KR20190066758A - Porcess assessment model for smart manufacturing - Google Patents

Abstract

Provided is a technology for process assessment model for smart manufacturing. According to embodiments of the present invention, a method of evaluating a data quality management process for smart manufacturing comprises the steps of: identifying processes associated with data quality management in the manufacturing process; evaluating the degree of achievement by a process attribute for each of the identified processes; and determining a capability level for each of the identified processes based on the evaluated degree of achievement by a process attribute for each of the identified processes.

Description

{PORCESS ASSESSMENT MODEL FOR SMART MANUFACTURING}

The following description relates to a process evaluation model technology for smart manufacturing, and more particularly to an evaluation method and an evaluation system for evaluating a data quality management process for smart manufacturing, and a computer- And more particularly to a computer program stored in a computer readable recording medium and a recording medium therefor.

Smart manufacturing means technology that actively applies information and communication technology to modern manufacturing processes and is revolutionizing the manufacturing industry economy around the world. The fifth industrial revolution that has emerged today is the era of "smart manufacturing", enabling the integration of more advanced digital technologies with production systems. The technologies involved include wireless communications technology, Internet of things, cloud computing, reprogrammable robots, and machine intelligence, which can connect the virtual world and the real world directly and in real time. For example, Korean Patent Laid-Open No. 10-2017-0087584 discloses a smart manufacturing system and method for producing customized products.

The key to smart manufacturing is how to acquire, manage, and use data as data. The data required here is to integrate sensors, controls, platforms and modeling technologies into commercial smart manufacturing systems using open source digital platforms and technology marketplaces as intelligent (smart) data rather than big data. Managing the quality of these data is critical, and it is also important to evaluate the data quality management process to achieve the quality control level for the data.

An evaluation method and an evaluation system for evaluating a data quality management process for smart manufacturing, and a computer program stored in a computer-readable recording medium for causing the computer to execute the evaluation method in combination with the computer.

An evaluation method and an evaluation system for evaluating a data quality management process in a shipbuilding process, and a computer program stored in a computer-readable recording medium for causing the computer to execute the evaluation method in combination with the computer.

A parameter processing method and parameter processing system for processing a parameter for process evaluation in a smart manufacturing environment and a computer program stored in a computer readable recording medium for causing the computer to execute the parameter processing method in combination with the computer, Lt; / RTI >

A method of evaluating a data quality management process for smart manufacturing, comprising: identifying processes associated with data quality management in a manufacturing process; Evaluating a degree of achievement by process attribute for each of the identified processes; And determining a capability level for each of the identified processes based on the evaluated degree of attainment per process attribute for each of the identified processes.

According to one aspect, the evaluation method includes classifying the identified processes by a plurality of maturity levels according to a processing order of processes; And determining the maturity level of the manufacturing process based on the maturity level at which the identified processes are classified and the capability level determined for each of the identified processes.

According to another aspect, the step of determining the maturity level of the manufacturing process may include determining a maturity level of each of the processes classified into the maturity level according to the capability level determined for each of the identified processes And the maximum maturity level is determined as the maturity level of the manufacturing process.

According to another aspect, the evaluation method further comprises the step of determining, based on the determined maturity level and the capability level determined for each of the identified processes, information about a process for which improvement is required, The method comprising the steps of:

According to another aspect, the providing step comprises the step of providing information on a process that fails to achieve a capability level corresponding to the exceeding maturity level among the processes classified into the maturity level exceeding the determined maturity level, And determines a process attribute corresponding to a capability level that the determined process does not achieve as a process attribute required to be improved.

According to another aspect, the degree of achievement according to the process attribute includes a degree of achievement of the predefined goal for each process attribute.

There is provided a computer program stored in a computer-readable medium for causing a computer to execute the evaluation method in combination with the computer.

There is provided a computer-readable recording medium having recorded thereon a program for causing a computer to execute the evaluation method.

An evaluation system for evaluating a data quality management process for smart manufacturing, comprising: a memory for storing computer readable instructions; And at least one processor configured to execute the instructions, wherein the at least one processor identifies processes associated with data quality management in the manufacturing process and determines a degree of achievement (degree) by process attribute for each of the identified processes of achievement of the identified processes and determining a capability level for each of the identified processes based on the evaluated degree of achievement per process attribute for each of the identified processes .

An evaluation method and an evaluation system for evaluating a data quality management process for smart manufacturing, and a computer program and its recording medium stored in a computer-readable recording medium in combination with a computer to execute the evaluation method on a computer .

An evaluation method and an evaluation system for evaluating a data quality management process in a shipbuilding process, and a computer program and its recording medium stored in a computer-readable recording medium for causing the computer to execute the evaluation method in combination with the computer .

A parameter processing method and parameter processing system for processing a parameter for process evaluation in a smart manufacturing environment and a computer program stored in a computer readable recording medium for causing the computer to execute the parameter processing method in combination with the computer, Can be provided.

1 is a diagram illustrating a relationship between embodiments of the present invention and data quality standards.
Figure 2 is an illustration of examples of standards tailored to the ISA 95 model.
3 is a diagram illustrating an example of shipbuilding processes in consideration of smart manufacturing, in an embodiment of the present invention.
4 is a diagram showing an example of the structure of a data quality management process in an embodiment of the present invention.
5 is a diagram showing an example of an organization maturity evaluation model in an embodiment of the present invention.
Figure 6 is an example of achieving maturity level 2 for smart manufacturing in one embodiment of the present invention.
7 is a block diagram for explaining an internal configuration of a computer apparatus according to an embodiment of the present invention.
8 is a flow chart illustrating an example of an evaluation method for evaluating a data quality management process for smart manufacturing, in an embodiment of the present invention.
9 is a flowchart showing an example of an evaluation method for evaluating a data quality management process in a shipbuilding process in an embodiment of the present invention.
10 is a flow chart illustrating an example of a method of processing parameters of a data quality management process for smart manufacturing, in an embodiment of the present invention.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings.

Embodiments of the present invention define a data quality management process maturity evaluation for smart manufacturing. For example, a process evaluation model for smart manufacturing based on the process reference model of the ISO 8000-61 standard and the maturity assessment model of the ISO 8000-62 standard can be provided.

The ability to generate, collect, store, maintain, transmit, process and present data to support business processes in a timely and cost-effective manner requires understanding the nature of the data that determines quality, Management, and reporting.

The ISO 8000 standard defines the characteristics that can represent data quality and provides methods for managing, measuring and improving the quality of general data, master data and product data. The ISO 8000 standard can be used independently or in conjunction with a quality management system.

A data-centric approach to correcting only data for which nonconformity is found has limitations in improving data quality. Tracking and correcting data incompatibility and related data or eliminating the root cause of data inconsistency through a data quality management (DQM) process can prevent the recurrence of the same type of data incompatibility. Therefore, a framework for process-oriented DQM is required to improve data quality more effectively and efficiently. It also improves the quality of the data by complementing the vulnerable processes found in the process evaluation and by evaluating the process.

To this end, embodiments of the present invention provide techniques for defining a data quality management process maturity assessment for smart manufacturing and are based on the process reference model of the ISO 8000-61 standard and the maturity assessment model of the ISO 8000-62 standard Process evaluation model for smart manufacturing. These techniques can be utilized by organizations that have multiple application systems that need to share and exchange data and manage data quality at an organizational level.

Data Quality - Data Quality Management: Process Assessment Model for Smart Manufacturing

1. Range

Embodiments of the present invention provide techniques for defining an assessment of data quality management process maturity for smart manufacturing as described above and include a process reference model of the ISO 8000-61 standard and a maturity assessment model of the ISO 8000-62 standard Based process assessment model for smart manufacturing.

For example, the following techniques may fall within the scope of the embodiments of the present invention.

- Data quality management process of smart manufacturing

- Evaluation of an exemplary data quality management process in smart manufacturing

- Smart manufacturing and data quality management process evaluation index

- conformance requirements.

In addition, as described above, the embodiments of the present invention can define rules for how to apply the data quality management process evaluation to smart manufacturing, and it is possible to define rules for sharing data and exchange data to measure data quality in smart manufacturing Can be utilized in smart manufacturing with application systems.

Embodiments of the present invention may be used with or independently of a quality management system standard such as the ISO 9001 standard.

2. Terms, Definitions and Abbreviations

2.1 Terms and Definitions

Smart Manufacturing can mean applications that dramatically enrich and disseminate networked information-based technologies across manufacturing and supply chains.

Industry 4.0 (Industry 4.0) focuses on the use of information and communications networks globally available for widely exchanging automated manufacturing and logistics systems in the form of Cyber-Physical Production Systems (CPPS) Describes a new emerging structure that matches.

2.2 Acronyms

The following abbreviated terms apply.

Data Quality (DQ)

Data Quality Management (DQM)

Process Attribute (PA)

Process Reference Model (PRM)

3. Relationship with other standards

3.1 Relationship between data quality standards

For data quality standards, embodiments of the present invention are based on the data quality management process reference model of the ISO 8000-61 standard and the maturity model of the ISO 8000-62 standard.

1 is a diagram illustrating a relationship between embodiments of the present invention and data quality standards. Figure 1 shows the relationship of the data quality standards included in the ISO 8000 standard described above.

Part 60 (100) defines an overview of process evaluation as an ISO 8000-60 standard, and more specifically explains concepts related to the implementation, evaluation and enhancement of data quality management.

Part 61 (110) defines the process reference model as an ISO 8000-61 standard, and more specifically, as a reference for evaluating process capability or organizational maturity for improving data quality and for managing data quality. Specify the processes required for quality control. As shown in Figure 1, Part 61 (110) describes the principles of DQM, the DQM process, and implementation requirements.

Part 62 (120) defines an organizational maturity rating model as an ISO 8000-62 standard, and describes evaluation practices and proofs of conformity, as shown in FIG. In more detail, Part 62 (120) specifies how the maturity model can be used to assess process maturity in relation to data quality management, as specified in Part 61 (110) It explains that these measurement indices can be determined using the measurement stack specified in Part 63 (130), which will be explained.

Part 63 (130) defines the measurement framework as the ISO 8000-63 standard and describes measurement procedures and measurement stacks for measuring the characteristics of the process for data quality management as shown in Figure 1, Provide evidence for evaluation to Part 62 (120) and Part 64 (140).

Part 64 (140) defines the application for maturity evaluation by the DQPI-model as the ISO 8000-64 standard, and describes the evaluation performing and joint authentication as shown in FIG. This Part 64 (140) specifies a model for applying the Test Process Improvement (TPI) method as a basis for determining organizational maturity related to data quality management.

Part 65 (150), Part 66 (160) and Part 67 (67) have not yet been proposed, and are each a process improvement model and an organizational maturity model, and an exemplary process evaluation model for smart manufacturing associated with embodiments of the present invention . In addition, Part 65 (150), Part 66 (160), and Part 67 (67) can utilize the Organizational Maturity Rating model of Part 62 (120), respectively.

Part 67 (67) associated with embodiments of the present invention may be provided with process information from Part 61 (110) and may provide example process information to Part 63 (130).

3.2 Relationship with Smart Manufacturing Standards

In the context of smart manufacturing standards, embodiments of the present invention may be implemented using the ISA 95 standard (Enterprise-Control System Integration) and the ISO / IEC 62264 standard (Enterprise-Control System Integration) ) Can be referred to. Figure 2 is an illustration of examples of standards tailored to the ISA 95 model. FIG. 2 illustrates an enterprise level for enterprise resource planning (ERP), a MOM level for manufacturing operations management (MOM), a human machine interface (HMI), and a distributed control system Examples of manufacturing pyramids separated by equipment levels for Supervisory Control and Data Acquisition (SCADA) levels and field equipment for control systems (DCS), and examples of standards associated with each level of the manufacturing pyramid have.

4. Data evaluation management process in smart manufacturing

4.1 Processes in Smart Manufacturing

The process of smart manufacturing is industry dependent.

3 is a diagram illustrating an example of shipbuilding processes in consideration of smart manufacturing, in an embodiment of the present invention. The shipbuilding processes can be roughly classified into processes for the Internet service 310 and processes for the Inter of Things (IoT) and the Cyber Physical Production System (CPPS) 320.

Processes for Internet service 310 may include processes for Quotation 311, Contract 312, Design 313, and Steel Pre-processing 314 .

Processes for the IoT and CPPS 320 may also be used for the steel processing 321, the steel assembly 322, the pre-outfitting 323, the pre-election, 324, painting 326, painting 337, launching 327, inner outfitting 328, sea trial 329, naming 330, and the like. And processes for delivery (331).

Considering smart manufacturing, the shipbuilding processes classified as shown in FIG. 3 can be utilized to describe a process evaluation model for smart manufacturing.

4.2 The Process of Data Quality Management

4 is a diagram showing an example of the structure of a data quality management process in an embodiment of the present invention. This data quality management process may largely include processes for Implementation 410, Data-Related Support 420, and Resource Provision 430.

The implementation 410 process includes a data quality planning 411, a data quality control 412, a data quality assessment 413, and a data quality improvement 414 ≪ / RTI >

Processes for data quality planning 411 may include managing data quality requirements, managing data quality strategies, managing data quality policies / standards / procedures, and planning data quality implementations Processes.

Processes for data quality control 412 may be processes for defining descriptions and guidelines for data quality, processing data, and monitoring and controlling data quality.

Processes for data quality assessment 413 can be processes for identifying data quality problems, defining data quality metrics, measuring data quality, and evaluating data quality measurement results.

Processes for data quality enhancement 414 may be processes for analyzing the root cause, deriving a solution, correcting data inconsistencies, and handling process enhancements to prevent data incompatibility.

Processes for Data-Related Support 420 may be processes for managing the architecture, transmission, operation, security, etc. of data, and processes for Resource Provision 430 may be data quality management And processes for managing human resource training.

5. Evaluation model

The evaluation model according to embodiments of the present invention may be based on the maturity model of the ISO 8000-62 standard.

5.1 Maturity Model

The ISO 8000-62 standard defines a data quality management process evaluation model. Evaluation of these organizational maturity levels can be made in accordance with the data quality management reference model introduced in the ISO 8000-61 standard. As a result of the evaluation, the evaluator can obtain the maturity level of data quality management for the organization.

5 is a diagram showing an example of an organization maturity evaluation model in an embodiment of the present invention. The graph 500 of FIG. 5 shows an example of a model for determining the maturity level through the capability levels of each of the processes described with reference to FIG.

For example, 'DQC' in 'DQC.2' may refer to the data quality control 412 in FIG. 4, and the number '2' may represent the data quality control 412 in the process of data quality control 412 The second process may be a process for data processing. In another example, 'DRS.4' may refer to a process for data security management, which is the fourth of processes for Data-Related Support 420. 'DQP.1' May refer to a process for managing data quality requirements, which is the first of the processes for plan 411. In addition, 'ML' in 'ML.1' may mean a maturity level, and the number '1' may mean that the value of the maturity level is '1'.

Assessment indicators for organizational maturity assessment can use the metrics of the ISO 8000-66 standard (Part 66 (160)). Part 66 (160) described above establishes an exemplary maturity assessment model for manufacturing operations defined in the IEC 62264 standard. The purpose of these Part 66 (160) is to evaluate manufacturing operations using the ISO 8000-62 standard (Part 62 (120)). Part 62 (120) is intended for use by actors with a vested interest in information or data quality, with an emphasis on one or more information systems, both at the organization and within the organization, at every stage of the data lifecycle. The purpose of evaluating organizational process maturity levels for data quality management is to understand how well the organization performs the requirements identified by the process reference model for data quality management specified in the ISO 8000-61 standard (Part 61 (110)). . To this end, embodiments of the present invention may define an evaluation metric for a manufacturing operation in association with Part 66 (160). This Part 66 (160) sets the manufacturing process reference model for the manufacturing operations defined in IEC 62264, and sets the indicators according to the evidences that are information related to the manufacturing operations. These indices may serve as a basis for evaluating the performance of the process, and in embodiments of the present invention, information related to manufacturing operations defined in IEC 62264 in connection with Part 66 (160) 1 to skill level 5, and define evidence for process attributes.

In this graph 500, the y-axis may refer to a capability level to be described later, and the x-axis may refer to each process that is classified according to the maturity level. For example, if processes 'DQP.1', 'DQC.1', and 'DQC.3' all attain capability level 2, it can be interpreted as achieving maturity level 2 (ML.2). As another example, if all of the processes 'DQI.1', 'DQI.2', and 'DQI.3' have achieved capability level 5, it can be interpreted as achieving maturity level 5 (ML.5).

Hereinafter, the capability level and the processor attribute rating will be described, and a more specific method for determining organizational maturity level for smart manufacturing in the embodiments of the present invention will be described.

6. Outline of best practice evaluation model for smart manufacturing

6.1 Examples of business processes for smart manufacturing are illustrated in FIG.

6.2 Capability dimension

There are six capability levels (from level 0 to level 5) that integrate process attributes for smart manufacturing.

There is no order between process attributes at each level, and each attribute deals with a specific aspect of the capability level. Table 1 below shows an example of a list of process levels and process attributes.

Process Capability Level Process Attributes Level 0: Incomplete Process n / a Level 1: Performed Process PA.1.1. Process performance Level 2: Managed Process PA.2.1. Performance management
PA.2.2. Work product Management Level 3: Established Process PA.3.1. Process definition
PA.3.2. Process deployment Level 4: Predictable Process PA.4.1. Quantitative analysis
PA.4.2. Quantitative control Level 5: Innovating Process PA.5.1. Process innovation
PA.5.2. Process innovation implementation

The capability level may correspond to the process capability level '1' to '5' as a process capability indicator, and the process attribute may define information for achieving the process attribute. For example, a process performance attribute (PA.1.1.) Is a measurement of the degree to which a process's purpose has been achieved. As a result of a complete performance of that attribute, the process achieves a defined result (capability level 1, can do. In another example, a process (capability level 1) performed through a managed process with capability level 2 will be implemented according to a management scheme (planned, monitored, and coordinated), and the work output of the performed process And can be properly set, controlled and maintained. Performance Management Attributes (PA 2.1.) Measure the extent to which the performance of a process is managed, and as a result of a complete performance of this attribute, a) the purpose for the performance of the process is identified, b) D) the responsibilities and authorities for the performance of the process are defined, assigned and communicated; and e) the resources and information necessary to perform the process are identified, available, allocated and used, f) The interface between the parties concerned may be managed to ensure effective communication and to ensure a clear allocation of responsibilities.

As such, process attributes can be set and utilized for each capability level, and capability levels can be assigned depending on the extent to which these attributes are achieved.

6.3 Proficiency Levels for Business Processes

The proficiency level according to embodiments of the present invention may be, for example, a value of '1' or 'basic'. Although there is no evidence of payment attention to data quality, an organization can demonstrate that the data used in the organization's business processes are correct data and that the processing is adequately secured and automated. This may mean that the execution of activities in the business processes of the organization should utilize the data management processors of the process reference model. For example, the quotation process 311 described in FIG. 3 may be Business Process 1 (BP.1), and the contract process 312 may be Business Process 2 (BP.2).

6.4 Rating of Process Attributes

The grade of the process attribute can determine the degree of achievement of the evaluated process. Table 2 below shows examples of process attribute classes.

Process BP.1 BP.2 BP.3 BP.4 BP.5 PA.1.1. F F F F F PA.2.1. F F F L F PA.2.2. F F F L F PA.3.1. L L F P F PA.3.2. L L F P F PA.4.1. N N P N F PA.4.2. N N P N F PA.5.1. N N N N L PA.5.2. N N N N L Capability Level 3 3 3 2 5

Here, 'N' indicates that the business process is not achieved, 'P' indicates that the business process is partially achieved, 'L' indicates that the business process is largely achieved (Largely achieved, and 'F' may mean that the business process is fully achieved. Capability levels are described in Table 1. For example, Table 2 shows that Business Process 1 (BP.1) has fully met the Process Performance Attributes (PA.1.1.), Indicating that the Quantitative Attributes attribute (PA.4.1.) Has not been achieved .

6.5 Proficiency Levels for Smart Manufacturing

Figure 6 is an example of achieving maturity level 2 for smart manufacturing in one embodiment of the present invention. Looking at the requirements set in the shaded cell and ISO 8000-62 standard in Figure 6, it can be seen that the embodiment of Figure 6 has achieved "Managed ", which is the organization maturity level 2 (ML.2) . For example, according to the graph 600 of FIG. 6, maturity level 3 indicates that smart manufacturing is not a skill level 3 because Business Process 8 (BP.8) and Business Process 11 (BP.11) Level 3 (ML.3) is not achieved. On the other hand, according to the graph 600 of FIG. 6, Business Processes 3 (BP.3), Business Processes 4 (BP.4) and Business Processes 5 (BP.5) classified as maturity level 2 It can be seen that smart manufacturing has achieved proficiency level 2 (ML.2) because all achievement level 2 is achieved. The roles of each business process can be specified within the organization.

7. Process Performance indicators

The process performance indicator of the process evaluation model provides information such as the following forms (a), (b) and (c).

(a) A set of basic practices in the process that provide the definition of the tasks and activities required to achieve process objectives and achieve process outcomes. Each basic task can be explicitly related to the process outcome.

(b) the number of input and output work products associated with each process and related to the results of one or more processes

(c) the characteristics associated with each work product,

Table 3 below shows examples of process performance indicators used in process capability level 1.

Process ID Process Name Requirements Management Process Purpose The objective of requirements management is to establish a basis for establishing or improving a data quality strategy that meets the needs and expectations of stakeholders. Process Outcomes - Stakeholder needs and expectations related to data are collected.
- Requests and expectations are improved to meet data requirements.
Note: These improvements may include structuring and classifying requirements to increase understanding of the interdependence of requirements.
- Analyze requirements to determine feasibility in terms of technology, cost, personnel and schedule.
- Requirements are prioritized and approved.
- The needs of different parts of the organization are balanced and a common set of agreed requirements is achieved. Base Practices - Identify data requirements: Collect requirements and expectations related to stakeholder data, identify and classify data requirements.
Note: For more information on data requirements, refer to ISO 8000-8 and ISO 8000-110 standards.
- Prioritize data requirements: Analyze the feasibility of identified requirements in terms of technology, cost, timeliness and importance while providing a basis for determining implementation priorities.
- Verification of data requirements: Track and evaluate the extent to which requirements are met through a data quality management process and, if necessary, modify requirements through consultation with stakeholders.

7 is a block diagram for explaining an internal configuration of a computer apparatus according to an embodiment of the present invention. An evaluation system according to an embodiment of the present invention may be implemented by the computer device 700 of FIG. 7, and an evaluation method according to an embodiment of the present invention may be performed by such a computer device 700. FIG. For example, a computer program according to an embodiment of the present invention may be installed and operated in the computer device 700, and the computer device 700 may perform the evaluation method under the control of a computer program that is driven.

Such a computer device 700 may include a memory 710, a processor 720, a communication interface 730 and an input / output interface 740, as shown in FIG. The memory 710 may be a computer-readable recording medium and may include a permanent mass storage device such as a random access memory (RAM), a read only memory (ROM), and a disk drive. Herein, the non-decaying mass storage device such as the ROM and the disk drive may be included in the computer device 700 as a separate persistent storage device separate from the memory 710. The memory 710 may also store an operating system and at least one program code. These software components may be loaded into the memory 710 from a computer readable recording medium separate from the memory 710. [ Such a computer-readable recording medium may include a computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD / CD-ROM drive, and a memory card. In other embodiments, the software components may be loaded into the memory 710 via the communication interface 730 rather than from a computer readable recording medium. For example, the software components may be loaded into the memory 710 of the computer device 700 based on a computer program installed by files received via the network 760.

The processor 720 may be configured to process instructions of a computer program by performing basic arithmetic, logic, and I / O operations. The instructions may be provided to the processor 720 by the memory 710 or the communication interface 730. [ For example, processor 720 may be configured to execute instructions received according to program code stored in a recording device, such as memory 710. [

The communication interface 730 may provide functionality for the computer device 700 to communicate with other devices (e. G., The storage devices described above) via the network 760. [ In one example, a request, command, data, file, or the like, generated by the processor 720 of the computer device 700 according to the program code stored in the recording device such as the memory 710, 760 to other devices. Conversely, signals, commands, data, files, etc., from other devices can be received by the computer device 700 via the network 760 and through the communication interface 730 of the computer device 700. The signals, commands, data, and the like received through the communication interface 730 can be transferred to the processor 720 or the memory 710 and the files and the like can be transferred to a storage medium Permanent storage).

The input / output interface 740 may be a means for interfacing with the input / output device 750. For example, the input device may include a device such as a microphone, a keyboard or a mouse, and an output device may include a device such as a display, a speaker, and the like. As another example, the input / output interface 740 may be a means for interfacing with a device having integrated functions for input and output, such as a touch screen. The input / output device 750 may be composed of the computer device 700 and one device.

Also, in other embodiments, the computing device 700 may include fewer or more components than the components of FIG. However, there is no need to clearly illustrate most prior art components. For example, the computer device 700 may be implemented to include at least some of the input / output devices 750 described above or may further include other components such as a transceiver, database, and the like.

8 is a flow chart illustrating an example of an evaluation method for evaluating a data quality management process for smart manufacturing, in an embodiment of the present invention. The evaluation method according to the present embodiment can be performed by the computer apparatus 700 described above. The processor 720 of the computer device 700 may be implemented to execute control instructions in accordance with the code of the operating system or code of at least one computer program that the memory 710 contains. Here, the processor 720 causes the computer apparatus 700 to perform the steps 810 to 850 included in the evaluation method according to the embodiment of FIG. 8, according to the control command provided by the code stored in the computer apparatus 700 The computer device 700 can be controlled.

At step 810, the computing device 700 may identify processes associated with data quality management in the manufacturing process. For example, FIG. 3 illustrates examples of shipbuilding processes that consider smart manufacturing, and that the roles of these processes can be specified within an organization. For example, an organization may set up a role for each of the processes and processes associated with data quality management in its manufacturing process, and the computing device 700 may identify processes in accordance with these settings. At this time, the computer device 700 may sort according to the processing order of the identified processes to determine the maturity level of the identified processes. The classification of maturity levels of these processes can be made according to the process attributes that each process has to achieve, as will be described later.

At step 820, the computing device 700 may evaluate the degree of achievement by process attribute for each identified process. For example, process attributes are described in Table 1 and Table 2. As a more specific example, if the process performance attribute (PA.1.1.) For capability level 1 is to measure the degree to which the purpose of the process has been achieved, the computer device 700 determines whether the purpose of each process has been achieved It can be judged. Thus, the degree of achievement by process attribute may include the degree of achievement of the predefined goal for each process attribute, and the criteria for distinguishing between the predefined goal and achievement level for each of these process attributes may vary from one type of manufacturing process to another.

At step 830, the computing device 700 may determine a capability level for each identified process based on the evaluated degree of attainment per process attribute for each identified process. The ability levels are also described in Table 1 and Table 2. For example, in Table 2, Business Process 3 (BP. 3) was identified as Process Attribute 3.2 (PA) while Business Process 5 (BP. 5) .3.2.), And the capability level is determined to be '3' because the process attribute 4.1 (PA.4.1.) Has not been partially achieved or achieved.

At step 840, the computing device 700 may determine the maturity level of the manufacturing process based on the maturity level at which the identified processes are classified and the capability level determined for each of the identified processes. For example, the computer device 700 may determine a maximum maturity level in which the processes classified into the maturity level are all satisfied, as the maturity level of the corresponding manufacturing process, according to the determined capability level. More specifically, FIG. 6 shows that processes (BP. 3, BP. 4 and BP. 5) classified as maturity level 2 have achieved capability level 2 corresponding to maturity level 2. On the other hand, in FIG. 6, the BP.8 process and the BP.11 process among the processes classified as the maturity level 3 (BP.6, BP.7, BP.8, BP.9, BP.10 and BP.11) 'Indicates that the process did not achieve capability level 3 corresponding to maturity level 3. FIG. 6 shows an example in which it is determined that the corresponding manufacturing process has achieved a maturity level of '2' (managed). As such, the computing device 700 may determine the maturity level of the entire manufacturing process based on whether all of the processes classified to a particular maturity level have achieved a capability level corresponding to that maturity level.

At step 850, the computer device 700 may provide information about the process for which improvement is desired based on the determined maturity level and the process-specific capability level, and information about the process attribute for which improvement is desired in the specific process. For example, the computer device 700 may provide information about a process that fails to achieve a capability level corresponding to the exceeding maturity level among processes classified in a maturity level exceeding a determined maturity level, Information, and determine a process attribute corresponding to a capability level that the determined process does not achieve as a process attribute that requires improvement. 6, the computer device 700 determines whether business process 8 (BP. 8) is associated with a business attribute associated with capability level 3 (according to Table 1, process definition attribute (PA. (PA.3.2, Process deployment). In this case, the computer device 700 can identify the processors for which improvement is required, and can provide information on which processes are required to be improved and which process attributes are required to be improved.

9 is a flowchart showing an example of an evaluation method for evaluating a data quality management process in a shipbuilding process in an embodiment of the present invention. FIG. 9 specifically explains how the evaluation method according to the present embodiment can be applied to the shipbuilding process described with reference to FIG. The evaluation method according to this embodiment can also be performed by the computer apparatus 700 described above. The processor 720 of the computer device 700 may be implemented to execute control instructions in accordance with the code of the operating system or code of at least one computer program that the memory 710 contains. Here, the processor 720 causes the computer apparatus 700 to perform the steps 910 to 970 included in the evaluation method according to the embodiment of FIG. 9, according to the control command provided by the code stored in the computer apparatus 700 The computer device 700 can be controlled.

In step 910, the computer device 700 may set information about the processes required in the shipbuilding process. 3, for example, the shipbuilding process may include a quotation 311, a contract 312, a design 313, a steel pre-processing 314, a steel processing 321, a steel assembly 322, The design 323, the pre-orientation 324, the orientation 325, the painting 326, the launch 327, the interior design 328, the marine commissioning 329, the naming 330 and the delivery 331 ), The computing device 700 may set information about the processes by inputting information about the respective processes and information about the roles of the processes from the organization.

At step 920, the computing device 700 may identify processes associated with data quality management in the shipbuilding process based on the set information. For example, the computer device 700 may include the above-described quotation 311, contract 312, design 313, still pre-processing 314, still processing 321, steel assembly 322, (323), a pre-orientation 324, an orientation 325, a painting 326, a launch 327, an interior design 328, a marine commission 329, a naming 330 and a delivery 331 ≪ / RTI >

At step 930, the computer device 700 may set the process attributes that the process should accomplish for each identified process. For example, the computer device 700 may determine the process attribute to be achieved for each of the identified processes, such as the process attribute for the process for the quotation 311 and the process attribute for the process for the contract 312 to achieve, Can be set. In other words, the process attributes to be achieved for achieving the capability level as described with reference to Table 1 are already predefined in the evaluation model according to embodiments of the present invention, and the computer device 700 is identified You can set the processes to achieve any of these predefined process attributes. This process attribute to be achieved can be set based on the roles of the identified processes.

At step 940, the computer device 700 may classify the identified processes into a plurality of maturity levels according to the order of processing of the processes. For example, processes for estimates 311 and contracts 312 are at maturity level 1, processes for design 313 and still pre-processing 314 are at maturity level 2, and still processing 321, Processes for assembly 322, pre-design 323 and pre-orientation 324 are shown at maturity level 3 and include an arrangement 325, a painting 326, a launch 327 and an interior design 328 The processes for the maritime commissioning 329, the naming 330 and the delivery 331 may be classified as maturity level 5, respectively. This classification can be made according to the process attributes that each process must achieve, as will be described later.

At step 950, the computing device 700 may evaluate the degree of achievement by process attribute for each identified process. For example, process attributes are described in Table 1 and Table 2. As a more specific example, if the process performance attribute (PA.1.1.) For capability level 1 is to measure the degree to which the purpose of the process has been achieved, the computer device 700 determines whether the purpose of each process has been achieved It can be judged. As an example, depending on the purpose of the process for the quotation 311 and the degree of achievement of the purpose, the degree of achievement of the process for the quote 311 is 'N' (Not achieved), 'P' (Partially achieved) , 'L' (Largely achieved) and 'F' (Fully achieved). In the example of Table 2, four achievements are introduced, but more or less achievement criteria may be utilized. Thus, the degree of achievement by process attribute may include the degree of achievement of the predefined goal for each process attribute, and the criteria for distinguishing between the predefined goal and achievement level for each of these process attributes may vary from one type of manufacturing process to another.

At step 960, the computing device 700 may determine a capability level for each identified process based on the evaluated degree of attainment per process attribute for each identified process. The ability levels are also described in Table 1 and Table 2. For example, in Table 2, Business Process 3 (BP. 3) was identified as Process Attribute 3.2 (PA) while Business Process 5 (BP. 5) .3.2.), And the capability level is determined to be '3' because the process attribute 4.1 (PA.4.1.) Has not been partially achieved or achieved. A similar method can be used to determine the capability level for each of the processes identified for the shipbuilding process.

At step 970, the computing device 700 may determine the maturity level of the manufacturing process based on the maturity level at which the identified processes are classified and the capability level determined for each of the identified processes. For example, according to the determined capability level, the maximum maturity level at which the processes classified into the maturity level are all satisfied can be determined as the maturity level of the corresponding manufacturing process. More specifically, FIG. 6 shows that processes (BP. 3, BP. 4 and BP. 5) classified as maturity level 2 have achieved capability level 2 corresponding to maturity level 2. On the other hand, in FIG. 6, the BP.8 process and the BP.11 process among the processes classified as the maturity level 3 (BP.6, BP.7, BP.8, BP.9, BP.10 and BP.11) 'Indicates that the process did not achieve capability level 3 corresponding to maturity level 3. FIG. 6 shows an example in which it is determined that the corresponding manufacturing process has achieved a maturity level of '2' (managed). As such, the computing device 700 may determine the maturity level of the entire manufacturing process based on whether all of the processes classified to a particular maturity level have achieved a capability level corresponding to that maturity level.

At step 980, the computing device 700 may provide information about the process for which improvement is desired based on the determined maturity level and the capability level for each process, and information about the process attribute for which improvement is desired in the specific process. For example, the computer device 700 may provide information about a process that fails to achieve a capability level corresponding to the exceeding maturity level among processes classified in a maturity level exceeding a determined maturity level, Information, and determine a process attribute corresponding to a capability level that the determined process does not achieve as a process attribute that requires improvement. 6, the computer device 700 determines whether business process 8 (BP. 8) is associated with a business attribute associated with capability level 3 (according to Table 1, process definition attribute (PA. (PA.3.2, Process deployment). In this case, the computer device 700 can identify the processors for which improvement is required, and can provide information on which processes are required to be improved and which process attributes are required to be improved. In other words, the organization can be provided with information on which processes should be improved for which process attributes in the shipbuilding process.

10 is a flow chart illustrating an example of a method of processing parameters of a data quality management process for smart manufacturing, in an embodiment of the present invention. The parameter processing method according to the present embodiment can be performed by the computer apparatus 700 described above. The processor 720 of the computer device 700 may be implemented to execute control instructions in accordance with the code of the operating system or code of at least one computer program that the memory 710 contains. Here, the processor 720 performs the steps 1010 to 1070 that the computer apparatus 700 includes in the parameter processing method according to the embodiment of FIG. 10, according to the control command provided by the code stored in the computer apparatus 700 The computer device 700 can be controlled.

At step 1010, the computing device 700 may store and manage information entered for identification of processes associated with data quality management in the manufacturing process. Herein, the input information may include information on the processes required in the manufacturing process and information on the role of the processes.

At step 1020, the computing device 700 may store and manage the process attributes that the process should accomplish for each of the identified processes. At this time, the process attribute to be achieved can be set for each of the identified processes based on information on the role of the input processes.

At step 1030, the computing device 700 may evaluate and manage the degree of achievement by process attribute for each identified process. For example, the degree of achievement by process attribute for each of the processes can be utilized for improvement of the process while being managed as a parameter by the computer device 700.

At step 1040, the computing device 700 may determine and manage a capability level for each of the identified processes based on the evaluated degree of attainment per process attribute for each identified process. The ability level for each of these processes may also be utilized for improvement of the process while being managed as a parameter by the computer device 700.

At step 1050, the computing device 700 may classify the identified processes into a plurality of maturity levels according to the order of processing of the processes. The classification of these processes can be based on the process attributes that the processes must achieve. For example, if a particular process A is a process that requires both quantitative attributes (PA.4.1.) And quantitative control attributes (PA.4.2.) Of capability level 4 described in Table 1, then at least maturity level '4' Or more. If Process A does not need to achieve the Process Innovation Attributes (PA.5.1.) Described in Table 1, Process A can be classified as a Maturity Level '4'.

At step 1060, the computing device 700 may determine and manage the maturity level of the manufacturing process based on the maturity level at which the identified processes are identified and the level of capability determined for each identified process. For example, according to the capability level determined in step 1040, the maximum maturity level at which the classified processes are all satisfied can be determined as the maturity level of the corresponding manufacturing process. This determined maturity level of the manufacturing process can also be utilized for improvement of the process while being managed as a parameter by the computer device 700.

At step 1070, the computer device 700 determines whether there is information about the process for which improvement is desired based on the managed maturity level and the capability level that is managed for each of the identified processes, Information can be provided. At this time, the computer device 700 may acquire information about a process that fails to achieve the capability level corresponding to the exceeding maturity level among the processes classified into the maturity level exceeding the managed maturity level, And determine a process attribute corresponding to a capability level that the process for which the improvement is not achieved, as a process attribute for which improvement is required.

Thus, in accordance with embodiments of the present invention, there is provided an evaluation method and evaluation system for evaluating a data quality management process for smart manufacturing, and a computer system coupled to the computer and configured to perform the evaluation method on a computer readable recording medium A program and its recording medium can be provided. The present invention also provides an evaluation method and an evaluation system for evaluating a data quality management process in a shipbuilding process, and a computer program stored in a computer-readable recording medium for causing the computer to execute the evaluation method, . The present invention also relates to a parameter processing method and a parameter processing system for processing parameters for process evaluation in a smart manufacturing environment and a computer program stored in a computer readable recording medium for causing the computer to execute the parameter processing method, A recording medium can be provided.

The system or apparatus described above may be implemented as a hardware component, or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA) , A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device As shown in FIG. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The medium may be one that continues to store computer executable programs, or temporarily store them for execution or download. In addition, the medium may be a variety of recording means or storage means in the form of a combination of a single hardware or a plurality of hardware, and is not limited to a medium directly connected to a computer system, but may be dispersed on a network. Examples of the medium include a magnetic medium such as a hard disk, a floppy disk and a magnetic tape, an optical recording medium such as CD-ROM and DVD, a magneto-optical medium such as a floptical disk, And program instructions including ROM, RAM, flash memory, and the like. As another example of the medium, a recording medium or a storage medium managed by a site or a server that supplies or distributes an application store or various other software to distribute the application may be mentioned. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (13)

A method of evaluating a data quality management process for smart manufacturing,
Identifying processes associated with data quality management in the manufacturing process;
Evaluating a degree of achievement by process attribute for each of the identified processes; And
Determining a capability level for each of the identified processes based on the evaluated degree of attainment per process attribute for each of the identified processes
And evaluating the evaluation result. The method according to claim 1,
Classifying the identified processes by a plurality of maturity levels according to a processing order of processes; And
Determining the maturity level of the manufacturing process based on the identified maturity level and the capability level determined for each of the identified processes
Further comprising the step of: 3. The method of claim 2,
Wherein determining the maturity level of the manufacturing process comprises:
And determining, as a maturity level of the manufacturing process, a maximum maturity level that satisfies all the processes classified into the maturity level according to the capability level determined for each of the identified processes, Assessment Methods. 3. The method of claim 2,
Providing information about a process for which an improvement is required based on the determined maturity level and a capability level determined for each of the identified processes, and information about a process attribute for which improvement is required in the specific process
Further comprising the step of: 5. The method of claim 4,
Wherein the providing step comprises:
Determining information on a process that fails to achieve a capability level corresponding to the exceeding maturity level among the processes classified as maturity levels exceeding the determined maturity level as information on a process for which improvement is required, And determining a process attribute corresponding to a capability level that is not achieved as a process attribute that requires improvement. The method according to claim 1,
Wherein the degree of achievement of each of the process attributes includes a degree of achievement of a predetermined goal for each of the process attributes. A computer program stored in a computer-readable medium for causing a computer to execute the method of any one of claims 1 to 6 in combination with the computer. A computer-readable recording medium storing a program for causing a computer to execute the method according to any one of claims 1 to 6. An evaluation system for evaluating a data quality management process for smart manufacturing, comprising:
A memory for storing instructions readable by a computer; And
At least one processor < RTI ID = 0.0 >
Lt; / RTI >
Wherein the at least one processor comprises:
Identify processes associated with data quality management in the manufacturing process,
Evaluating a degree of achievement by process attribute for each of the identified processes,
Determining a capability level for each of the identified processes based on the evaluated degree of attainment per process attribute for each of the identified processes
. 10. The method of claim 9,
Wherein the at least one processor comprises:
Classifying the identified processes into a plurality of maturity levels according to a processing order of processes,
Determining the maturity level of the manufacturing process based on the identified maturity level and the capability level determined for each of the identified processes
. 11. The method of claim 10,
Wherein the at least one processor comprises:
Determining a maximum maturity level at which the processes classified into the maturity level are all satisfied according to the capability level determined for each of the identified processes as the maturity level of the manufacturing process
. 11. The method of claim 10,
Wherein the at least one processor comprises:
Providing information about a process for which improvement is required based on the determined maturity level and a capability level determined for each of the identified processes and information about a process attribute for which improvement is required in the specific process
Evaluation system that features. 13. The method of claim 12,
Wherein the at least one processor comprises:
Determining information on a process that fails to achieve a capability level corresponding to the exceeding maturity level among the processes classified as maturity levels exceeding the determined maturity level as information on a process for which improvement is required, Determining the process attribute corresponding to the unreachable capability level as a process attribute that requires improvement
.

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