processing step of a production process according to DIN 8580 can be carried out. In other words, a production station is set up in particular to carry out at least one processing step of a production process, in particular a production process according to DIN 8580.

In addition to a production station, a work station in the sense of the present invention, in particular as part of a production system according to the invention, can also be a PPS station, i.e. a production planning and control station. In particular, a work station can also be a work preparation station, a production program planning station, a quantity planning station, a scheduling and/or capacity planning station, an order monitoring station, an order initiation station, a design station and/or a testing and/or measuring station.

In other words, a workstation within the meaning of the present invention can be any station at which data associated with a component are at least partially processed as part of a manufacturing process for a component.

A workstation does not have to be designed to be able to process all of the data assigned to a component, but in the sense of the present invention it is sufficient if a workstation is set up to process only a subset of the data assigned to a component.

A workstation can in particular comprise or be a CAx station. Preferably, at least one workstation is a CAD station, a CAM station or a CAQ station or a combination thereof or comprises one of these.

A production system according to the present invention can in particular be a CIM production system.

A “component” within the meaning of the present invention is any workpiece, in particular any embodied workpiece, the manufacture and/or processing of which comprises at least one physical step, in particular a physical manufacturing step.

The “processing” of data assigned to a component in the sense of the invention means in particular at least one generation, processing, storage, reading out, capturing, reading in, outputting, displaying, converting, caching, changing, comparing, checking, sorting, converting and any other data processing option, in particular any data processing option possible with the aid of a computer, in particular any electronic data processing option, and/or combinations thereof.

Data assigned to a component can in particular be data which define a geometry of the component (geometry data), such as dimensions, tolerances, in particular dimensional, shape and position tolerances, and/or data which define one or more properties of the component (property data), such as material information, surface properties (roughness or the like), production data such as manufacturing parameters and/or specifications, such as the manufacturing process required for at least one processing step of the component and/or associated machine tool data or control parameters or process parameters such as cutting speeds, feed rates, cutting depths, manufacturing aids, cutting heads, etc., and/or test and/or measurement data which include test and/or measurement program information. Data assigned to a component can in particular also be associated design data, required process parameters such as process temperatures, rest times and/or temperature profiles, and/or production process data, for example after which step which quality controls are to be carried out, order data, and/or component identification data, such as batch numbers, production time and location, etc.

The data assigned to a component are in particular at least partially summarized into so-called feature groups, i.e. into groups of features, with at least one feature group being assigned to the component in particular. For example, all data that are assigned to a specific hole, for example “Hole 1”, in a workpiece can be summarized to form the feature group “Hole 1”. For example, for a feature group of the type “Hole”, the nominal diameter of the hole, the hole depth, shape and position tolerances of this hole, surface qualities in various inner surfaces of the hole, etc., an alphanumeric identification name and/or an object color that can be interpreted by the workstation and/or other recognition attributes, i.e. associated feature group data, can be summarized and assigned to one or more components via the associated feature group, here a feature group “Hole”, for example feature group “Hole 1”.

It is particularly advantageous if every component that can be processed within the production system and which includes a corresponding feature group with the associated data is assigned to the feature group or this feature group is assigned to the component.

Particularly when many components within a production system have one or more identical feature groups, such an assignment of feature groups to components can be used to achieve a high degree of standardization in a simple manner. When changes are made, only the data for each feature group needs to be changed, not for each component. This significantly reduces the amount of work required to make changes and thus significantly improves a production system. In particular, the production system can be operated more easily. Above all, the amount of work required to update can be reduced. Furthermore, less storage space is required to store the changes. In addition, version control can be simplified and auditability increased.

For example, features and their associated data can be grouped on the basis of so-called geometric form elements, i.e. in particular on the basis of geometric shapes that represent in particular basic geometric bodies or standard shapes.

For example, data and/or features that define a cylinder can be grouped into a feature group “cylinder”. The associated data that defines or characterizes a feature group are so-called “feature group data”.

Examples of form elements that can form particularly advantageous feature groups can be, for example: cylinders or cylindrical sections, bores, flat surfaces, chamfers, circles, partial circles, spheres, sphere sections - each positive or negative, ie as a recess or in Formed from solid material - grooves, cubes, cuboids and/or prisms.

For example, a bore 1 can be assigned a nominal diameter 1 with a borehole depth 1 and shape and position tolerances XY and/or an attribute for the unique identification and/or recognition of the shape element.

The provision of data in step a) of a method according to the invention comprises in particular the provision of data that contain information on one or more feature groups and/or are assigned to one or more components. The data can either only contain information about which feature group(s) is/are assigned to the component and/or information, i.e. data that directly defines the features of the group and/or the component at least partially. This means that for step a) it is generally sufficient if only or at least partially only data is provided that can be used, for example, to determine which components that can be processed in a production system are all assigned to a specific feature group, for example the feature group “bore” or “cylinder”, but that cannot be used to determine how precisely the feature group is defined. For an engine block, for example, this can be data that shows that the engine block has 4 cylindrical bores of the feature group “cylinder bore”, without the data already specifying the cylinder bore precisely in this step.

This information, such as how the cylinder bore is defined, i.e. precise feature group data, such as nominal diameter, tolerances, surface qualities, honing process parameters, possibly other associated machining processes and/or associated testing process(es) at a workstation (CAM, CAQ) and/or as mentioned above, can also only be provided later when required, for example only for, with or in step c) when this information is required for an evaluation, whereby in this case in particular only the feature group data from the selected feature group(s) is provided and not for additional feature groups. As a result, considerably less data needs to be provided for the provision of the feature group data in step c), which can save data streams, storage requirements, network resources, computing power and other resources.

The provision of data may in particular comprise reading data from a memory, in particular from a computer-readable memory, capturing data, collecting data, generating data and/or entering data, and a combination thereof.

In particular, data collection can also take place in a separate step before provision, in particular using one or more sensor devices.

Before providing corresponding data, in particular when deposited, saved or recorded data is provided, it can first be checked whether the available data intended for provision has already been assigned to one or more components. If this is not the case, the available data, at least part of this data, can first be assigned to one or more components and/or feature groups.

The available data is at least partially assigned to one or more components and/or one or more feature groups. The data can in particular contain information on one or more feature groups and/or components.

In some cases, it can be advantageous if the respective data is not assigned directly to one or more components, but only indirectly to a component via one or more feature groups. This has the advantage that no redundant assignments have to be maintained, but rather the data is only assigned to one associated feature group, for example, and only the feature group is assigned to the component, but the data and the feature groups are not directly assigned to the component. In particular, when there are a large number of components that can be processed within a production system, but many of which have one or more identical feature groups, this can significantly reduce the amount of information that needs to be stored or maintained. Furthermore, in many cases this can lead to a reduction in the error rate, an improvement in process reliability, an improvement in data consistency, timeliness and quality, an increase in the standardization rate, an increase in audit security, an acceleration of automation across workstations or an improvement in data version control and, as a result, a reduction in costs, an increase in transparency regarding costs and the required capacities and thus a general optimization of the production system and its operation.

“Feature group data” in the sense of the present invention are data which are assigned to at least one feature group and which contain at least part of the information for defining the feature group(s).

Using the example of a geometric form element "bore", feature group data can be, for example, the geometric data, such as nominal diameter and borehole depth. In addition to geometry data, feature group data can also be, as explained above in connection with data in general, production data and/or test and measurement program data. In particular, feature group data can be any type of attribute that can be assigned to a feature group, such as machine parameters for manufacturing the component, identification data, coordinate measurement reference data, etc.

In particular, the feature group data of a feature group can be individual or all data that can define and/or characterize the feature group or the features combined to form a group.

Feature groups do not have to be purely component-related groups of features or features combined in a geometrically meaningful way to form a group, but feature groups can also be groups of very different features. A feature group can also be a combination of feature groups, in particular of different feature groups. A feature group can, for example, be a group of features that on the one hand include features of a geometric form element and on the other hand, for example, features that define and/or characterize a throughput time, a scrap rate and/or costs. Feature group data can in particular be CAM data, CAQ data and/or CMM data.

A feature group can also be a group of features that includes multiple feature subgroups, such as a feature group "bore", which can include a wide variety of bores, in particular bores with different nominal diameters, whereby the bores with different nominal diameters can each represent individual feature subgroups. A feature group and/or one or more feature subgroups can alternatively or additionally also be assigned to a workstation (CAx), for example based on a revision status and/or identification using an ID number.

For example, feature groups have proven to be advantageous which each comprise features which characterize or define at least one geometric shape element, as well as other features associated with at least one geometric shape element, such as costs, throughput time and scrap rate and/or features which characterize the manufacturing process or one or more manufacturing steps and/or one or more testing processes. In particular, the feature groups “geometric shape element”, “geometric shape element and costs”, “geometric shape element and throughput time”, “geometric shape element and scrap rate” and “revision status of the geometric shape element” have proven to be advantageous with regard to improving the control of a production system, in particular with regard to improving the operation of a production system according to the invention, preferably with regard to optimizing a production system.

If data is available, in particular data that is assigned to one or more components and/or feature group data, but there is still no assignment of feature groups to one or more components or, conversely, no assignment of at least one feature group to each component, a method according to the invention can in particular comprise an assignment step, which is preferably carried out or takes place before the data is provided in step a), wherein in this assignment step, in particular, each component is assigned at least one feature group.

In an advantageous embodiment of a method according to the invention, this can be done in particular at least partially automated, in particular with the aid of corresponding, predefined reference feature groups which can be compared with the component, and if there is sufficient agreement, the component is assigned a corresponding feature group, in particular a predefined and/or stored feature group or a newly created or newly to be created feature group, depending on the reference feature group with which an at least partial agreement has been established.

Fully automated assignment is also conceivable, but partially automated assignment still allows manual control of the assignment. Fully automated assignment, on the other hand, enables faster assignment and avoidance of human errors as well as assignment independent of working hours, which in particular enables efficient assignment outside of a product. operation with little staff, for example at weekends or at night.

In the context of the present invention, the term “manual” refers in particular to the execution of individual actions and/or method steps by a user, operator, machine operator or the like.

In the sense of the present invention, “partially automated” means a process in which individual process steps are carried out manually, i.e. by a user, operator, or the like, and individual process steps are carried out with the aid of a corresponding computer device, automation device, or the like, in particular with the aid of a computer and/or a data processing device.

“Fully automated” means carrying out a process or process step without any manual steps.

Manual steps or procedural actions in this context can be, in particular, the input of data, the checking and/or release of data, the confirmation of actions, the starting and/or ending and/or the linking of data with one another or the like. The selection of at least one group of features in step b) takes place in particular according to defined criteria, preferably according to predefined criteria. A corresponding criterion can, for example, be the frequency of occurrence of a form element across all components that can be manufactured in a production system. Or the frequency of occurrence or manufacture of a specific form element in a defined period of time.

In one possible embodiment of a method according to the present invention, the feature group to be selected can be selected from all feature groups that are associated with the provided data or to which the provided data is associated, or only from a portion of these feature groups. This means that filtering can be carried out if necessary between the step of providing and selecting.

For example, the set of all feature groups from which a feature group is to be selected can be the set of all feature groups of one component, of several components, or only of selected components that can be manufactured in a production system. Alternatively or additionally, the set of all feature groups from which at least one feature group is to be selected can comprise a set of feature groups with one or more identical properties, for example with one or more identical work plans and/or steps and/or one or more identical CAx data sets, such as a common CAD model, a common CAM setup and/or a common CMM setup.

The data assigned to a component can in particular be feature group data and can be assigned to at least one feature group, whereby feature group data in particular can only be mandatorily linked to the feature group, but does not necessarily have to be directly linked to an associated component that is linked to the associated feature group.

Alternatively or furthermore, feature group data can also be data that is directly assigned to a component, in particular the component to which the associated feature group is assigned. Not all data that is directly assigned to a component necessarily has to be feature group data. It is also possible for data to be assigned to a component that is not assigned to a feature group. This can be, for example, part numbers, identification numbers or the like.

Likewise, feature groups can exist or be defined and thus be selectable, in particular one or more associated form elements to which no processing process or step is assigned. These can, for example, be surfaces on a component that are not machined, i.e. the surface on the raw part and the finished part are identical and are not subject to any process.

After the selection in step b), at least a portion of the feature group data associated with the at least one selected feature group is provided in step c). The provision can also be carried out in this step by reading from a memory, generating, capturing, retrieving or the like.

If the feature group data are provided by the at least one selected feature group, they are evaluated in step d) and at least one value of at least one variable characteristic of the feature group is determined. Such a value can be, for example, the mean value of a run through time of a defined geometric form element and/or an average, actually achieved feed rate of a milling machine for milling the contour of a geometric form element, in particular during roughing. However, such a value can also be, for example, an average achieved scrap rate due to an unachieved surface quality of a flat surface to be polished or the like.

A "characteristic size" for a selected feature group is understood to mean in particular a size with which the feature group can be at least partially characterized. This does not have to be a size that only allows conclusions to be drawn about the geometric properties of the component or dimensions, but can be any size that can be related to the feature group of a component. However, the characteristic size is particularly preferably a size that in particular allows a conclusion to be drawn about at least one process step in the production of the associated feature group in a production system. Once the characteristic size has been determined, it is stored, output and/or further processed in step e), in particular with the aid of a computer and/or a data processing device.

A characteristic value can be, for example: a frequency of occurrence of a characteristic group(s) in the components of the production system or across all or one or more selected workstations, a defined (target process duration) or an actual process duration (actual process duration) and/or these individually or combined cumulatively over the frequency of the characteristic group(s) and/or the associated costs.

A characteristic quantity can also be a revision history over a defined period of time, a current revision status, a maturity level and/or a physical or economic quantity.

In addition, every change to a feature group or the associated feature group data is subject to a revision history, given via the revision status, which provides both the level of maturity in the product development process and the associated economic and physical variables, which are defined in time via the feature group data.

The output may in particular comprise displaying on a display or other display device and/or outputting an advisory tone or signal tone or the like and/or voice information.

The further processing can in particular comprise at least one generation of a signal, for example a control signal for controlling at least one machine at at least one workstation and/or a data signal with data information for transmission to one or more workstations. A data signal can for example be a signal which comprises data information about the time of the last change to the feature group or at least one parameter value of the feature group data. This data signal can be used for example to ensure that no machining operation is carried out at a production station if a machining program is based on older data than an associated feature group which is to be machined at this workstation.

Further processing may alternatively or additionally include checking the determined value, for example checking whether this value is within a defined limit range and/or exceeds or falls below a defined threshold value. In this case, further processing may include, for example, generating a blocking signal that production of components to which the feature group from which the feature group data was evaluated is assigned and for which a characteristic value outside a permissible limit range has been determined is only permitted after a separate check and/or is blocked until approval has been given by an authorized body. For example, corresponding machine programs for processing the component, which include the respective associated feature group, may be blocked until corresponding changes to the component and/or feature group data have been made by the design department or one of the other workstations and these have been manually approved, in particular by an authorized body or person.

This makes it easy to achieve data consistency and quality across the entire production system. In particular, this can ensure that, for example, the correct data is always available for a processing operation at a workstation. This can reduce defective production and, as a result, reduce the scrap rate.

In particular, the further processing may comprise the generation and/or output and/or display and/or transmission of one or more control signals for the manual, partially automated and/or fully automated control of a production system depending on the at least one value determined in step d).

An advantageous embodiment of a production system according to the invention can further comprise a control step for manual, semi-automatic ized and/or fully automated control of the production system, which is carried out in particular as a function of the at least one value determined in step d).

In addition to at least one workstation, a production system can in particular also comprise at least one production data management system (PDMS), in particular a central PDMS, with the aid of which the data can be provided in particular centrally, wherein the data can in particular be received by the PDMS and sent from it to one or more workstations.

A PDMS can in particular comprise at least one data storage. At least one data storage can be a cloud data storage. This enables a flexible architecture of a production system in a simple manner.

A production system according to the present invention is preferably designed in particular to exchange data wired or wirelessly between the individual workstations and/or the production data management system.

In one possible embodiment of a method according to the present invention, in particular at least one method step is carried out with the aid of a data processing device and/or with the aid of a computer system.

A corresponding data processing device and/or a corresponding computer system can in particular be integrated into one of the workstations and/or several of the workstations and/or into the production data management system, but is (data) communication-connected or (data) communication-connectable to at least one of these units.

All steps of a method according to the present invention can be repeated once or several times. If technically reasonable and possible, the individual method steps can also be carried out in a different order and/or individual method steps can be carried out again before or after.

In an advantageous embodiment of a method according to the present invention, steps c), d) and e) are carried out in the order described above, i.e. first c), then d) and then e).

Depending on the design of a production system, however, it may be advantageous in some cases to carry out steps c), d) and e) in a different order, in particular in a second or further cycle, for example after the steps have been carried out once in the order a) to e) in a first cycle. This means that the prescribed procedure can also be applied iteratively.

In particular, in a second cycle, for example, feature group data of several selected feature groups can first be provided, evaluated and then, on the basis of the provided feature group data, one or a few feature groups can be selected, for example the most frequently occurring feature group or the five most common feature groups.

In particular, the method can be used to control an operation of the computer-aided production system, wherein it can be configured for manual control of the production system, for partially automated control of the production system, for fully automated control of the production system or for a combination thereof.

For a particularly advantageous result of a method according to the invention or for a particularly advantageous production system, at least one feature group is a group of features for a geometric shape element or a group of features that has features for a geometric shape element, wherein the associated feature group data characterize and/or define the shape element.

It has been shown that almost every component can be defined almost completely by one or more geometric form elements and their associated data. Components can therefore be grouped according to form elements. If processing data is assigned to the form elements, i.e. the respective feature groups "form element...", for example machine programs for manufacturing these form elements, standardization, adaptation, modification and data consistency can be achieved across many components with little effort.

In a possible embodiment of a method according to the present invention, at least one feature group, in particular each feature group, has at least one geometric shape element, in particular a geometric base body, and/or at least one feature dependent on a geometric shape element, wherein the associated feature group data in particular include at least geometry and/or production data and/or test and/or measurement data for the at least one geometric cal form element. In particular, each form element can be assigned at least one data set with data on the relative and/or absolute position of the form element. Alternatively or additionally, each feature group, in particular each form element, can be assigned an ID number for unique identification, in particular for unique identification of the feature groups and feature group data.

A geometric shape element can in particular have or be a bore, an elongated hole, a thread, a pin, a cylinder, a flat surface, a cuboid, a chamfer, a pocket, a cone, a truncated cone, a groove, a sphere, a sphere segment, a circle, a circle segment or the like, or can be at least partially formed or defined from a combination of these.

Feature group data can in particular be design data (geometric data, dimensions, tolerances, weight, material, ...), administrative data (order number, part number, ...), manufacturing data (feed rate, cutting speed, tool data, NC program, ...), production data (actual manufacturing data, throughput times, ...), test data, cost information, planning data or other data.

A feature group can in particular comprise or be a combination of feature (sub)groups, for example a combination of the feature groups “geometric shape element” and “costs” or “geometric shape element” and “throughput time” or “geometric shape element” and “rejection rate”, wherein at least one feature group and/or feature (sub)group in particular always comprises or is a “geometric shape element”, and wherein each feature subgroup is in particular also a feature group and can in particular be selected in step b).

A component can be assigned several feature groups and/or feature subgroups, whereby the feature groups and/or feature subgroups are in particular different and/or belong to one and the same main feature group.

A main feature group can be formed, for example, by the geometric shape element “bore” and a sub-feature group can be, for example, a feature group “bore with a defined nominal diameter”. A feature subgroup is in particular a feature group which comprises at least one parameter and an associated parameter value which further specifies the feature subgroup compared to the associated higher-level main feature group. A feature subgroup can have further subgroups. A feature group or subgroup can be, for example, a bore, for example a “bore with nominal diameter XY”. This feature group or subgroup can, for example, comprise two (further) feature subgroups, such as “bore with nominal diameter XY with flat countersink” and “bore with nominal diameter XY with conical countersink”.

In a further possible embodiment of a method according to the present invention, in particular in an advantageous embodiment, the selection of the at least one feature group takes place depending on a frequency distribution of at least one of the parts of the feature groups.

A selection depending on the frequency distribution of at least some of the feature groups, each of which is assigned to a geometric shape element or represents a geometric shape element, has proven to be particularly advantageous.

The selection can be made, depending in particular on the frequency distribution, across all characteristic groups occurring within a production system or only across a portion of the characteristic groups occurring.

Making the selection based on a frequency distribution has proven to be particularly advantageous for a production system, because the Pareto principle generally applies, according to which in a production system around 80% of the processing processes are usually attributable to just 20% of the feature groups, or to put it the other way around, 20% of the feature groups are the basis for 80% of the processing processes or define them. In many production systems in particular around 80% of the processing processes are attributable to just 20% of all the form elements within this production system. In other words, if you can identify those 20%, and in particular reliably identify the 20% of the form elements that cause around 80% of the expenditure, a lot can be achieved by optimizing these 20%. This can lead to a particularly efficient optimization of a production system.

In this context, however, the question arises as to how the 20% “correct” components can be clearly identified. For this purpose, it has proven advantageous to use feature groups and to assign one or more feature groups depending on a resulting frequency distribution of the feature groups, whereby in particular the most frequently occurring feature group and, if necessary, further feature groups are selected in descending order of frequency, in particular until around 20% of all occurring feature groups are recorded. These can then be evaluated in a further step, in particular their associated feature group data, and if necessary, appropriate measures can be initiated.

For a production system, it has proven particularly advantageous to use feature groups which comprise at least one geometric shape element and/or contain or group features of a geometric shape element, with associated feature group data which define and/or characterize the respective geometric shape elements. Therefore, the selection can be based in particular on a frequency distribution of feature groups which are based on at least one geometric shape element, across some or all of the components processed in the production system.

If all components that are processed within a production system are assigned to corresponding feature groups, in particular feature groups based on one or more geometric form elements, i.e. if the component is mentally "broken down" into several of these feature groups or if each component is composed of one or more feature groups, in particular structurally, the individual feature groups, in particular in this case the individual geometric form elements, represent the basis, in particular a kind of construction kit, for all components to be processed within the production system. In a similar way to how the individual words of a language can be put together to form sentences and entire texts, the components can be put together from the feature groups. Similar to language, the individual feature groups or form elements are found with different frequencies in the individual components and thus in particular with different frequencies within the production system. This means that not all of the generally occurring feature groups or in particular all geometric form elements occur equally often, but some more and others less. Some of the feature groups occur disproportionately often, similar to the behavior of the words in a language.

If it is possible to identify the relevant 20% of the feature groups, which account for approximately 80% of the effort or the like of a production system, a particularly efficient optimization of the production system of the products and the associated product development process (PEP) can be achieved, even at least partially automated.

In particular, by assigning feature groups to components and to processes within the production system, in particular to individual process steps within the product development process, for example in production planning and/or in production planning and control, in particular on the basis of geometric form elements, standardization can be efficiently achieved across the entire component spectrum of a company.

Standardization, in turn, enables efficient collection of operating data and consistent key figures on duration, costs, etc. By means of consistent operating data collection and/or generally consistent data collection on the production system, the production system, in particular production planning and control, can be supplied with the determined key figures and the operation and in particular the control of the production system can be continuously improved. This can achieve a type of self-management and self-organization of the production system, in particular in production planning and control. Furthermore, manufacturing processes that occur frequently, cause large capacities or costs, or are unstable or have low process reliability can be identified, filtered out and analyzed. Based on the evaluation results subsequently obtained for the selected feature groups, in particular form element-related feature group data and the key figures (characteristic variables) determined on this basis, such as frequency, throughput times, capacity requirements, costs and scrap, individual processes or process steps of the production system can be optimized by improving/changing the control of the respective process or process step.

This makes it possible to achieve an improvement and/or optimization in approximately 80% of the associated feature groups with little effort, namely based on approximately 20% of relevant feature groups from a developed set of feature groups.

In particular, a high level of data consistency can be achieved with just a few feature groups, as well as particularly efficient central management of all data in the production system.

The key to selecting the right, relevant feature groups is the correct definition of the feature groups. This means that Feature groups should be defined in such a way that they have sufficient, but not too high, "resolution" in relation to the component spectrum of the production system. This means that the type and number of feature groups from which selection can be made, particularly depending on their frequency, should be chosen appropriately.

For a production system, it has proven particularly advantageous in some cases if the feature groups are selected in such a way that a frequency distribution is established that approximates a frequency distribution according to Zipf's law, whereby the most frequently occurring feature group, i.e. the feature group at rank 1, has a frequency of around 5-10%, in particular around 7-12%, in particular around 10%. And the other feature groups in the subsequent ranks have a frequency that roughly follows Zipf's law.

The mathematical definition of Zipf's law is: If the elements of a set - for example the words of a text - are ordered according to their frequency, the probability p of their occurrence is inversely proportional to the position n on the frequency list. The position is also called rank: $$p\left(n\right)=1/n\to p\left(1\right)/n\text{with}n=RANG=\mathrm{1,}\mathrm{2,}\dots ,100000$$

Depending on how often the most common element (word) occurs, the frequency of all other elements can be estimated using the Zipf distribution function. Let's assume that the most common element occurs with a frequency of 10%: p(1) = 10%. Then you can determine the frequency of the subsequent ranks.

• RANG 1: $$p\left(1\right)=p\left(1\right)/1=10\%\text{ bei }R=1$$
  
• RANG 2: $$p\left(2\right)=p\left(1\right)/2=5\%\text{ bei }R=2$$
  
• RANG 3: $$p\left(3\right)=p\left(1\right)/3=\mathrm{3,3}\%\text{ bei }R=3$$
  

usw...So we know that:

• RANK 1: $$p\left(1\right)=p\left(1\right)/1=10\%\text{at}R=1$$
  
• RANK 2: $$p\left(2\right)=p\left(1\right)/2=5\%\text{at}R=2$$
  
• RANK 3: $$p\left(3\right)=p\left(1\right)/3=3.3\%\text{at}R=3$$
  

etc...

In a further possible embodiment of a method according to the present invention, the feature group is selected using Zipf's law based on the determined frequency distribution, wherein the feature groups are assigned a rank depending on their frequency according to Zipf's law and the feature group is selected depending on its rank, wherein in particular the highest-ranking feature group is selected. Alternatively, however, the second highest or a lower-ranking feature group can also be selected.

It is particularly advantageous to select the feature groups with the highest frequency, which represent approximately the most frequent 15-30%, especially the most frequent 20%.

The frequency distribution of the individual feature groups should preferably correspond to the Zipf distribution function, as it has been shown that this can achieve particularly good optimization results. This means that the feature group at rank 1 should have a frequency of around 10%, that at rank 2 around 5%, etc.

However, if the determination and/or frequency distribution of the feature groups reveals that, for example, the feature group at rank 1 occurs with a frequency of 50%, this is an indication that the underlying feature group definition has not been selected appropriately, in particular that it does not have sufficient “resolution”.

In this case, it can be advantageous, for example, to assign at least one additional parameter and corresponding values to the feature group at rank 1 or to other feature groups, and, for example, to define feature subgroups and carry out a second process cycle and, if necessary, repeat the individual process steps until the frequency distribution approaches the Zipf distribution function. If, for example, the geometric form element hole occurs most frequently at around 50%, it can be useful to define sub-feature groups of the feature group "hole", for example depending on the respective nominal diameter of the holes, to re-determine the frequency distribution of the feature groups with the new feature groups and then select the highest-ranking feature groups, analyze them and, if necessary, initiate measures. This is the only way to achieve efficient control of the production system. If the analysis/optimization of the production system were based on all holes, too many components would be optimized or too much effort would be required to significantly increase the level of automation, especially up to "80% automation". This allows the desired optimization to be achieved, but it is possible probably with a worse cost-benefit ratio.

In some cases, it may also be advantageous to choose the feature group definitions in such a way that they approximate an adapted/modified Zipf distribution function, which may be better suited to the production system in question and the associated components.

For example, the Zipf distribution function can be adapted to optimize feature group selection using compression and/or stretching parameters and/or one or more offsets.

In some cases it may be advantageous to use a frequency distribution function other than the Zipf distribution function. However, the Zipf distribution function has proven to be particularly advantageous for production systems.

In particular, if only very few feature groups are defined due to the production system and, as a result, one feature group (the most common) has a frequency of more than 20% and a meaningful increase in the "resolution" is not possible due to a lack of appropriate subdivision options, it can be advantageous to use a different distribution function as the basis to which the frequency distribution should approximate. For example, in this case a stretched Zipf distribution function (using appropriate parameters) or another distribution function can be used. However, a left-distributed frequency distribution seems to be advantageous in any case. Approaches or corresponding frequency distributions based on "Benford's Law", the "Pareto principle", the "Pareto effect", the "20/80 rule", a representation according to "ABC analysis" and/or a representation according to the so-called "top task analysis" are particularly advantageous.

However, it is generally important for a good result that the resolution of the feature groups on whose frequency distribution the selection is based is selected appropriately, which can be checked in particular with a defined frequency distribution, in particular with a frequency distribution adapted to the respective production system. In particular by means of a comparative representation (comparison plot).

In a further possible embodiment of a method according to the present invention, in particular in a further step e), it is checked whether the value determined in step d) is within a predefined, permissible value range and/or below or above a defined limit value. This makes it easy to determine whether the production system is working as desired or whether the control of the production system needs to be changed and/or optimized.

One or more permissible value ranges can in particular be specified, i.e. in particular predefined and stored in a memory and read out from it when required, and/or be or have been obtained from recorded process data of the production system, i.e. based on so-called operating data.

In a further possible embodiment of a method according to the present invention, in particular in a further step f), preferably depending on the value of the at least one characteristic variable determined in step d), at least one measure is initiated, wherein preferably at least one parameter value is changed, in particular of at least one parameter of the feature group data of the at least one selected feature group. And/or one or more parameters and their associated values are added to the data, in particular to the feature group data of the at least one selected feature group, wherein in particular a value of at least one control parameter for controlling the production system and/or at least one value of a component parameter is changed or added.

In particular, action will be taken if the test shows that the determined value is outside the permissible range.

If, for example, it is determined that a mold element has a particularly high scrap rate, it may be advantageous to change the values of one or more machining parameters at one of the associated production stations at which the mold element in question is machined (e.g. specify a different tool and/or adjust feed, speed, etc.) or, if necessary, to correct incorrect design data on which the mold element is based, or to check the quality of the component blanks.

If a production system has several similar workstations for processing a form element, it is easy to determine whether the scrap rate is within a defined tolerance range around the average scrap rate across all machines, or outside of it, and thus the control of the production system should be adjusted to reduce the scrap rate of the respective mold element.

In an advantageous embodiment of a method according to the present invention, in a further step c1) at least one parameter value of the provided feature group data is changed and preferably, in particular also in a further step d1), the feature group data of at least some components, preferably of all components, to which the feature group with the feature group data is assigned, of which at least one parameter value has been changed, is updated.

In this case, at least one parameter value is preferably adapted, preferably depending on the value of at least one characteristic variable of the feature group determined in step d), preferably a parameter which is suitable for controlling the production system and in particular such that an improved operation of the associated production system can be achieved, in particular an optimization.

An adaptation can in particular include component optimization, i.e. an adaptation of the component data, e.g. geometry data, and/or an adaptation of machine/workstation data for processing on a production station. An adaptation can, however, also include a change in production planning, for example a change in process planning, for example the relocation of the processing of a form element from one processing machine to another.

An added parameter (value) can, for example, be a blocking flag that indicates or contains information that, for example, form element XY may no longer be manufactured on machine Z, whereby such a blocking flag can, for example, trigger a blocking of processing on machine Z if a component with the relevant form element XY accidentally ends up on machine Z for processing. This can be particularly advantageous in production systems with CAx workstations or CAx processing processes that are downstream of one or more CAD processing stations or steps.

Data to be added can also be new test and measurement program information, for example a new, additional measuring point, an additional tolerance specification or the like.

Process data can also be data that can be added or changed in the form of parameters and associated values, such as temperature specifications or temperature curves to define temperature control in a machining process.

Physical quantities can also be corresponding (added) data.

In some cases it may be necessary, for example, to restrict previously freely selectable values of a parameter to a defined, permissible range and/or, for example, to widen or narrow tolerance bands.

In a further possible embodiment of a method according to the present invention, the changed parameter value and/or one or more parameters to be added and their parameter values as well as information about the associated change(s) are stored in a production data management system, in particular centrally. This makes it particularly easy to reduce data redundancy, improve data consistency, timeliness and quality, increase the standardization rate, increase audit security and improve version control of the data. Furthermore, central data storage and the resulting reduced data redundancy can reduce the error rate in many cases. This in turn has a beneficial effect on process reliability and costs.

In particular, all data, preferably all feature group and component data, can be stored in a production data management system, in particular centrally.

If the data assigned to a component and/or a feature group and their changes are stored centrally in a production data management system (PDMS) and this is linked to the individual workstations, i.e. in particular if it is connected or connectable via data communication, data changes can be implemented quickly and without much effort across many components and transmitted to the respective workstations or, conversely, values changed at workstations can be played back directly to each component via the associated feature group.

In a further possible embodiment of a method according to the present invention, the parameter value and/or one or more parameters to be added and their parameter values as well as information about the associated change(s) are changed across all components to which the at least one selected feature group is assigned, wherein the change(s) and/or updates can be carried out in particular manually, partially automated or fully automated.

If the data assigned to a component and/or a feature group and its changes are stored centrally in a production data management system (PDMS) and this is linked to the individual workstations, i.e. in particular connected or connectable via data communication, data changes can be implemented quickly and without much effort across many components by assigning feature groups to components and transmitted to the respective workstations or, conversely, values changed at workstations can be played back directly to each component via the associated feature group, since not all components need to be changed, only the feature group data, the number of which is considerably lower than the number of components. This means that considerably fewer changes are required in numerical terms.

This allows for easier version control and easier tracking of changes. In particular, the resources required to manage the changes (such as the required storage space) can be significantly reduced.

Furthermore, this approach can be used to determine the maturity level of a component with little effort, in particular within the CAx chain of the associated production system, namely via the respective maturity levels of the feature group(s) assigned to the component. The maturity level of a feature group across one or more workstations or across the entire CIM architecture is defined in particular by the revision status or the version or change status of the feature group, in particular by the revision status or the version or change status of the associated feature group data and can therefore be determined in an advantageous embodiment of a method according to the invention in particular with the aid of the revision status and/or the version and/or change status of some or all of the feature group data of a feature group. In another possible embodiment of a method according to the present invention, the maturity level of the component can also be determined from the maturity level of one or more feature groups of a component.

In a further possible embodiment of a method according to the present invention, in particular during operation of the production system, before starting a work process at a work station of the production system for processing a component, the data provided locally at or in the work station for processing the component are at least partially compared with the data stored centrally in the production data management system, wherein in the event of a data inconsistency, in particular the work process for processing the component is at least temporarily blocked and/or stopped and/or terminated, in particular until an authorized release is made, preferably a manual release.

For example, it can be checked in particular whether the programs etc. stored at the workstation for processing the component are based on the latest or current data assigned to the component or whether changes made at the workstation for improved processing have been assigned to the component and/or the affected feature group(s) of the component and have been stored in the central production data management system.

If a data inconsistency is detected, a warning message may be issued (acoustically and/or using a visual display) indicating that the data is not up to date.

If feature groups are also assigned to machine data and/or process data, and to the individual components via the feature groups, this also makes it possible to implement simple revision control over part or the entire process chain with little effort, in particular with few resources.

An improvement/optimization of the operation of a computer-aided production system can be achieved even without the above-described selection of a feature group and the associated evaluation of the associated feature group data if the changed parameter value and/or one or more parameters to be added and their parameter values as well as information about the associated change(s) are stored centrally in a production data management system, and before starting a work process at a workstation of the production system for processing a component, the data provided locally at or in the workstation for processing the component are compared with the data stored centrally in the production data management system, whereby in the event of a data inconsistency, in particular the work process for processing the component, preferably for all affected components, is blocked at least temporarily.

This could be achieved, for example, with a computer-implemented method for controlling the operation of a computer-aided production system, in which the feature group data of a feature group are updated in particular at regular intervals can, whereby in particular after each change to the feature group data made by an operator at a processing station, a production system-wide change is or can be proposed, which becomes or can become binding across the production system after successful, authorized release.

1. a) Bereitstellen von Daten, die einem oder mehreren Bauteilen zugeordnet sein können, wobei die Daten Informationen enthalten können zu zwei oder mehr Merkmalsgruppen, die einem oder mehreren Bauteilen zugeordnet sind, wobei jedem Bauteil, zu dem Daten bereitgestellt werden können, wenigstens eine Merkmalsgruppe zugeordnet sein kann, und wobei jeder Merkmalsgruppe Merkmalsgruppendaten zugeordnet sein können,
2. b) Auswählen wenigstens einer Merkmalsgruppe,
3. c1) Ändern wenigstens eines Parameterwertes, insbesondere wenigstens eines Parameterwertes der bereitgestellten Merkmalsgruppendaten,
4. d1) Aktualisieren der Merkmalsgruppendaten von zumindest einigen Bauteilen, vorzugsweise von allen Bauteilen, denen die Merkmalsgruppe mit den Merkmalsgruppendaten zugeordnet ist, von der wenigstens ein Parameterwert geändert worden ist.

A computer-implemented method, preferably for use in a computer-aided production system, in particular for operating a computer-aided production system and/or for controlling a computer-aided production system, can accordingly also comprise only one or more of the following steps:

1. a) providing data that can be assigned to one or more components, wherein the data can contain information on two or more feature groups that are assigned to one or more components, wherein each component for which data can be provided can be assigned at least one feature group, and wherein each feature group can be assigned feature group data,
2. b) selecting at least one group of characteristics,
3. c1) changing at least one parameter value, in particular at least one parameter value of the provided feature group data,
4. d1) Updating the feature group data of at least some components, preferably of all components, to which the feature group with the feature group data is assigned, of which at least one parameter value has been changed.

In particular, at least one method step can be carried out with the aid of a data processing device and/or with the aid of a computer system.

This can significantly improve the process reliability of a production system. In particular, it is easy to ensure that the most current data is always used.

A computer-aided production system according to the present invention can be characterized in particular in that it is designed and in particular configured to carry out one of the methods described above, wherein the production system can in particular comprise corresponding means for carrying out such a method.

The computer-aided production system can in particular have one or more workstations, whereby the workstations can in particular be networked with one another for communication purposes (wireless and/or wired). A production system can have one or more identical or identical workstations as well as different workstations.

At least one workstation is particularly configured to process at least a subset of data associated with a component.

The production system may comprise at least one data processing device and/or at least one computer system.

A production system according to the present invention may in particular be configured to collect and store production system data during operation.

A production system according to the present invention can in particular be configured to assign production system data, in particular production system data acquired during operation, at least partially in a feature group-specific or feature group-related manner, in particular in a form element-related manner, and preferably at least partially automated, preferably fully automated.

A production system according to the present invention can in particular be configured to assign production system data acquired in connection with the processing of a component, in particular during the processing of a component, in a feature group-specific and/or feature group-related manner to the feature group(s) assigned to the component, in particular in a form element-related manner, i.e. to the form elements assigned to the component.

In a possible embodiment of a production system according to the present invention, the production system is further configured in particular to at least partially compare the data provided locally at or in the workstation for processing the component with the data stored centrally in the production data management system before starting a work process at a workstation of the production system for processing a component, wherein the production system is further configured in particular to at least temporarily block and/or stop and/or terminate the work process for processing the component in the event of a data inconsistency.

A computer program according to the present invention may in particular comprise instructions which, when the program is executed by a computer, cause the computer to carry out one of the methods described above.

A computer-readable storage medium according to the present invention is in particular a computer-readable storage medium on which a computer program is stored, in particular a computer program which comprises instructions which, when the program is executed by a computer, cause the computer to carry out one of the methods described above.

A data processing device according to the present invention can in particular be a computer or a control device for a production system according to the invention, wherein the data processing device can comprise means for carrying out a method according to the present invention.

A further aspect of the present invention can be a database, a database structure or a database system which can be communicatively connected in particular to a previously described data processing device and/or can be part of the latter, wherein the database comprises in particular data and relations associated with the data which are at least partially feature group data and are associated with at least one feature group, wherein the database is set up for use in a previously described production system and the data and relations are stored in the database in such a way that at least part of the data stored in the database can be used to carry out a previously described method.

All preferred embodiments and their advantages described herein with reference to the method apply accordingly to a production system according to the invention, a computer program according to the invention, a computer-readable storage medium according to the invention and a data processing device according to the invention and vice versa, insofar as this is technically possible in each case.

Further features of the invention emerge from the claims, the figures and the description of the figures. All features and combinations of features mentioned above in the description as well as the features and combinations of features mentioned below in the description of the figures and/or shown alone in the figures can be used not only in the combination specified in each case, but also in other combinations or on their own.

The invention will now be explained in more detail using a preferred embodiment and with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

• 1: in schematischer Prinzipdarstellung ein Ausführungsbeispiel eines erfindungsgemäßen Produktionssystems
• 2: ein Flussdiagramm mit Verfahrensschritten eines Ausführungsbeispiels eines erfindungsgemäßen Verfahrens,
• 3: ein Flussdiagramm mit weiteren, möglichen Verfahrensschritten eines erfindungsgemäßen Verfahrens,
• 4: ein Flussdiagramm mit Verfahrensschritten eines weiteren möglichen, insbesondere vorteilhaften Verfahrens zur Verwendung in einem computerunterstützten Produktionssystem,
• 5: die Referenz-Formelemente bzw. die Merkmalsgruppen „Bohrung“ und „Quader“ des Bauteils aus 1 in vergrößerter Darstellung,
• 6: eine beispielhafte, schematische Darstellung einer möglichen Zuordnung von Merkmalsgruppen und Merkmalsgruppendaten zu einem Bauteil mit den Merkmalsgruppen im Zentrum der Abbildung,
• 7: ein Beispiel einer ersten, für ein Produktionssystem ermittelten Häufigkeitsverteilung von Merkmalsgruppen, hier geometrischen Formelementen, von Bauteilen, die von einem zugehörigen Produktionssystem bearbeitet werden,
• 8: die Häufigkeitsverteilung aus 7, wobei diejenigen geometrischen Formelement, welche ca. 80% aller Formelemente, die in dem Produktionssystem bearbeitet werden, hervorgehoben sind,
• 9: in schematischer Prinzipdarstellung der Kurvenverlauf einer Zipf`schen Verteilung, d.h. den Kurvenverlauf einer Häufigkeitsverteilung, die dem Zipf`schen Gesetz folgt,
• 10: eine Tabelle mit den einer Zipf`schen Häufigkeitsverteilung zugrundeliegenden Funktionsvariablen und ihr Zusammenhang,
• 11: Beispieldaten einer Zipf`schen Verteilung,
• 12: eine Tabelle mit Beispieldaten zur Häufigkeitsverteilung von verschiedenen Merkmalsgruppen, hier von verschiedenen geometrischen Formelementen, die in einem computergestützten Produktionssystem bearbeitet werden, wobei die Formelemente in Abhängigkeit von ihrer Häufigkeit nach Rängen sortiert sind,
• 13: eine Tabelle zur Häufigkeitsverteilung von Unter-Formelementen X... des Formelements X, die in einem computergestützten Produktionssystem bearbeitet werden, wobei die Unter-Formelemente in Abhängigkeit von ihrer Häufigkeit nach Rängen sortiert sind,
• 14: die Häufigkeitsverteilung der Formelemente aus den 7 und 8 mit in Unter-Formelemente aufgeteilten Formelementen bzw. Merkmalsgruppen,
• 15: einen schematischen Kurvenverlauf der Häufigkeitsverteilung aus 14 für die Häufigkeitsverteilung der Merkmalsgruppe „geometrisches Formelement“ über die zugehörigen geometrischen Formelemente sortiert nach Rang,
• 16: einen schematischen Kurvenverlauf einer Häufigkeitsverteilung für die Häufigkeitsverteilung der Merkmalsgruppe „geometrisches Formelement x Durchlaufzeit“ über die zugehörigen geometrischen Formelemente sortiert nach Rang,
• 17: einen schematischen Kurvenverlauf der Häufigkeitsverteilung aus 14 für die Häufigkeitsverteilung der Merkmalsgruppe „geometrisches Formelement x Kosten“ über die zugehörigen geometrischen Formelemente sortiert nach Rang,
• 18: eine Prinzipdarstellung für ein Ausführungsbeispiel zur Schnittstellenorganisation und für mögliche Daten- und Informationsströme zwischen verschiedenen Arbeitsstationen eines erfindungsgemäßen Produktionssystems, und
• 19: eine weitere Prinzipdarstellung für ein Ausführungsbeispiel für mögliche Daten- und Informationsströme ausgehend von einem Merkmalsgruppen-Referenz-Template (Merkmalsgruppen-Referenz-Datensatz) an verschiedene CAx-Arbeitsstationen eines erfindungsgemäßen Produktionssystems.

Show it:

• 1 : in schematic principle representation an embodiment of a production system according to the invention
• 2 : a flow chart with method steps of an embodiment of a method according to the invention,
• 3 : a flow chart with further possible process steps of a process according to the invention,
• 4 : a flow chart with process steps of another possible, particularly advantageous method for use in a computer-aided production system,
• 5 : the reference form elements or the feature groups “bore” and “cuboid” of the component from 1 in enlarged view,
• 6 : an exemplary, schematic representation of a possible assignment of feature groups and feature group data to a component with the feature groups in the centre of the figure,
• 7 : an example of a first frequency distribution of feature groups, here geometric form elements, of components that are processed by an associated production system, determined for a production system,
• 8th : the frequency distribution of 7 , highlighting those geometric form elements which represent approximately 80% of all form elements processed in the production system,
• 9 : in schematic representation of the curve of a Zipf distribution, i.e. the curve of a frequency distribution that follows Zipf's law,
• 10 : a table with the functional variables underlying a Zipf frequency distribution and their relationship,
• 11 : Example data of a Zipf distribution,
• 12 : a table with sample data on the frequency distribution of different feature groups, here of different geometric form elements, which are in a computer-aided production system, whereby the form elements are sorted by ranks depending on their frequency,
• 13 : a table showing the frequency distribution of sub-form elements X... of the form element X which are processed in a computer-aided production system, whereby the sub-form elements are sorted by ranks depending on their frequency,
• 14 : the frequency distribution of the formula elements from the 7 and 8th with form elements or feature groups divided into sub-form elements,
• 15 : a schematic curve of the frequency distribution from 14 for the frequency distribution of the feature group “geometric form element” over the associated geometric form elements sorted by rank,
• 16 : a schematic curve of a frequency distribution for the frequency distribution of the feature group “geometric form element x processing time” over the associated geometric form elements sorted by rank,
• 17 : a schematic curve of the frequency distribution from 14 for the frequency distribution of the feature group “geometric form element x costs” over the associated geometric form elements sorted by rank,
• 18 : a schematic diagram of an embodiment of the interface organization and of possible data and information flows between different workstations of a production system according to the invention, and
• 19 : a further schematic representation of an embodiment of possible data and information flows starting from a feature group reference template (feature group reference data set) to various CAx workstations of a production system according to the invention.

DESCRIPTION OF PREFERRED EMBODIMENTS

1 shows a schematic diagram of an embodiment of a production system 100 according to the invention, wherein the production system 100 according to the invention is designed to carry out a method according to the invention and has a production data management system 120 with a data processing device 130 according to the invention and a data storage device 140 located in a cloud 110.

Furthermore, this embodiment of a production system 100 according to the invention comprises a plurality of work stations 10, 20, 30, 50, 60, 70, 80 and 90, which are each designed in particular to process at least a subset of data associated with a component 101 which is in 1 symbolized by a star with a hole 106 in the middle, or to at least partially physically process the component 101.

The component 101 can be, for example, a Christmas candlestick or the like. However, the geometry of the component 101 is not important in this case. Only a component has been selected that enables a simplified, pictorial representation for a better understanding. All features and advantages and the like described in connection with the component 101 are not to be understood as a limitation, but merely as an example for the basic description of the present invention.

Likewise, all embodiments described in connection with the embodiment of the production system 100 according to the invention are not to be understood as limiting, but merely as an exemplary explanation of the invention. The production system 100 described and the method for operating this production system 100 described in this context are each examples of a possible embodiment based on the present invention.

In this embodiment of a production system according to the present invention, the workstations 10, 20 and 30 of the production system 100 are each organizationally assigned to production planning and are designed in particular for product-specific processing, with the workstation 10 being in particular a CAD workstation, the workstation 20 in particular a CAM workstation, the workstation 30 in particular a CAQ workstation. The workstations 50 to 90, on the other hand, are assigned to production planning and control (PPS), which in 1 is symbolized by block 40 and is configured and set up in particular for order-related processing.

The workstation 50 is in particular a product program planning workstation, the workstation 60 a quantity planning workstation, the workstation 70 a scheduling and capacity planning workstation, the workstation 80 an order monitoring workstation and the workstation 90 an order initiation workstation.

All workstations 10 to 30 and 50 to 90 are each connected to the production data management system 120 or the associated data processing device 130 by data communication, in this embodiment in particular via a wireless communication connection (WLAN) or radio or in another wireless manner, which is symbolized by the connecting lines with the reference numerals 104 and 105.

In addition, the individual workstations 10 to 30 and 50 to 90 are also connected to one another via data communication and are also in data communication with the data storage 140 in the cloud 110 via the data communication connections 102 and 103, which are also designed as wireless communication connections in this embodiment.

This enables efficient and rapid data exchange between the individual workstations 10 to 30 and 50 to 90 and thus between all components of the production system 100. This enables high data consistency, rapid provision of current data at each workstation 10 to 30 and 50 to 90 and thus optimal processing of the data at the individual workstations 10 to 30 and 50 to 90.

A high level of data integrity and data consistency can be achieved through the central storage of the data in the data storage 140 and the central production data management system 120, via which the workstations are supplied with the respective data or via which data can be played back from the workstations. In particular, the data for each component 101 can be kept up to date almost in real time at each workstation 10 to 30 and 50 to 90 with minimal effort and thus, for example, the current data can be made available before each work step at a workstation 10 to 30 and 50 to 90. This reduces defective production based on incorrect data assigned to a component and thus reduces the scrap rate, optimizes the production system and reduces costs.

For particularly efficient operation of a production system 100 according to the invention, one or more feature groups 106 are assigned to each of the individual components 101 that can be processed within the production system 100. These are in turn assigned corresponding feature group data, with at least one feature group 106 that is assigned to a respective component 101 comprising a group of features for a geometric form element 106 and in particular comprising or being a feature group 106 of the “geometric form element” type. This enables particularly efficient operation of a production system 100 to be achieved. This is because it has been found that almost all components 101 can be composed of several, in particular so-called standard geometry form elements.

One such example of a geometric form element which can form a first feature group is, for example, the geometric form element bore 106 of the component 101. The associated form element 106 or the associated feature group 106 can be defined by the feature group data assigned to the form element or the feature group “geometric form element”.

Corresponding feature group data can, for example, be geometric data such as dimensions, relative and absolute positions, shape and position tolerances, but also information such as surface qualities, materials, or production data, such as process parameters for production such as cutting speeds, feed rates or the like, for example in a machining process, required production aids for holding, chucks, as well as test programs, plans and points or other quality assurance measures, machine data or information on which machine the component is to be manufactured on, flow charts for defining individual processing steps, etc. In addition, other data can also be assigned to a feature group, such as process parameters such as temperature control curves, rest times, drying times, maximum permissible throughput times, maximum permissible rest times before further processing, costs, capacity requirements, outline times, cleaning instructions or the like.

In this way, most or even all components can be defined in many production systems, especially via the various feature groups, whereby only the individual feature groups need to be assigned to a component, but not the individual feature group data. Rather, it is sufficient if the individual feature group data is only assigned to the feature groups, but the assignment of the individual parameters for each component is not stored separately. Since there are considerably fewer feature groups in a production system than there are usually components, the storage requirements for all data on the individual components can be significantly reduced and a high degree of standardization can be achieved in a simple manner with minimal effort. However, it is important that suitable feature groups are assigned to the components and that these, in turn, are assigned suitable feature group data in order to fully exploit this effect.

A further advantage of this approach is that particularly simple changes and updates to data can be made by making a single change to a feature group or the associated feature group data on a large number of components 101, namely on all those components to which the associated, changed feature group 106 is assigned. This can achieve considerable savings in the operation of a production system 100, in particular fewer resources are required for storing, processing and documenting changes. In other words, version control or assurance and change management can be significantly simplified. This also makes it easy to extend version control or revision security, as known from design, to all workstations 10 to 30 and 50 to 90 within a production system. In this way, production data such as machine data and manufacturing parameters that are assigned to a feature group, for example a geometric shape element for its production, can be assigned to version control and change management together with the geometric data that defines the geometry of the respective element. This creates the possibility of comprehensive and audit-proof data management.

Furthermore, this approach enables particularly efficient operation and, in a particularly simple manner, advantageous, in particular improved control and/or optimization of a production system designed according to this approach.

A particularly advantageous operation or a particularly advantageous control of a production system according to the invention can be achieved, for example, with a method according to the present invention.

2 shows a flow chart with the first four method steps S1 to S4 of an embodiment of a method according to the invention for use in a computer-aided production system, such as a production system 100, in particular for controlling an operation of the computer-aided production system 100.

• S1: a) Bereitstellen von Daten, die einem oder mehreren Bauteilen 101 zugeordnet sind, wobei die Daten Informationen enthalten zu zwei oder mehr Merkmalsgruppen 106, die jeweils einem oder mehreren Bauteilen 101 zugeordnet sind, wobei jedem Bauteil, zu dem Daten bereitgestellt werden, wenigstens eine Merkmalsgruppe zugeordnet ist, wobei eine Merkmalsgruppe jeweils eine Gruppe von Merkmalen umfasst, welche das Bauteil, dem die Merkmalsgruppe zugeordnet ist, zumindest teilweise definieren, und wobei jeder Merkmalsgruppe Merkmalsgruppendaten zugeordnet sind,
• S2: b) Auswählen wenigstens einer Merkmalsgruppe,
• S3: c) Bereitstellen von zumindest einem Teil der Merkmalsgruppendaten, die der wenigstens einen ausgewählten Merkmalsgruppe zugeordnet sind,
• S4: d) Auswerten der bereitgestellten Merkmalsgruppendaten und Bestimmen eines Wertes wenigstens einer für die ausgewählte Merkmalsgruppe charakteristischen Größe, d.h., den Wert einer Kennzahl für die ausgewählte Merkmalsgruppe,
• S5: e) Speichern, Ausgeben und/oder Weiterverarbeiten des in Schritt d) wenigstens einen ermittelten Wertes,
• S6: f) Einleiten wenigstens einer Maßnahme in Abhängigkeit von dem in Schritt d) bestimmten Wert der wenigstens einen charakteristischen Größe, wobei wenigstens ein Parameterwert von wenigstens einem Parameter der Merkmalsgruppendaten der wenigstens einen ausgewählten Merkmalsgruppe geändert wird und/oder ein oder mehrere Parameter und ihre zugehörigen Werte den Merkmalsgruppendaten der wenigstens einen ausgewählten Merkmalsgruppe hinzugefügt werden, wobei insbesondere ein Wert wenigstens eines Steuerparameters zur Steuerung des Produktionssystems und/oder wenigstens ein Wert eines Bauteilparameters geändert oder hinzugefügt wird,
• S7: g) Speichern des/der geänderte(n) Parameterwert(e) und/oder des oder der hinzugefügten Parameter und ihrer Parameterwerte sowie Informationen über die zugehörige(n) Änderung(en) zentral in einem Produktionsdatenmanagementsystem, und
• S8: h) Prüfen einer Datenkonsistenz während eines Betriebs des Produktionssystems, insbesondere vor einem Start eines Arbeitsprozesses an einer Arbeitsstation des Produktionssystems zur Bearbeitung eines Bauteils, wobei dazu die lokal an oder in der Arbeitsstation für die Bearbeitung des Bauteils bereitgestellten Daten zumindest teilweise mit den zentral im Produktionsdatenmanagementsystem gespeicherten Daten verglichen werden, wobei bei einer Dateninkonsistenz der Arbeitsvorgang zur Bearbeitung des Bauteils zumindest vorübergehend gesperrt und/oder angehalten und/oder beendet und/oder manuell, teilautomatisiert oder vollautomatisiert aktualisiert wird.

3 shows a flow chart with further possible method steps of a method according to the invention, which immediately follow in this embodiment. The embodiment of a method according to the present invention described here comprises in particular at least the following steps:

• S1: a) providing data that is assigned to one or more components 101, wherein the data contains information about two or more feature groups 106, each of which is assigned to one or more components 101, wherein each component for which data is provided is assigned at least one feature group, wherein a feature group comprises a group of features that at least partially define the component to which the feature group is assigned, and wherein each feature group is assigned feature group data,
• S2: b) selecting at least one group of features,
• S3: c) providing at least part of the feature group data associated with the at least one selected feature group,
• S4: d) evaluating the provided feature group data and determining a value of at least one characteristic quantity for the selected feature group, ie, the value of a key figure for the selected feature group,
• S5: e) storing, outputting and/or further processing the at least one value determined in step d),
• S6: f) initiating at least one measure depending on the value of the at least one characteristic variable determined in step d), wherein at least one parameter value of at least one parameter of the feature group data of the at least one selected feature group is changed and/or one or more parameters and their associated values are added to the feature group data of the at least one selected feature group, wherein in particular a value of at least one control parameter for controlling the production system and/or at least one value of a component parameter is changed or added,
• S7: g) storing the changed parameter value(s) and/or the added parameter(s) and their parameter values as well as information about the associated change(s) centrally in a production data management system, and
• S8: h) Checking data consistency during operation of the production system, in particular before starting a work process at a work station of the production system for processing a component, whereby the data provided locally at or in the work station for processing the component are at least partially compared with the data stored centrally in the production data management system, whereby in the event of data inconsistency the work process for processing the component is at least temporarily blocked and/or stopped and/or terminated and/or updated manually, partially automated or fully automated.

Related to the production system 100 from 1 In step a) or S1, data associated with the component 101 and other components not shown here are provided, which contain information on at least the feature group 106 (“geometric shape element bore”) and at least one further feature group, in particular on further geometric shape elements, for example on triangular shape elements, by means of which the tips of the star of the component 101 are defined.

Based on these data, in step S2 (b)) a feature group is selected from the set of all feature groups for these data, whereby in a particularly advantageous embodiment of a method the most frequently occurring feature group is selected.

A group of features is assigned to each of the respective feature groups, which at least partially define the component 101, with corresponding feature group data being assigned to each feature group. For example, a nominal diameter, a borehole depth and corresponding process parameters for the associated drilling machine are assigned to the feature group 106 "geometric shape element bore", which define how the bore is to be produced, how the workpiece is to be clamped with which production aids, which tool is to be used to produce the bore and, for example, how the bore is to be checked afterwards with regard to its dimensional accuracy and shape and position tolerances. Alternatively or additionally, this can also include the provision of a machining program, for example an NC program, for machining and/or producing the bore and/or the creation of a testing process. The processing program and/or the test process can also be created and created manually, partially automatically or fully automatically, whereby in one possible embodiment the processing program and/or the test process can be created and/or created based on one or more already known processing programs and/or test processes of the associated feature group or one or more comparable feature groups. If a comparable feature group is used as a basis for this, it can be particularly advantageous to select the feature group from the comparable feature groups that has the greatest frequency, i.e. occurs most frequently.

After the data for the feature groups 106 assigned to the component 101 and further feature groups have been provided, at least one feature group is selected from the feature groups for which data has been provided and the associated feature group data is provided (step (b) or S2).

The selection of the feature group in step b) or S2 is carried out in particular depending on a frequency distribution of the feature groups, whereby in particular the most frequently occurring feature group is selected.

In a further step, the respective feature group data are provided (step S3 or c)) and subsequently evaluated (step d) or S4) and at least one variable characteristic of the selected feature group, i.e. in particular a key figure characteristic of the feature group, for example a scrap rate, is determined.

In a further step S5 or e), the determined characteristic variable in this embodiment of a method according to the invention is stored, in particular in the data storage 140 in the cloud 110, output and further processed.

The output is made in particular by the determined key figure or the value of the determined characteristic quantity being displayed on a display device or being reproduced by means of a display device.

During further processing, the data processing device 130 is used to check whether the value determined in step d) or S4 lies within a permissible limit range.

If not, a corresponding measure is initiated in step S6 or f), in particular at least one parameter value of the associated feature group data is changed and/or added in order to facilitate the operation of the production system, in particular in particular the control of the production system, to adapt, in particular to improve. For example, one or more process parameters and/or machine tool control parameters of a machine tool can be changed if a scrap rate of an associated manufacturing step on a machine tool for a machining process when machining a shaped element is above a permissible limit value.

In a further step S7 or g), the changed or added parameter value(s) are stored, in particular in the data storage 140 centrally in the cloud 110, in particular together with information about the associated change(s).

Furthermore, for a particularly advantageous operation of the production system 100, during operation of the production system in step S8 or h) before starting a work process at one of the work stations 10 to 30 or 50 to 90 for processing the form element 106, a data consistency is checked, wherein for this purpose the data provided locally at or in the work station 10 to 30 or 50 to 90 for processing the form element 106 are at least partially compared with the centrally stored data, wherein in the event of a data inconsistency the work process for processing the form element 106 is at least temporarily blocked and/or stopped and/or terminated.

Let us assume that feature group 106 (“geometric form element hole”) is the most frequently occurring feature group from the feature groups for which data was provided in step a) or S1. Then, after this feature group 106 has been selected, the associated feature group data is evaluated and analyzed.

A characteristic value can be, for example, the scrap rate of the last 4 weeks. One result of this analysis can be, for example, that in the production of hole 106, i.e. in the production of the geometric form element hole 106, a current, determined scrap rate of production of the last 4 weeks, which can be determined from the operating data recorded and assigned to the form element, is 10%, but the average scrap rate of the last year was 5%.

If a maximum scrap rate of, for example, 7% is permitted, appropriate measures are initiated to reduce the scrap rate again. In particular, the control of the production system 100 is adjusted, with at least one control variable, i.e. a parameter for controlling the production system, which in particular affects the scrap rate of the associated feature group “form element bore” 106, being adjusted or changed. For example, a cutting speed, a selected tool, a feed rate or the like can be adjusted.

The change is stored centrally and distributed to all affected workstations on which the form element 106 is processed within the production system.

Before starting a work process at one of the work stations 10 to 30 or 50 to 90 for processing the form element 106, data consistency is checked in each case, whereby the data provided locally at or in the work station 10 to 30 or 50 to 90 for processing the feature group 106 is at least partially compared with the centrally stored data, whereby in the event of a data inconsistency the work process for processing the form element 106 is at least temporarily blocked and/or stopped and/or terminated.

• S1A: a) Bereitstellen von Daten, die einem oder mehreren Bauteilen 101 zugeordnet sind, wobei die Daten Informationen enthalten zu zwei oder mehr Merkmalsgruppen 106, die jeweils einem oder mehreren Bauteilen 101 zugeordnet sind, wobei jedem Bauteil 101, zu dem Daten bereitgestellt werden, wenigstens eine Merkmalsgruppe 106 zugeordnet ist, wobei eine Merkmalsgruppe 106 jeweils eine Gruppe von Merkmalen umfasst, welche das Bauteil 101, dem die Merkmalsgruppe 106 zugeordnet ist, zumindest teilweise definieren, und wobei jeder Merkmalsgruppe 106 Merkmalsgruppendaten zugeordnet sind,
• S2A: b) Auswählen wenigstens einer Merkmalsgruppe 106,
• S3A: c1) Ändern wenigstens eines Parameterwertes der bereitgestellten Merkmalsgruppendaten,
• S4A: d1) Aktualisieren der Merkmalsgruppendaten von zumindest einigen Bauteilen 101, vorzugsweise von allen Bauteilen, denen die Merkmalsgruppe 106 mit den Merkmalsgruppendaten zugeordnet ist, von der wenigstens eine Parameterwert geändert worden ist.

4 shows a flow chart with method steps of another possible, particularly advantageous method for use in a computer-aided production system, wherein this example of an advantageous method for a production system comprises the following steps, which can be carried out in particular in addition to or as an alternative to a method according to the invention:

• S1A: a) providing data that is assigned to one or more components 101, wherein the data contains information about two or more feature groups 106, each of which is assigned to one or more components 101, wherein each component 101 for which data is provided is assigned at least one feature group 106, wherein a feature group 106 comprises a group of features that at least partially define the component 101 to which the feature group 106 is assigned, and wherein each feature group 106 is assigned feature group data,
• S2A: b) selecting at least one feature group 106,
• S3A: c1) Changing at least one parameter value of the provided feature group data,
• S4A: d1) Updating the feature group data of at least some components 101, preferably of all components to which the feature parameter group 106 is assigned to the feature group data, of which at least one parameter value has been changed.

These procedural steps enable a particularly efficient implementation of changes, in particular an efficient and revision- or version-controlled implementation and documentation of changes to a large number of components with little change effort and little memory requirement, since the changes only have to be made to the associated feature group 106, but not to each component 101.

In the production system 100, the method steps described above are each carried out using the data processing device 130.

5 shows the reference form elements or the feature groups “Hole” and “Cuboid” of the component from 1 in an enlarged view, wherein the component 101 is assigned not only the first feature group 106 “geometric shape element bore” but also in particular a second feature group 109 “geometric shape element cuboid”.

6 shows an exemplary, schematic representation of a possible assignment of feature group data to feature groups 106, 109 or a combination of feature groups and/or to a component 101. In addition to feature groups 106, 109, which include or represent geometric form elements, other feature groups and feature group data can also be assigned to the component, such as feature groups with feature group data of category 107 (“Components/year”), 108 (“Number/type of feature groups”), 111 (“Material”), 112 (“Key figures/KPIs”) and other categories in the form of main and subcategories 113 (main category “Test and production process data”), 114 (subcategory “Production resources and production aids”), 115 (subcategory “Strategy/production organization”) and 116 (subcategory “Test and production parameters”).

7 shows an example of a first frequency distribution of feature groups, here geometric form elements, of components that are processed by the associated production system 100, determined for the production system 100, wherein the most frequent feature group is of the type “bore” and in particular makes up about 50% of all feature groups.

8th shows the frequency distribution of 7 , highlighting those geometric form elements which represent approximately 80% of all form elements processed in the production system.

An optimization of the most frequent feature group would therefore affect more than the 20% that are only intended to be optimized in order to adapt the production system to maximum efficiency. A change in the feature group definitions is therefore necessary in order to obtain a more suitable "resolution" of the feature groups. To this end, the method steps S1 to S8 according to the invention are repeated iteratively until a frequency distribution of the feature groups is established that approaches a Zipf distribution function in particular.

Once this has been achieved and the most relevant feature groups for the production system have been identified and each of these feature groups can be assigned a unique process within the CAx chain, the production system can then be optimized with little effort.

9 shows a schematic representation of the curve of a Zipf distribution, i.e. a frequency distribution that follows Zipf's law.

10 shows a table with the functional variables underlying a Zipf frequency distribution and their relationship, in particular the occurrence of the probabilities of the first 10 ranks when the frequency at rank 1 is 10%.

11 shows example data of a Zipf distribution. With such a frequency distribution, the first 10 ranks of feature groups represent approximately 30% of all feature groups, which therefore represents a suitable "resolution" of a frequency distribution. If the most relevant feature groups for the production system have been identified with a suitable "resolution" and each of these feature groups can be assigned a unique process within the CAx chain, the production system can then be optimized with little effort.

This means that the frequency distribution determined in a first step from 7 is adapted in an embodiment of a method according to the present invention by repeating the method steps, for example by adding and/or changing feature group data, which in particular enable a division into further sub-feature groups, until a frequency distribution according to Zipf's law is established. The frequency distribution according to Zipf's law appears to apply to most production systems.

It has been shown that with a basic set of approximately 60,000 form elements in a company, approximately the most common 1,600 form elements are crucial for efficient control of the production system, in particular for efficient standardization and optimization of the production system, especially for an improvement of 80% of the machining processes in production planning.

12 shows a table with example data on the frequency distribution of various feature groups, here of various geometric form elements 1 to 20, which are processed in a computer-aided production system 100, whereby the form elements are sorted by rank depending on their frequency. Form element 1 ("bore") has a frequency of more than 22%. However, this is not yet meaningful because no clear manufacturing process is assigned to the form element.

By adding the nominal diameter and dividing it into sub-feature groups of form elements XY to XZ and determining the frequency distribution with the "new" feature groups, the resolution is significantly improved and the form element of the "bore" type with a respective nominal diameter can be identified which occurs most frequently among the form elements of the "bore" type. A clear manufacturing process can now also be assigned to this. This is therefore the most relevant and has the greatest potential for improvement with regard to the control or operation of the production system (here: form element XY). This is done using 13 which shows a table for the frequency distribution of sub-form elements X... of the form element 1 that can be processed in the computer-aided production system 100, with the sub-form elements being sorted by rank depending on their frequency. This example shows that in the underlying production system to which the data belongs, even when broken down into sub-form elements with just ten data sets or feature groups and feature group data, 20% of all processes are already recorded in the CIM architecture of the production system. Since the sub-form elements have the same effect as the higher-level form elements (exponentially decreasing frequency distribution), 20% of the total expenditure in the CIM architecture can be covered with just a few sub-form elements, in this case with just 10.

• - der Häufigkeit aller Formelemente pro Arbeitsschritt/Arbeitsplan/Bauteil/Baugruppe/Produkt/Jahr,
• - der Herstellungsdauer jedes einzelnen Formelementes und der kumulierten Herstelldauer eines Formelements/Bauteils/Baugruppe/Produkt/Jahr,
• - der Herstellkosten jedes einzelnen Formelements und der kumulierten Kosten pro Formelement/Bauteil/Baugruppe/Produkt/Jahr,
• - einer formelementbezogenen Ausschussquote, welche ein Maß für die Prozessrobustheit ist, sowie der kumulierten Ausschussquote pro Formelement/Bauteil/Baugruppe/Produkt/Jahr, und/oder
• - einem Revisionsstatus.

It is particularly advantageous to evaluate the data depending on

• - the frequency of all form elements per work step/work plan/component/assembly/product/year,
• - the manufacturing time of each individual mold element and the cumulative manufacturing time of a mold element/component/assembly/product/year,
• - the manufacturing costs of each individual mold element and the cumulative costs per mold element/component/assembly/product/year,
• - a scrap rate related to the mold element, which is a measure of the process robustness, as well as the cumulative scrap rate per mold element/component/assembly/product/year, and/or
• - a revision status.

The set of form elements assigned to a component can in particular define the component. The set of components assigned to an assembly can in particular define the assembly. The set of assemblies assigned to a product can in particular define the product. The costs and/or capacities of a product can in particular be defined by associated form elements or associated feature groups and the associated feature group data. The cumulative amount of the costs of each individual form element can define the costs of work step/work plan/component/assembly/product/year via the feature groups.

This means that 80% of all process-related expenditures in the CIM architecture of the associated production system can be identified using 20% of the form elements sorted by frequency.

14 shows the frequency distribution of the formula elements from the 7 and 8th with form elements or feature groups divided into sub-form elements.

15 shows a schematic curve of the frequency distribution from 14 for the frequency distribution of the feature group “geometric form element” across the associated geometric form elements sorted by rank, whereby the approximation to the Zipf distribution function can be seen here. With 20% of the feature groups, an area of about 80% under the curve can be covered.

16 shows a schematic curve of a frequency distribution for the frequency distribution of the feature group “geometric form element x lead time”, over the associated geometric form elements sorted by rank, which corresponds to the representation of the cumulative lead time 20% of the feature groups (the associated form elements) are responsible for about 80% of the throughput time (area under the curve up to the 20% limit).

17 shows a schematic curve of the frequency distribution from 14 for the frequency distribution of the feature group "geometric form element x costs" across the associated geometric form elements sorted by rank, which corresponds to the representation of the cumulative costs. 20% of the feature groups (of the associated form elements) are responsible for about 80% of the costs (area under the curve up to the 20% limit).

18 shows a schematic diagram of an embodiment of the interface organization and of possible data and information flows between the various workstations 10, 20 and 30 of a production system 100 according to the invention, wherein a feature group reference template TRef (feature group reference data set, cf. 5 ) in particular be associated with a CAD workstation 10 and the associated data initially be forwarded to this after a change. From there, the data, in particular the changed data, can be forwarded to a CAM station 20 and from there assigned, for example, as component reference data DRef to all components to which the respective feature group is assigned. At a test station 30, the component target data 101target and the component actual data 101actual meet and measures derived from these can be fed back in the form of data changes to the feature group data into the feature group reference data TRef and, for example, into the process data or the processing data of the individual workstations 10, 20 and 30.

19 shows another schematic diagram for an embodiment of possible data and information flows starting from a feature group reference template (feature group reference data set) to various CAx workstations of a production system according to the invention, whereby this schematic diagram shows in particular an update process, in particular the feature group-related data update, which can also be referred to as feature group-related process revision. The vertical chain represents the processes of the CAx chain CAD-CAM-CAQ.

An advantageous production system can also be designed to carry out a duplication step so that at least one (reference) feature group and its associated feature group data can be at least partially duplicated or copied. Optionally, the production system can also be designed to carry out an adaptation step to adapt the copied feature group (template) and/or its feature group data in order to create a new feature group. In particular, the "copying" of the position and orientation of an object, in particular a form element, of geometric bodies, associated features, associated machine (machining) features and/or parameters, appears to be advantageous.

It can be particularly advantageous if a bidirectional link (relation) is maintained between the original feature group (template) and the new feature group generated based on the feature group template. This enables particularly efficient revision, for example starting from the reference feature group for all "dependent" feature groups generated based on the reference feature group and vice versa. This means that if a change is required to the new feature group, this can be integrated into the feature group template and, if necessary, via this into all dependent feature groups.

MORE IMPLEMENTATION EXAMPLES

• Nr. 1: Ein computerimplementiertes Verfahren, vorzugsweise zur Verwendung in einem computergestützten Produktionssystem, insbesondere zum Betrieb eines computergestützten Produktionssystems und/oder zur Steuerung eines computergestützten Produktionssystems, wobei insbesondere wenigstens ein Verfahrensschritt mithilfe einer Datenverarbeitungsvorrichtung und/oder mit Hilfe eines Computersystems ausgeführt wird, und wobei das Verfahren die folgenden Schritte umfasst:
  1. a) Bereitstellen von Daten, die einem oder mehreren Bauteilen zugeordnet sind, wobei die Daten Informationen enthalten zu zwei oder mehr Merkmalsgruppen, die einem oder mehreren Bauteilen zugeordnet sind, wobei jedem Bauteil, zu dem Daten bereitgestellt werden, wenigstens eine Merkmalsgruppe zugeordnet ist, wobei eine Merkmalsgruppe jeweils eine Gruppe von Merkmalen umfasst, welche das Bauteil, dem die Merkmalsgruppe zugeordnet ist, zumindest teilweise definieren, und wobei jeder Merkmalsgruppe Merkmalsgruppendaten zugeordnet sind,
  2. b) Auswählen wenigstens einer Merkmalsgruppe,
  3. c) Bereitstellen von zumindest einem Teil der Merkmalsgruppendaten, die der wenigstens einen ausgewählten Merkmalsgruppe zugeordnet sind,
  4. d) Auswerten der bereitgestellten Merkmalsgruppendaten und Bestimmen eines Wertes wenigstens einer für die ausgewählte Merkmalsgruppe charakteristischen Größe,
  5. e) Speichern, Ausgeben und/oder Weiterverarbeiten des in Schritt d) wenigstens einen ermittelten Wertes.
• Nr. 2: Ein computerimplementiertes Verfahren nach Nr. 1, wobei vor dem Bereitstellen von Daten in Schritt a) ein Erfassen von Daten erfolgt, vorzugsweise in einem separaten Schritt, insbesondere zum Erfassen der bereitzustellenden Daten, vorzugsweise unter Verwendung einer oder mehrerer Sensoreinrichtungen.
• Nr. 3: Ein computerimplementiertes Verfahren nach Nr. 1 oder 2, wobei vor dem Bereitstellen von Daten in Schritt a) verfügbare Daten (hinterlegte/gespeicherte oder erfasste Daten) einem oder mehreren Bauteilen zugeordnet werden, wobei die Daten insbesondere Informationen zu einer oder mehreren Merkmalsgruppen enthalten.
• Nr. 4: Ein computerimplementiertes Verfahren nach Nr. 3, wobei jedem Bauteil insbesondere jeweils wenigstens eine Merkmalsgruppe zugeordnet wird, vorzugsweise zumindest teilautomatisiert, insbesondere mithilfe entsprechender vordefinierter Referenz-Merkmalsgruppen, welche mit dem Bauteil verglichen werden, wobei bei ausreichender Übereinstimmung, dem Bauteil die ausreichend übereinstimmende Merkmalsgruppe zugeordnet wird.
• Nr. 5: Ein computerimplementiertes Verfahren nach Nr. 1 bis 4, wobei die Merkmalsgruppendaten mit der zugehörigen Merkmalsgruppe verknüpft sind oder mit der zugehörigen Merkmalsgruppe und dem Bauteil, welchem die zugehörige Merkmalsgruppe zugeordnet ist.
• Nr. 6: Ein computerimplementiertes Verfahren nach Nr. 1 bis 5, wobei eine Merkmalsgruppe insbesondere eine Gruppe von Merkmalen zu einem geometrischen Formelement, insbesondere einem geometrischen Grundkörper, aufweist und die zugehörigen Merkmalsgruppendaten wenigstens das Formelement charakterisieren und/oder definieren.
• Nr. 7: Ein computerimplementiertes Verfahren nach Nr. 6, wobei ein geometrisches Formelement insbesondere eine Bohrung, ein Langloch, ein Gewinde, ein Zapfen, ein Zylinder, eine ebene Fläche, ein Quader, eine Fase, ein Kegel, ein Kegelstumpf, eine Nut, eine Kugel, ein Kugelabschnitt, ein Kreis, ein Kreisabschnitt oder dergleichen aufweist oder ist oder zumindest teilweise aus einer Kombination aus diesen gebildet oder definiert ist.
• Nr. 8: Ein computerimplementiertes Verfahren nach Nr. 1 bis 7, wobei die Merkmalsgruppendaten Konstruktionsdaten (geometrische Daten, Abmessungen, Toleranzen, Gewicht, Material, ...), administrative Daten (Bestellnummer, Teilenummer, Identifikationsnummer, sonstiges Wiedererkennungsattribut, ...), Fertigungsdaten (Vorschubgeschwindigkeit, Schnittgeschwindigkeit, Werkzeugdaten, NC-Programm, ...), Produktionsdaten (tatsächliche Fertigungsdaten, Durchlaufzeiten, ...), Prüfdaten, Kosteninformationen, Planungsdaten oder sonstige Daten, insbesondere physikalische oder wirtschaftliche Daten, sein können.
• Nr. 9: Ein computerimplementiertes Verfahren nach Nr. 1 bis 8, wobei eine Merkmalsgruppe eine Kombination von Merkmals(unter)gruppen umfasst oder ist, beispielsweise eine Kombination aus den Merkmalsgruppen „geometrisches Formelement“ und „Kosten“ oder „geometrisches Formelement“ und „Durchlaufzeit“ oder „geometrisches Formelement“ und „Ausschussquote“, wobei wenigstens eine Merkmalsgruppe und/oder Merkmals(unter)gruppe insbesondere stets ein „geometrisches Formelement“ ist, und wobei jede Merkmalsuntergruppe insbesondere auch eine Merkmalsgruppe ist oder sein kann und insbesondere in Schritt b) ausgewählt werden kann.
• Nr. 10: Ein computerimplementiertes Verfahren nach Nr. 1 bis 9, wobei einem Bauteil mehrere Merkmalsgruppen und/oder Merkmalsuntergruppen zugeordnet sind, wobei die Merkmalsgruppen und/oder Merkmalsuntergruppen insbesondere verschieden sind und/oder ein- und derselben Haupt-Merkmalsgruppe angehören.
• Nr. 11: Ein computerimplementiertes Verfahren nach Nr. 10, wobei eine Haupt-Merkmalsgruppe durch das geometrische Formelement „Bohrung“ gebildet wird und eine Unter-Merkmalsgruppe insbesondere eine Merkmalsgruppe „Bohrung mit einem definierten Nenndurchmesser“ ist.
• Nr. 12: Ein computerimplementiertes Verfahren nach Nr. 1 bis 11, wobei die Schritte c), d), e) in der folgenden Reihenfolge durchgeführt werden: c), d) und e).
• Nr. 13: Ein computerimplementiertes Verfahren nach Nr. 1 bis 12, wobei wenigstens die Schritte c) und d) wenigstens einmal wiederholt werden, wobei die Auswahl der Merkmalsgruppe in Schritt c) des zweiten Zyklus insbesondere basierend auf dem Ergebnis der Auswertung aus Schritt e) des ersten Zyklus basiert.
• Nr. 14: Ein computerimplementiertes Verfahren nach Nr. 1 bis 13, wobei in einem weiteren Schritt c1) ein Ändern wenigstens eines Parameterwertes der bereitgestellten Merkmalsgruppendaten erfolgt und vorzugsweise, insbesondere ebenfalls in einem weiteren Schritt d1), ein Aktualisieren der Merkmalsgruppendaten von zumindest einigen Bauteilen, vorzugsweise von allen Bauteilen, denen die Merkmalsgruppe mit den Merkmalsgruppendaten zugeordnet ist, von der wenigstens eine Parameterwert geändert worden ist.
• Nr. 15: Ein computerimplementiertes Verfahren nach Nr. 1 bis 14, insbesondere nach Nr. 14, wobei die Merkmalsgruppendaten einer Merkmalsgruppe in regelmäßigen Abständen aktualisiert werden, wobei insbesondere nach jeder von einem Bearbeiter an einer Bearbeitungsstation vorgenommenen Änderung an den Merkmalsgruppendaten, eine produktionssystemweite Änderung vorgeschlagen wird, welche nach erfolgreicher Freigabe produktionssystemweit verbindlich wird.
• Nr. 16: Ein computerimplementiertes Verfahren, vorzugsweise zur Verwendung in einem computergestützten Produktionssystem, insbesondere zum Betrieb eines computergestützten Produktionssystems und/oder zur Steuerung eines computergestützten Produktionssystems, wobei das Verfahren die folgenden Schritte umfasst und insbesondere wenigstens ein Verfahrensschritt mithilfe einer Datenverarbeitungsvorrichtung und/oder mit Hilfe eines Computersystems ausgeführt wird:
  1. a) Bereitstellen von Daten, die einem oder mehreren Bauteilen zugeordnet sind, wobei die Daten Informationen enthalten zu zwei oder mehr Merkmalsgruppen, die einem oder mehreren Bauteilen zugeordnet sind, wobei jedem Bauteil, zu dem Daten bereitgestellt werden, wenigstens eine Merkmalsgruppe zugeordnet ist, und wobei jeder Merkmalsgruppe Merkmalsgruppendaten zugeordnet sind,
  2. b) Auswählen wenigstens einer Merkmalsgruppe,
  3. c1) Ändern wenigstens eines Parameterwertes der bereitgestellten Merkmalsgruppendaten,
  4. d1) Aktualisieren der Merkmalsgruppendaten von zumindest einigen Bauteilen, vorzugsweise von allen Bauteilen, denen die Merkmalsgruppe mit den Merkmalsgruppendaten zugeordnet ist, von der wenigstens eine Parameterwert geändert worden ist.
• Nr. 17: Ein computergestütztes Produktionssystem zur Durchführung eines Verfahrens nach Nr. 1 bis 16.
• Nr. 18: Ein computergestütztes Produktionssystem nach Nr. 17, wobei das Produktionssystem eine oder mehrere Arbeitsstationen aufweist, wobei die Arbeitsstationen insbesondere miteinander kommunikationsvernetzt sind (drahtlos und/oder drahtgebunden).
• Nr. 19: Ein computergestütztes Produktionssystem nach Nr. 17 oder 18, wobei das Produktionssystem wenigstens eine Datenverarbeitungsvorrichtung und/oder ein wenigstens ein Computersystem aufweist.
• Nr. 20: Ein computergestütztes Produktionssystem nach Nr. 17 bis 19, wobei das Produktionssystem dazu konfiguriert ist, während des Betriebs Produktionssystemdaten zu erfassen und zu speichern.
• Nr. 21: Ein computergestütztes Produktionssystem nach Nr. 17 bis 20, wobei das Produktionssystem dazu konfiguriert ist, Produktionssystemdaten, insbesondere während des Betriebs erfasste Produktionssystemdaten, zumindest teilweise merkmalsgruppenspezifisch oder merkmalsgruppenbezogen zuzuordnen, insbesondere formelementbezogen, und vorzugsweise zumindest teilautomatisiert, vorzugsweise vollautomatisiert.
• Nr. 22: Ein computergestütztes Produktionssystem nach Nr. 21, wobei das Produktionssystem dazu konfiguriert ist, im Zusammenhang mit der Bearbeitung eines Bauteils, insbesondere während der Bearbeitung eines Bauteils erfasste Produktionssystemdaten, merkmalsgruppenspezifisch und/oder merkmalsgruppenbezogen zuzuordnen zu der oder den Merkmalsgruppe(n), die dem Bauteil zugeordnet sind, insbesondere formelementbezogen, d.h. zu den Formelementen, welche dem Bauteil zugeordnet sind.
• Nr. 23: Ein computergestütztes Produktionssystem nach Nr. 17 bis 22, wobei das Produktionssystem dazu konfiguriert ist, Informationen über die letzte Änderung und/oder die Änderungshistorie von zumindest einigen der Merkmalsgruppendaten anzuzeigen.
• Nr. 24: Ein computergestütztes Produktionssystem nach Nr. 17 bis 23, wobei das Produktionssystem wenigstens eine Anzeigevorrichtung zur Anzeige von Merkmalsgruppendaten und/oder von Änderungsinformationen zu den Merkmalsgruppendaten aufweist, vorzugsweise an jeder Arbeitsstation.
• Nr. 25: Ein computergestütztes Produktionssystem nach Nr. 17 bis 24, wobei das Produktionssystem ein Produktionsdatenmanagementsystem umfasst, insbesondere zur Verwaltung der Bauteildaten, der innerhalb des Produktionssystems bearbeitbaren Bauteile und/oder zur Verwaltung der Merkmalsgruppendaten, wobei das Produktionssystem insbesondere dazu eingerichtet ist, die Daten zentral zu speichern, vorzugsweise auf wenigstens einem Server, insbesondere auf wenigstens einem Server der Teil des Produktionssystems ist und sich insbesondere mit wenigstens einer Arbeitsstation im selben Netzwerk befindet, und/oder auf einem externen Server in einer Cloud.
• Nr. 26: Ein computergestütztes Produktionssystem nach Nr. 17 bis 25, wobei das Produktionssystem konfiguriert ist, vor einem Start eines Arbeitsprozesses an einer Arbeitsstation des Produktionssystems zur Bearbeitung eines Bauteils, die lokal an oder in der Arbeitsstation für die Bearbeitung des Bauteils bereitgestellten Daten mit den zentral im Produktionsdatenmanagementsystem gespeicherten Daten zumindest teilweise zu vergleichen, wobei das Produktionssystem ferner insbesondere konfiguriert ist, bei einer Dateninkonsistenz insbesondere der Arbeitsvorgang zur Bearbeitung des Bauteils zumindest vorübergehend zu sperren und/oder anzuhalten und/oder zu beenden.
• Nr. 27: Ein computergestütztes Produktionssystem nach Nr. 17 bis 26, wobei das Produktionssystem eine Auswerteeinrichtung aufweist, insbesondere eine Auswerte- und Anzeigeeinrichtung, welche für eine merkmalsgruppenbezogene Auswertung von Bauteil- und/oder Produktionssystemdaten eingerichtet ist, insbesondere für eine formelementbezogene Auswertung von Bauteil- und/oder Produktionssystemdaten.
• Nr. 28: Ein computergestütztes Produktionssystem nach Nr. 27, wobei die Auswerteinrichtung dazu konfiguriert ist, Produktionssystemdaten merkmalsgruppenbezogen, insbesondere formelementbezogen, nach Häufigkeit, Kosten, Ressourcen bzw. Kapazitätsbedarf und Prozesssicherheit bzw. Robustheit und/oder Ausschussquote, insbesondere je Merkmalsgruppe, vorzugsweise je Formelement, auszuwerten.
• Nr. 29: Ein computergestütztes Produktionssystem nach Nr. 28, wobei die Auswerteinrichtung dazu eingerichtet ist, Merkmalsgruppen danach zu unterscheiden, insbesondere Formelemente, ob diese eine Bearbeitung, insbesondere einen physischen Bearbeitungsschritt erfordern oder nicht.
• Nr. 30: Ein computergestütztes Produktionssystem nach Nr. 17 bis 29, wobei das Produktionssystem eine Auswerteeinrichtung aufweist, insbesondere eine Auswerte- und Anzeigeeinrichtung, welche konfiguriert ist, eine bauteilspezifische Merkmalsgruppenstückliste, insbesondere eine bauteilspezifischen Formelementstückliste, zu erzeugen und insbesondere auszugeben und/oder zu speichern, vorzugsweise inklusive zugehöriger Änderungsinformationen.
• Nr. 31: Ein computergestütztes Produktionssystem nach Nr. 17 bis 30, wobei das Produktionssystem eine Auswerteeinrichtung aufweist, insbesondere eine Auswerte- und Anzeigeeinrichtung, welche für eine merkmalsgruppenbezogene Kapazitätsbedarfs- und/oder Kostenkalkulation eingerichtet ist, insbesondere für eine formelementbezogene Kapazitätsbedarfs- und/oder Kostenkalkulation.
• Nr. 32: Ein Computerprogramm, wobei das Computerprogramm Befehle umfasst, die bei der Ausführung des Programms durch einen Computer diesen veranlassen, ein Verfahren nach einem der Nr. 1 bis 16 auszuführen.
• Nr. 33: Ein Computerlesbares Speichermedium, wobei auf dem computerlesbaren Speichermedium ein Computerprogramm nach Nr. 32 gespeichert ist, das Befehle umfasst, die bei der Ausführung des Programms durch einen Computer diesen veranlassen, ein Verfahren nach einer der Nr. 1 bis 16 auszuführen.
• Nr. 34: Datenverarbeitungsvorrichtung, insbesondere ein Computer oder eine Steuervorrichtung für ein Produktionssystem nach einer der Nr. 17 bis 31, umfassend Mittel zur Ausführung des Verfahrens nach einer der Nr. 1 bis 16.

Further examples may be:

• No. 1: A computer-implemented method, preferably for use in a computer-aided production system, in particular for operating a computer-aided production system and/or for controlling a computer-aided production system, wherein in particular at least one method step is carried out with the aid of a data processing device and/or with the aid of a computer system, and wherein the method comprises the following steps:
  1. a) providing data that is associated with one or more components, the data containing information on two or more feature groups that are associated with one or more components, each component for which data is provided being associated with at least one feature group, each feature group comprising a group of features that at least partially define the component to which the feature group is associated, and each feature group being associated with feature group data,
  2. b) selecting at least one group of characteristics,
  3. c) providing at least part of the feature group data that the at least are assigned to a selected feature group,
  4. d) evaluating the provided feature group data and determining a value of at least one characteristic quantity for the selected feature group,
  5. e) storing, outputting and/or further processing the at least one value determined in step d).
• No. 2: A computer-implemented method according to No. 1, wherein prior to the provision of data in step a), data is acquired, preferably in a separate step, in particular for acquiring the data to be provided, preferably using one or more sensor devices.
• No. 3: A computer-implemented method according to No. 1 or 2, wherein prior to the provision of data in step a), available data (deposited/stored or recorded data) are assigned to one or more components, wherein the data in particular contain information on one or more groups of features.
• No. 4: A computer-implemented method according to No. 3, wherein each component is assigned in particular at least one feature group, preferably at least partially automated, in particular with the aid of corresponding predefined reference feature groups, which are compared with the component, wherein, if there is sufficient agreement, the sufficiently matching feature group is assigned to the component.
• No. 5: A computer-implemented method according to Nos. 1 to 4, wherein the feature group data is linked to the associated feature group or to the associated feature group and the component to which the associated feature group is assigned.
• No. 6: A computer-implemented method according to Nos. 1 to 5, wherein a feature group in particular comprises a group of features for a geometric shape element, in particular a geometric basic body, and the associated feature group data characterize and/or define at least the shape element.
• No. 7: A computer-implemented method according to No. 6, wherein a geometric shape element in particular has or is a bore, an elongated hole, a thread, a pin, a cylinder, a flat surface, a cuboid, a chamfer, a cone, a truncated cone, a groove, a sphere, a sphere segment, a circle, a circle segment or the like, or is at least partially formed or defined from a combination of these.
• No. 8: A computer-implemented method according to Nos. 1 to 7, wherein the feature group data can be design data (geometric data, dimensions, tolerances, weight, material, ...), administrative data (order number, part number, identification number, other recognition attribute, ...), manufacturing data (feed rate, cutting speed, tool data, NC program, ...), production data (actual manufacturing data, throughput times, ...), test data, cost information, planning data or other data, in particular physical or economic data.
• No. 9: A computer-implemented method according to Nos. 1 to 8, wherein a feature group comprises or is a combination of feature (sub)groups, for example a combination of the feature groups “geometric shape element” and “costs” or “geometric shape element” and “throughput time” or “geometric shape element” and “rejection rate”, wherein at least one feature group and/or feature (sub)group is in particular always a “geometric shape element”, and wherein each feature subgroup is or can be in particular also a feature group and can in particular be selected in step b).
• No. 10: A computer-implemented method according to Nos. 1 to 9, wherein a component is assigned several feature groups and/or feature subgroups, wherein the feature groups and/or feature subgroups are in particular different and/or belong to one and the same main feature group.
• No. 11: A computer-implemented method according to No. 10, wherein a main feature group is formed by the geometric shape element “bore” and a sub-feature group is in particular a feature group “bore with a defined nominal diameter”.
• No. 12: A computer-implemented method according to Nos. 1 to 11, wherein steps c), d), e) are performed in the following order: c), d) and e).
• No. 13: A computer-implemented method according to Nos. 1 to 12, wherein at least steps c) and d) are repeated at least once, wherein the selection of the feature group in step c) of the second cycle is based in particular on the result of the evaluation from step e) of the first cycle.
• No. 14: A computer-implemented method according to Nos. 1 to 13, wherein in a further step c1) at least one parameter value of the provided feature group data is changed and preferably, in particular also in a further step d1), the feature group data of at least some components, preferably of all components, to which the feature group with the feature group data is assigned, of which at least one parameter value has been changed, is updated.
• No. 15: A computer-implemented method according to Nos. 1 to 14, in particular according to No. 14, wherein the feature group data of a feature group are updated at regular intervals, wherein in particular after each change to the feature group data made by an operator at a processing station, a production system-wide change is proposed, which becomes binding throughout the production system after successful release.
• No. 16: A computer-implemented method, preferably for use in a computer-aided production system, in particular for operating a computer-aided production system and/or for controlling a computer-aided production system, wherein the method comprises the following steps and in particular at least one method step is carried out with the aid of a data processing device and/or with the aid of a computer system:
  1. a) providing data associated with one or more components, the data containing information on two or more feature groups associated with one or more components, each component for which data is provided being associated with at least one feature group, and each feature group being associated with feature group data,
  2. b) selecting at least one group of characteristics,
  3. c1) changing at least one parameter value of the provided feature group data,
  4. d1) Updating the feature group data of at least some components, preferably of all components, to which the feature group with the feature group data is assigned, of which at least one parameter value has been changed.
• No. 17: A computer-aided production system for carrying out a process according to Nos. 1 to 16.
• No. 18: A computer-aided production system according to No. 17, wherein the production system has one or more workstations, wherein the workstations are in particular networked with one another for communication purposes (wireless and/or wired).
• No. 19: A computer-aided production system according to No. 17 or 18, wherein the production system comprises at least one data processing device and/or at least one computer system.
• No. 20: A computer-aided production system according to Nos. 17 to 19, wherein the production system is configured to collect and store production system data during operation.
• No. 21: A computer-aided production system according to Nos. 17 to 20, wherein the production system is configured to assign production system data, in particular production system data acquired during operation, at least partially in a feature group-specific or feature group-related manner, in particular in a form element-related manner, and preferably at least partially automated, preferably fully automated.
• No. 22: A computer-aided production system according to No. 21, wherein the production system is configured to assign production system data recorded in connection with the processing of a component, in particular during the processing of a component, in a feature group-specific and/or feature group-related manner to the feature group(s) assigned to the component, in particular in a form element-related manner, i.e. to the form elements assigned to the component.
• No. 23: A computer-aided production system according to Nos. 17 to 22, wherein the production system is configured to display information about the last change and/or the change history of at least some of the feature group data.
• No. 24: A computer-aided production system according to Nos. 17 to 23, wherein the production system has at least one display device for displaying feature group data and/or change information to the feature group data, preferably at each workstation.
• No. 25: A computer-aided production system according to Nos. 17 to 24, wherein the production system comprises a production data management system, in particular for managing the component data, the components that can be processed within the production system and/or for managing the feature group data, wherein the production system is in particular designed to store the data centrally, preferably on at least one server, in particular on at least one server that is part of the production system and is in particular located in the same network as at least one workstation, and/or on an external server in a cloud.
• No. 26: A computer-aided production system according to Nos. 17 to 25, wherein the production system is configured, before starting a work process at a workstation of the production system for processing a component, to at least partially compare the data provided locally at or in the workstation for processing the component with the data stored centrally in the production data management system, wherein the production system is further configured, in particular, to at least temporarily block and/or stop and/or terminate the work process for processing the component in the event of a data inconsistency.
• No. 27: A computer-aided production system according to Nos. 17 to 26, wherein the production system has an evaluation device, in particular an evaluation and display device, which is set up for a feature group-related evaluation of component and/or production system data, in particular for a form element-related evaluation of component and/or production system data.
• No. 28: A computer-aided production system according to No. 27, wherein the evaluation device is configured to evaluate production system data in relation to feature groups, in particular in relation to mold elements, according to frequency, costs, resources or capacity requirements and process reliability or robustness and/or scrap rate, in particular per feature group, preferably per mold element.
• No. 29: A computer-aided production system according to No. 28, wherein the evaluation device is designed to distinguish between groups of features, in particular form elements, according to whether they require processing, in particular a physical processing step, or not.
• No. 30: A computer-aided production system according to Nos. 17 to 29, wherein the production system has an evaluation device, in particular an evaluation and display device, which is configured to generate and in particular to output and/or store a component-specific feature group parts list, in particular a component-specific form element parts list, preferably including associated change information.
• No. 31: A computer-aided production system according to Nos. 17 to 30, wherein the production system has an evaluation device, in particular an evaluation and display device, which is set up for a feature group-related capacity requirement and/or cost calculation, in particular for a form element-related capacity requirement and/or cost calculation.
• No. 32: A computer program, the computer program comprising instructions which, when executed by a computer, cause the computer to carry out a method according to any one of Nos. 1 to 16.
• No. 33: A computer-readable storage medium, wherein a computer program according to No. 32 is stored on the computer-readable storage medium, which includes instructions which, when the program is executed by a computer, cause the computer to carry out a method according to one of Nos. 1 to 16.
• No. 34: Data processing device, in particular a computer or a control device for a production system according to one of Nos. 17 to 31, comprising means for carrying out the method according to one of Nos. 1 to 16.

Although some aspects have been described in the context of a device, in particular in connection with a production system and/or a data processing device, it is clear that these aspects also represent a description of the corresponding method, insofar as this is technically possible, wherein in particular a block or a device corresponds or can correspond in particular to a method step or a function of a method step. Analogously, aspects that are described in the context of a method step also represent a description of a corresponding block or element or a property of a corresponding device, insofar as this is technically possible.

This means in particular that the preferred embodiments presented with reference to the method described above and their advantages also apply accordingly to a production system according to the present invention as well as to a computer program, a computer-readable storage medium and a data processing device according to the present invention and vice versa, even if this is referred to the relevant person in this application, in particular in order to avoid repetition. The relevant passages are not explicitly described again.

The embodiments of the present invention can be implemented in a computer system and/or with the aid of a computer system, in particular with a computer system for a production system or with a computer system within a production system. The computer system can in particular comprise a data processing device according to the present invention or alternatively also be a part of it.

The computer system may be a local computing device (e.g., personal computer, laptop, tablet computer, or mobile phone) having one or more processors and one or more storage devices, or a distributed computing system (e.g., a cloud computing system having one or more processors or one or more storage devices distributed at different locations, e.g., at a local client and/or one or more remote server farms and/or data centers). The computer system may include any one or more such circuits, or one or more combinations of circuits. In one embodiment, the computer system may include one or more processors, which may be of any type. As used herein, processor may mean any type of computing circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set microprocessor (CISC), a reduced instruction set microprocessor (RISC), a very long instruction word (VLIW) microprocessor, a graphics processor, a digital signal processor (DSP), a multi-core processor, a field programmable gate array (FPGA), or any other type of processor or processing circuit. Other types of circuits that may be included in the computer system may be a custom-built circuit, an application specific integrated circuit (ASIC), or the like, such as one or more circuits (e.g., a communications circuit) for use with wireless devices such as cellular phones, tablet computers, laptop computers, two-way radios, and similar electronic systems.

The computer system may include one or more storage devices, which may include one or more storage elements suitable for the particular application, such as a main memory in the form of random access memory (RAM), one or more hard disks, and/or one or more drives handling removable media such as CDs, flash memory cards, DVDs, and the like. The computer system may also include a display device, one or more speakers, and a keyboard and/or controller, which may include a mouse, trackball, touch screen, voice recognition device, or any other device that allows a system user to enter information into and receive information from the computer system.

Some or all of the method steps may be performed by (or using) a hardware device, such as a processor, a microprocessor, a programmable computer, or an electronic circuit. In some embodiments, one or more of the key method steps may be performed by such a device.

Depending on specific implementation requirements, embodiments of the invention can be or are implemented in hardware or software. The implementation can be carried out with a non-volatile storage medium such as a digital storage medium, such as a floppy disk, a DVD, a Blu-Ray, a CD, a ROM, a PROM and EPROM, an EEPROM or a FLASH memory, on which electronically readable control signals are stored that interact (or can interact) with a programmable computer system, in particular a computer system according to the invention, and/or a data processing device, in particular a data processing device according to the invention, such that the respective method is carried out. Therefore, the digital storage medium can be computer-readable.

Some possible embodiments according to the invention comprise a computer-readable storage medium, in particular a data carrier, with electronically readable control signals that can interact with a programmable computer system, in particular a computer system according to the invention, and/or a data processing device, in particular a data processing device according to the invention, so that one of the methods described herein is carried out.

In general, embodiments of the present inventions, in particular embodiments of the method inventions, can be implemented as a computer program product with a program code, wherein the program code is effective for executing one of the methods when the computer program product is run on a computer ter runs. The program code can, for example, be stored on a machine-readable medium.

Further embodiments include a computer program for carrying out one of the methods described herein, which is stored on a machine-readable carrier.

In other words, an embodiment of the present invention may therefore be a computer program with a program code for carrying out one of the methods described herein, wherein the computer program runs on a computer.

A further possible embodiment of the present invention is therefore, for example, a storage medium (or a data carrier or a computer-readable medium) comprising a computer program stored thereon for carrying out one of the methods described herein when executed by a processor. The data carrier, the digital storage medium or the recorded medium is usually tangible and/or non-transparent. A further embodiment of the present invention can, for example, be a device as described herein, which comprises a processor and the storage medium.

A further embodiment of the invention can be a data stream or a signal sequence that represents the computer program for carrying out one of the methods described herein. The data stream or the signal sequence can, for example, be configured such that the transmission can or does take place via a data communication connection, for example via the Internet.

A data stream or a signal sequence that is transmitted via a data communication connection can also comprise only individual data or data packets of individual process steps and does not necessarily have to represent the computer program. For example, a data stream or a signal sequence can contain component and/or feature group data that is transmitted to a data processing device via a data communication connection to provide data in step a), for example via WLAN or LAN, in particular from one or more workstations and/or from one or more readable data memories of the production data management system to the data processing device.

Likewise, a data stream or a signal sequence can contain component and/or feature group data and/or one or more evaluation results and values determined during the evaluation in step d), which are transmitted via a data communication connection from a data processing device, for example via WLAN or LAN, in particular to one or more workstations and/or to one of the several data memories of the production data management system.

Another embodiment includes a processing means, for example a computer or a programmable logic device, configured or adapted to perform any of the methods described herein.

A further embodiment comprises a computer on which the computer program for carrying out one of the methods described herein is installed.

A further embodiment according to the invention comprises a device or system configured to transmit (e.g. electronically or optically) a computer program for carrying out one of the methods described herein to a recipient. The recipient may, for example, be a computer, a mobile device, a storage device or the like. The device or system may, for example, comprise a file server for transmitting the computer program to the recipient.

In some embodiments, a programmable logic device (e.g., a field programmable gate array, FPGA) may be used to perform some or all of the functionality of the methods described herein. In some embodiments, a field programmable gate array may cooperate with a microprocessor to perform any of the methods described herein. In general, the methods are preferably performed by any hardware device.

In addition to the described embodiments and examples of embodiment, further embodiments are possible, in particular of a constructive nature, without departing from the scope of protection defined by the patent claims.

LIST OF REFERENCE SYMBOLS

100

inventive production system

130

Data processing device according to the invention

140

Data storage (computer-readable storage medium according to the invention)

10

CAD workstation

20

CAM workstation

30

CAQ workstation

35

Production planning, especially product-specific

40

Production planning and control, especially order-related

50

Product program planning workstation

60

Quantity planning workstation

70

Scheduling and capacity planning workstation

80

Order monitoring workstation

90

Order initiation workstation

101

Component

101ist

Actual component

101 should

Target component

102

Data communication connection for data transmission

103

Data communication connection for data transmission

104

Data communication connection for data transmission

105

Data communication connection for data transmission

106

first feature group “geometric form element hole”

107

Feature group data category “Components/Year”

108

Feature group data category “Number/type of feature groups”

109

second feature group “geometric shape element cuboid”

110

Cloud

111

Feature group data category “Material”

112

Feature group data category “Key figures (KPls)”

113

Feature group data main category “Testing and manufacturing process”

114

Feature group data subcategory “Production equipment and production resources”

115

Feature group data subcategory “Strategy/Manufacturing Organization”

116

Feature group data subcategory “Test and production parameters”

120

Production Data Management System (PDMS)

DRef

Component reference data

S1..S8

Method steps of a first embodiment of a method according to the invention

S1A..S4A

Process steps of a further advantageous process

TRef

Feature group reference template (feature group reference data set)

QUOTES INCLUDED IN THE DESCRIPTION

This list of documents listed by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions.

Cited patent literature

• WO 2020204915 A1 [0006]
• WO 2019226167 A1 [0007]
• WO 2018083512 A1 [0008]
• WO 2016178107 A1 [0009]

Cited non-patent literature

• https://de.wikipedia.org/wiki/Computer-integrated_manufacturing, last accessed on October 3, 2022 [0003]
• A. Agovic, T. Trautner, F. Bleicher, Digital Transformation - Implementation of Drawingless Manufacturing: A Case Study, Procedia CIRP, Volume 107, 2022, Pages 1479-1484, ISSN 2212-8271, https://doi.org/10.1016/j.procir.2022.05.178 [0005]

Claims (14)

Computer-implemented method for use in a computer-aided production system (100), in particular for controlling an operation of the computer-aided production system (100), the method comprising at least the following steps: a) providing (S1) data that are assigned to one or more components (101), the data containing information on two or more feature groups (106, 109) that are assigned to one or more components (101), each component for which data is provided being assigned at least one feature group (106), each feature group (106) comprising a group of features that at least partially define the component (101) to which the feature group (106) is assigned, and each feature group (106) being assigned feature group data, b) selecting (S2) at least one feature group (106), c) providing (S3) at least part of the feature group data that are assigned to the at least one selected feature group, d) evaluating (S4) the provided feature group data and determining a value of at least one variable characteristic of the selected feature group, and e) storing, outputting and/or further processing (S5) the at least one value determined in step d). Procedure according to Claim 1 , wherein at least one feature group, in particular each feature group, has at least one geometric shape element and/or at least one feature dependent on a geometric shape element, wherein the associated feature group data in particular contain at least geometry and/or production data for the at least one geometric shape element. Procedure according to Claim 1 or 2 , wherein the selection of the at least one feature group is dependent on a frequency distribution of at least one of the parts of the feature groups. Method according to one of the Claims 1 until 3 , whereby the selection of the feature group is carried out with the help of Zipf's law based on the determined frequency distribution, whereby the feature groups are assigned a rank depending on their frequency according to Zipf's law and the feature group is selected depending on its rank. Method according to one of the Claims 1 until 4 , whereby in a further step it is checked whether the value determined in step d) lies within a predefined, permissible range of values. Method according to one of the Claims 1 until 5 , wherein in particular in a further step f), preferably depending on the value of the at least one characteristic variable determined in step c), at least one measure is initiated, wherein preferably at least one parameter value, in particular of at least one parameter of the feature group data of the at least one selected feature group, is changed and/or one or more parameters and their associated values are added to the data, in particular to the feature group data of the at least one selected feature group, wherein in particular a value of at least one control parameter for controlling the production system and/or at least one value of a component parameter is changed or added. Method according to one of the Claims 1 until 6 , wherein the changed parameter value and/or one or more parameters to be added and their parameter values as well as information about the associated change(s) are stored centrally in a production data management system (120). Method according to one of the Claims 1 until 7 , wherein the parameter value and/or one or more parameters to be added and their parameter values as well as information about the associated change(s) are changed across all components to which the at least one selected feature group is assigned. Method according to one of the Claims 1 until 8th , wherein, in particular during operation of the production system, before starting a work process at a work station (10, 20, 30, 50, ...90) of the production system for processing a component, the data provided locally at or in the work station for processing the component are at least partially compared with the data stored centrally in the production data management system (120), wherein in the event of a data inconsistency, in particular the work process for processing the component is at least temporarily blocked and/or stopped and/or terminated. Computer-aided production system (100), characterized in that the production system (100) is designed to carry out a method according to one of the Claims 1 until 9 is trained. Production system (100) according to Claim 10 , wherein the production system is further configured, before starting a work process at a workstation of the production system for processing a component, to at least partially compare the data provided locally at or in the workstation for processing the component with the data stored centrally in the production data management system, wherein the production system is further configured in particular to at least temporarily block and/or stop and/or terminate the work process for processing the component in the event of a data inconsistency. Computer program, wherein the computer program comprises instructions which, when the program is executed by a computer, cause the computer to carry out a method according to one of the Claims 1 until 9 to execute. Computer-readable storage medium, on which a computer-readable storage medium a computer program according to Claim 12 which comprises instructions which, when the program is executed by a computer, cause the computer to carry out a method according to one of the Claims 1 until 9 to execute. Data processing device, in particular a computer or a control device for a production system according to Claim 10 , comprising means for carrying out the method according to one of the Claims 1 until 9 .

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