KR102706535B1 - Data correlation between different machines in a production line for electronic components - Google Patents

Abstract

A data set associated with a common PCB is correlated by: (a) providing a first data set from a first machine, wherein the first data set comprises first location information and first feature information for feature target characteristics of a product-feature structure of the printed circuit board at a plurality of locations on the printed circuit board; (b) providing a second data set from a second machine, wherein the second data set comprises second location information and second feature information for feature target characteristics of a product-feature structure of the printed circuit board at a plurality of locations on the printed circuit board; (c) geometrically superimposing the first location information on the second location information; and (d) repositioning the first location information and/or the second location information such that a sum of distances between two correlated pieces of location information, i.e., the first location information and the associated second location information, from one and the same location on the printed circuit board are reduced.

Description

Data correlation between different machines in a production line for electronic components

The present invention relates in particular to the field of technology for the production of electronic assemblies in a production line having a plurality of machines, such as a placement machine for placing electronic components on a printed circuit board and an inspection machine for determining the quality of the previous process step. The present invention particularly relates to a method for analyzing process data of such a production line and to a method for optimizing a manufacturing process for electronic assemblies.

Electronic assemblies typically have a printed circuit board and a plurality of electronic components attached to the printed circuit board and electrically connected to each other by conductor tracks. These electronic assemblies are manufactured on a production line having a plurality of machines connected to each other via conveyor belts for manufacturing or processing and machines for (optical) inspection of intermediate products. These machines typically include:

(a) a solder paste printing machine that selectively applies solder paste to a component connection area or connection area formed on the surface of a related printed circuit board;

(b) a solder paste inspection machine to verify accurate application of solder paste;

(c) at least one placement machine for placing electronic components on the surface of a printed circuit board provided with solder paste;

(d) Placement inspection machine for verifying correct placement of printed circuit boards;

(e) a soldering machine or oven for melting solder paste located between the component connection area of the mounted printed circuit board and the electrical connection contacts of the relevant components; and

(f) Soldering inspection machine to verify accurate soldering of components.

For quality determinations that may be somewhat degraded, it is not necessary to use all three inspection machines mentioned above. All that is needed is an inspection machine, but it does not necessarily have to be the soldering inspection machine mentioned above.

In a production line known today for electronic assemblies, at least one inspection machine is used to separate defective or improperly processed printed circuit boards from the production process or to direct them for repair. This separation occurs at a specific point in the production line by means of a suitable discharge device, technically referred to in this document as a gate. For cost-benefit reasons, this separation should be done as quickly as possible.

There can be two different reasons for the separation. The first reason can be that the processed printed circuit board, also called product or intermediate product in this document, is actually defective or of (very) poor quality. The second reason can be that the product or intermediate product is completely normal, but the relevant inspection machine reports an error incorrectly. Therefore, for the sorting of products by the inspection machine, it is reasonable to choose a threshold for error detection that reliably detects defective products on the one hand, and on the other hand minimizes the output of false errors as much as possible.

The separated products or separated printed circuit boards can be manually inspected by a skilled operator and reprocessed if necessary. Based on these evaluation results, process parameters such as the squeegee speed of the solder paste printing machine can be improved or optimized for future printing processes. In addition, the above-mentioned thresholds for error detection can be adapted.

However, manual optimization of these process parameters and appropriate adjustment of thresholds for error detection are actually very difficult. These two factors depend particularly on the ability and experience of the operator optimizing the process parameters and adjusting these thresholds.

The present invention is based on the purpose of making it easier to optimize process parameters and/or adjust thresholds for error detection when producing electronic assemblies.

This purpose is achieved by the subject of the independent claim.

Advantageous embodiments of the invention are set forth in the dependent claims.

According to a first aspect of the present invention, a method for correlating different data sets associated with one and the same printed circuit board from which an electronic assembly having a plurality of electronic components is built by automated production in a production line is described. The described method comprises the steps of (a) providing a first data set from a first machine, said first data set being associated with (al) said first machine, (a2) controlling the operation of said first machine, and (a3):

A step of providing a first data set, said first data set including first location information and first feature information for feature target characteristics of a product-feature structure of said printed circuit board at a plurality of locations on said printed circuit board; (b) a step of providing a second data set from a second machine, said second data set being (b1) associated with said second machine, (b2) controlling operation of said second machine, and said second data set comprising: (b3):

providing a second data set, said second data set including second location information and second feature information for feature target characteristics of a product-feature structure of said printed circuit board at a plurality of locations on said printed circuit board; (c) geometrically superimposing said first location information on said second location information; and

(d) a step of rearranging the first location information and/or the second location information such that a sum of distances between two pieces of correlated location information from a same location on the printed circuit board, i.e., the first location information and the associated second location information, is reduced.

The described method is based on the knowledge that by a suitable geometrical rearrangement of the first coordinate system of the first position information and/or of the second coordinate system of the second position information relative to one another, the process data of the different machines can be compared or correlated with one another with respect to the product-characteristic results of the intermediate or final product (finished assembly). For the sake of illustration, this rearrangement represents the basis for comparing or correlating data from different machines. This means that not only the influence of process parameters on the processing results of a single machine can be examined. Rather, the (combinative) effect of a plurality of process parameters associated with different processing machines can be evaluated on the characteristic properties or quality of the intermediate product, in particular the final product. This advantageously allows an automatic optimization of the most diverse process parameters with respect to the best quality of the intermediate and final product.

In a common database shared by multiple machines and/or inspection machines, a database having correlated data sets, appropriate adjustment of the process parameters of the processing machines and/or appropriate adjustment of the thresholds of the inspection machines or (gate) separation devices can improve the manufacturing process of electronic assemblies in two ways. Firstly, the quality of the electronic assemblies or final products produced can be improved. Alternatively or in combination, the proportion of defect-free (final) products that are incorrectly separated in the manufacturing process can be reduced.

The described relative rearrangement of the two (different) coordinate systems is carried out according to the invention so that the product-specific structures of the printed circuit board, which are of course detected and processed or processed by various machines in identical and different coordinate systems for (one and the same) printed circuit board, overlap as much as possible in the two coordinate systems after the rearrangement. In explanation, this means that the (two) geometrical descriptions of the product-specific printed circuit board structures are adapted to one another by the described rearrangement so that an exact geometrical correlation of the two data sets can be carried out.

In this document, the term "correlation" is understood to mean any type of geometrical relationship between coordinates in different coordinate systems, such that the same structure of a printed circuit board is described as the same structure in both coordinate systems (and in both data sets). For example, a particular pad on a printed circuit board that is provided for a particular electrical connection contact of a particular component of an electronic assembly should be described as the same pad in both data sets. It is clear that the correct geometrical realignment is of utmost importance.

The correlation of different data sets can take place in any appropriately programmed data processing device where the data sets are located, at least temporarily. It does not matter whether these data sets are obtained from each machine in the production line by means of an appropriate data transmission, or whether the two data sets are already stored in the relevant data processing device and transmitted to the relevant machine.

The correlation, i.e. the result of the correlation, can be recorded in the form of a table, for example, also called a correlation table. Such a correlation table represents a particularly simple but effective way of describing or recording the relationships between different contents or elements of different data sets. In the case described herein together with the product-specific information of the printed circuit board, the component connection contacts of the component and the component connection areas of the printed circuit board on which the component is to be mounted can be correlated with each other, for example, as described in detail below.

In this document, the term "machine" is understood to mean any type of device contributing to the production of electronic assemblies. The machine may be a processing machine or an inspection machine. The processing machine of the described production line is, for example, a soldering machine, such as a solder paste printing machine, a placement machine, or a reflow oven, as described in the introduction. The inspection machine may be an optical inspection machine that detects intermediate or final products in two or three dimensions. The inspection machine may be arranged in the most different positions on the production line.

(a) When arranged along the transport direction, the result of the solder paste printing process can be inspected downstream of the solder paste printing machine and upstream of the placement machine. Such inspection machine is referred to in this document as a "solder paste inspection machine."

(b) When arranged downstream of the placement machine and upstream of the soldering machine, the result of the placement process can be inspected. Such an inspection machine is referred to as a "placement inspection machine" in this document.

(c) When arranged downstream of a soldering machine, the (reflow) soldering results of components placed on each component connection area or pad of a printed circuit board can be inspected. Such inspection machines, which generally inspect the final products of a production line, are referred to in this document as "placement inspection machines."

In this document, the term "position information" is to be understood to mean any position-specific indication of a point or location on a printed circuit board. The position information is in particular the location of a component connection area or pad on the surface of a printed circuit board which makes electrical contact with the connection contact of a component when the component is mounted on the printed circuit board. The position information for one and the same printed circuit board location will naturally have different values in different coordinate systems (of different machines).

In this document, the term "characteristic information" is to be understood to mean any information about the spatial physical, optical and/or electrical state or properties of a specific location on a printed circuit board, such as a pad, or of a specific (small) area on a printed circuit board. The spatial physical characteristic information may be geometric two-dimensional information, such as an indication of the location, size and/or shape of a pad. Alternatively or in combination, the spatial physical characteristic information may be three-dimensional information, such as an indication of the amount of solder paste applied on a specific pad. The optical characteristic information may be information about the color and/or reflectivity of a pad, which may be an indication of possible corrosion or cold solder joints of the pad, for example. The electrical characteristic information may be indicative of the electrical conductivity of a conductor track on the surface of the printed circuit board, for example.

In this document, the term "product-characteristic structure" is to be understood to mean any structural or spatial physical feature that is characteristic of a particular type of printed circuit board. In particular, one type of printed circuit board can be distinguished from another type of printed circuit board based on (a) its product-characteristic structure(s). Such features can be, for example, the location, size, and/or shape of pads.

In this document, the term "repositioning" can be any type of geometric change in the coordinate system used to describe the relevant data sets. In particular, repositioning can be a displacement, a rotation, and/or, in some application cases, a distortion of at least one of the two coordinate systems each associated with one of the two data sets.

In the described "realignment", the two data sets based on the coordinate system are geometrically transformed so that the positional information of the two data sets for a selected location on the printed circuit board in question is closer to each other than before the realignment. Preferably, the positional information is as close to each other as possible or even overlaps. For example, the two coordinate systems are adapted to each other by means of a suitable coordinate transformation. As described above, this coordinate transformation may include translation, rotation and/or distortion.

The described "rearrangement" can be implemented by means of known mathematical and geometrical calculations. Like any other calculation or algorithm, it can occur in any data processing unit of the relevant production line for electronic assemblies. This data processing unit can be associated with a specific machine. Alternatively or in combination, it can also be a central or higher-level data processing unit that is directly or indirectly communicatively coupled to the individual machines.

In this document, the term "sum of distances between two pieces of position information associated with each other" may be understood to mean the sum of the distances between two pieces of position information in different coordinate systems, where the two pieces of position information are coordinate points associated with the same location on the printed circuit board. The sum is formed by adding the absolute values of the distances for the different locations on the printed circuit board. The sum may also be the sum of all squared distances between the position information associated with each other with respect to one and the same location on the printed circuit board. Thus, the re-alignment may be similar to the best fit ("best fit") of a mathematical function to a plurality of measurement points, which are distance values in the described method, with a (statistical) spread.

At this point, it should be emphasized again that the two data sets described control the relevant machine. This means that the actual operation of the machine in question depends on the data sets associated with it. Thus, according to the invention, not only does the data set contain information about the product-specific structure of the relevant printed circuit board, but rather the data set also contains instructions or information about how the relevant machine performs its task. This applies to all machines mentioned, which may be processing machines or inspection machines, as described below.

Specifically, in the case of a processing machine, a suitable controller ensures the processing of the relevant printed circuit board. For example, in the case of a placement machine, this is the exact positioning of the components on the printed circuit board. In the case of an inspection machine, the relevant data set is not or is not exclusively a measurement data set with the results of a previously performed inspection. Rather, the relevant data set (also) represents an inspection data set which controls the operation of the relevant inspection machine. Thus, a data set or inspection data set for an inspection machine is a work recipe (typically containing a plurality of individual work instructions) for the relevant inspection machine, just as a process data set is a work recipe for a processing machine.

In this context, it is self-evident that the operation of the inspection machine must also be controlled. This is because, for reasons of efficiency, it cannot be justified to inspect all areas of the (intermediate) product, i.e. at least partially processed printed circuit boards, with the same accuracy. This would actually significantly increase the time it takes to carry out the inspection. For example, areas of the inspection object that are particularly relevant can be inspected with particular accuracy, while other areas can be inspected with less accuracy or not at all.

According to an exemplary embodiment of the present invention, the first machine is a first processing machine that creates a physical change in a product comprising a printed circuit board and a product-feature structure by a processing process. The physical change may include the addition of a product-feature structure and/or a change in a property of the product-feature structure. The product-feature structure may be, for example, a volume of solder paste applied to or on (at least) one component connection area or pad, for example by solder paste printing, which is formed on a surface of the printed circuit board in question. The product-feature structure may also be a two-dimensional or three-dimensional spatial position of an electronic component or electronic component placed on or on the printed circuit board by a placement machine.

According to another exemplary embodiment of the present invention, the first processing machine is a machine selected from the group consisting of: (i) a solder paste printing machine for selectively applying solder paste to component connection areas of the printed circuit board; (ii) a placement machine for placing electronic components on the printed circuit board; and (iii) a soldering machine for melting the solder paste located between the component connection areas of the printed circuit board and electrical connection contacts of components placed on the printed circuit board.

The described selection of processing machines has the advantage that all typical processing machines in an electronic component production line are included. In principle, the described method can be used for data correlation between all types of processing machines in a production line. This applies to all machines that work with specific-position information or provide specific-position information as part of a measurement.

According to another exemplary embodiment of the present invention, the second machine is a first inspection machine which detects a product-feature structure by means of an inspection process. The first inspection machine or, more precisely, a data processing device which is included in the first inspection machine or connected downstream of the first inspection machine can compare the detected actual product-feature structure with a corresponding predetermined target product-feature structure and thereby determine a quality value for the manufactured and detected product-feature structure. This quality value can be used to suitably adapt the process parameters of the processing machine and/or at least one threshold value of the first inspection machine or of the further inspection machine.

The first inspection machine preferably detects not only a single product-feature structure but also a plurality of product-feature structures. The data processing device can then compare one or more or at least some of the detected actual product-feature structures with corresponding predetermined target product-feature structures and determine a plurality of quality values and/or higher-level quality values for the produced and detected product-feature structures therefrom.

In this document, the term "quality value" is understood to mean any parameter or parameter value that determines or at least helps to determine the quality of a manufactured electronic assembly. Such parameters include, for example, the location and quantity (volume) of individual solder paste applications, the exact placement location, and the visual appearance of the solder after soldering, which may indicate a "cold solder joint". This list is by no means exhaustive and can be supplemented almost arbitrarily by a person skilled in the art of placement technology.

As detailed below, the parameters described above can be the position and height of the placed or soldered components, and of course also the amount of soldering paste used for each soldering connection. In this context, it is clear that these parameters are related to the quality of the produced electronic assembly, otherwise there would be no need to detect these parameters in the relevant inspection machine.

The first inspection machine described may be an optical inspection machine for detecting product-feature structures in one dimension, preferably in two dimensions, more preferably in three dimensions. This has the advantage of being able to perform inspections quickly and with high accuracy.

According to another exemplary embodiment of the present invention, the first inspection machine is a machine selected from the group consisting of (i) a solder paste inspection machine for detecting applied solder paste; (ii) a placement inspection machine for detecting placed components; and (iii) a soldering inspection machine for detecting soldered components.

Detection of solder paste may include, for example, detection of the location, volume and/or shape of the solder paste application. All of these observables naturally (strongly) influence the quality of the contact of the components yet to be placed.

Detection of a placed component may include, for example, the type of component, the placement location in the plane of the printed circuit board, and/or the height location of the component above the surface of the printed circuit board (the component is placed in a volume of solder paste prior to subsequent soldering). It is clear that all of these observable items have a significant impact on the subsequent soldering process and the final electrical contact of the component.

The detection of the soldered components can also include the type of the soldered components, their final position on the printed circuit board plane and/or their height position above the printed circuit board surface (after soldering the components are temporarily melted and then solidified and then settled on a certain volume of solder paste). In particular, it can be detected whether the component connection contacts (of the components) are correctly soldered to the corresponding component connection areas (of the printed circuit board) and thus make correct electrical contact. It is clear that all these observables have a significant influence on the quality of the final end product, i.e. the produced electronic assembly. Therefore, the detection by the described soldering inspection machine can be an important part of the final quality analysis of the finished (final) product. The final quality analysis, optionally together with at least one non-final quality analysis, can be used to optimize the process parameters of the processing machine and/or the threshold values of the first inspection machine and optionally of the further inspection machines by means of a suitable learning process.

In an embodiment where the first machine is a (first) processing machine and the second machine is a (first) inspection machine, it should be noted that the measurement data and the process data can advantageously be merged by the described method. This can be done in particular for the purpose of optimizing the process data with the help of the measurement data. This can advantageously enable a particularly accurate analysis of the automated production.

The described selection of inspection machines has the advantage that all typical inspection machines of an electronic component production line are included. In principle, the described method can therefore be used for data correlation between all types of inspection machines of a production line and optionally also for data correlation between all processing machines and all inspection machines of a production line for electronic assemblies.

According to another exemplary embodiment of the present invention, the method comprises the steps of: (a) providing a third data set from a third machine, the third data set being (al) associated with the third machine, (a2) controlling operation of the third machine, and (a3) the third data set:

Further comprising the step of providing a third data set, the third data set including third location information and third feature information for feature target characteristics of a product-feature structure of the printed circuit board at a plurality of locations on the printed circuit board,

The above geometric overlapping step is

further comprising geometrically overlapping said third location information with said first location information and/or said second location information; and

The above relocation steps are

The sum of the three distances between each of the three correlated location information fragments, i.e.

At one identical point on the above printed circuit board,

(i) a first distance between the first location information and the associated second location information;

(ii) a second distance between the third location information associated with the first location information and the second location information and the associated second location information, and

(iii) so that the sum of the third distances between the third location information and the first location information is reduced;

It additionally includes the relocation of the above third location information.

The described correlation between three (particular machine) data sets has the advantage that the production process of an electronic assembly is jointly analysed not only on two but also on three different machines (processing machines and/or inspection machines) and that the analysis results are used for an improved adaptation of the process parameters of the processing machines and/or of the threshold values of the first and optionally of further inspection machines.

Depending on the specific application, the third machine may be a processing machine or an inspection machine, and in principle, any type of processing machine described above is possible. In the case of a processing machine, the third machine must be a type of machine such that the production line does not have two solder paste printing machines and two soldering machines. However, the production line may include more than two placement machines. In the case of an inspection machine, the type of the inspection machine is also the same.

According to another exemplary embodiment of the present invention, the third machine is a second processing machine that creates additional physical changes to the product including the printed circuit board and the product-feature structure by the processing process.

Additional physical changes may also include adding product-feature structures and/or changing properties of the product-feature structures. As described above, the product-feature structures may be electronic components placed or arranged on a printed circuit board, for example, by a placement machine. The product-feature structures may be associated with a pre-soldering state or a post-soldering state.

It should be noted that the above-described second machine implemented as a first inspection machine can be arranged between two processing machines with respect to the transport direction of the production line. In this case, the first inspection machine detects processing by the first processing machine, but does not detect processing by the second processing machine.

The first inspection machine is preferably arranged downstream of the two processing machines. This means that the “work” of both processing machines can be inspected jointly.

More preferably, no additional processing machine is arranged downstream of the first inspection machine. This means that the first inspection machine inspects the end product of the production line. The inspection of the end product and the appropriate feedback of the inspection results to the two processing machines have the advantage that the process parameters of the processing machine(s) can be adapted or optimized with respect to the final desired product characteristics of the manufactured electronic assembly.

According to another exemplary embodiment of the present invention, the method comprises the steps of: (a) providing a fourth data set from a fourth machine, wherein (a1) the fourth data set is associated with the fourth machine, (a2) controls operation of the fourth machine, and (a3) the fourth data set:

The method further comprises the step of providing a fourth data set, the fourth data set including fourth location information and fourth feature information for feature target characteristics of a product-feature structure of the printed circuit board at a plurality of locations on the printed circuit board.

In addition, the geometric overlapping step further includes geometrically overlapping the fourth location information with the first location information, the second location information, and/or the third location information. In addition, the repositioning step further includes repositioning the fourth location information such that a sum of six distances between each of the four correlated location information fragments, i.e., a sum of (i) the first distance, (ii) the second distance, (iii) the third distance, (iv) a fourth distance between the fourth location information and the third location information, (v) a fifth distance between the fourth location information and the second location information, and (vi) a sixth distance between the fourth location information and the first location information, is reduced.

It should be noted that four or more data sets, each associated with a machine in a production line for electronic assemblies, may also be correlated using the described method, creating a larger database for optimizing the assembly production process.

Depending on the specific application, the fourth machine may be a processing machine or an inspection machine. As to the type of machine, the same applies to the fourth machine as to the third machine described above for different machines.

According to another exemplary embodiment of the present invention, the first machine is a first processing machine; the second machine is a first inspection machine that detects a product-feature structure at a first inspection point along the production line; the third machine is a second processing machine arranged downstream of the first processing machine with respect to the transport direction of the production line; and the fourth machine is a second inspection machine that detects a product-feature structure at a second inspection point along the production line.

With respect to the transport direction of the production line, the second inspection is preferably upstream of the first inspection point, and more preferably between (a) the first processing position by the first processing machine and (b) the second processing position by the second processing machine.

A preferred configuration of a production line according to this exemplary embodiment is characterized by an arrangement and distribution of machine types, in which four different machines are arranged along the transport direction of the production line in the following order:

Position 1: The first machine or first processing machine is a solder paste printing machine;

Position 2: The fourth machine or the second inspection machine is a solder paste inspection machine;

Position 3: The third machine or second processing machine is a placement machine; and

Position 4: The second machine or the first inspection machine is a placement inspection machine or a soldering inspection machine.

If the second machine or the first inspection machine is a soldering inspection machine, the third processing machine, i.e., the soldering machine, is located upstream as the fifth machine. Additionally, in this case, the placement inspection machine implemented as the third inspection machine for directly inspecting the assembly result may optionally be located between the second processing machine implemented as a placement machine and the soldering machine.

In the above described embodiment having a total of six machines, the different types of machines are preferably arranged in the following order:

Position 1: The first machine or first processing machine is a solder paste printing machine;

Position 2: The fourth machine or the second inspection machine is a solder paste inspection machine;

Position 3: The third machine or second processing machine is a placement machine;

Position 4: The sixth machine or third inspection machine is a placement inspection machine;

Position 5: The fifth machine or third processing machine is a soldering machine; and

Position 6: The second machine or first inspection machine is a soldering inspection machine.

In many embodiments, the placement machine is a system comprising two or more placement devices. The placement devices may each have one or more placement heads, which are movable in a known manner through a portal system to pick up parts from a parts supply device in a placement operation and place them on a printed circuit board currently positioned in a placement area of the placement device.

According to another aspect of the present invention, a method for adapting process parameters for a process for the production of electronic assemblies by automated production in a production line is described. The method comprises the steps of performing the method described above, wherein said performing steps are performed by at least three machines, wherein (a) a first machine is a first processing machine and the first data set comprises a first process data set, (a2) a second machine is a first inspection machine and the second data set comprises the first inspection data set, and (a3) a third machine is a second processing machine and the third data set comprises the second process data set. The method for adapting process parameters comprises the steps of (b) determining, by the first inspection machine, a first deviation between an actual characteristic and a target characteristic of a product-feature structure in a first area of a printed circuit board associated with a first (spatial) area of the printed circuit board; (c) (i) in each case, further comprising a step of generating a first combined data set based on at least a first portion of said first process data set, (a first portion of) said second process data set, and at least a first portion of said first inspection data set, said first portion being associated with a first area of said printed circuit board, and (ii) further based on the relocated first position information and/or the relocated second position information and/or the relocated third position information. The process parameter adaptation method further comprises a step of (d) adapting the first process parameters of the first processing machine and/or the second process parameters of the second processing machine based on the generated first combined data set and the determined first deviation.

The method described for adapting the process parameters is based on knowledge of the causes of undesired (first) deviations of the actual characteristics from the desired target characteristics of the product-feature structure(s) by joint consideration of several possible different processing machines, which allows in particular to adjust the process parameters well. This adaptation leads to significantly better results or improved production compared to conventional adaptations that only consider the process data set of a single processing machine. The causes of these undesired deviations are suboptimally set process parameters of the processing machines involved in the production.

In order to be able to perform such a joint consideration with the help of a combined data set, it is essential to generate a combined data set using data or information related to the relevant first area of the printed circuit board. Since the data sets from different machines (processing machines and/or inspection machines) are usually based on different (format) descriptions and different coordinate systems, it is necessary to first perform a positionally precise correlation of the various data sets described above. This is the only way to ensure that the information sets contained in the various data sets are positionally precise correlated with each other with respect to each location or each area of the printed circuit board. The described correlation can therefore also be understood as a positionally precise combination of information.

To illustrate, the above-described method for correlating different data sets, by adaptation of the described process parameters, ensures a positionally accurate transformation of different machine-specific data sets (process data sets and/or inspection data sets). During this “transformation”, the “language” and/or “data format” of the different data sets is transformed to enable a positionally accurate correlation of the information contained in the different data sets.

The combined data set described herein represents a positionally accurate combination of information from the output data sets with respect to each different region of the printed circuit board. In other words, this means that the information contained in the two process data sets and the inspection data set is positionally accurate merged with respect to the actual printed circuit board.

The flow of the above described reordering and data set combination data sets is related to each other as follows: In order to positionally accurately merge feature information between the feature target characteristics of the product-feature structure of the printed circuit board, it is necessary to first transform the different coordinate systems of the relevant data sets so that the information can be positionally accurately merged. As already mentioned above, reordering, which may include rotation and/or distortion, represents this transformation. This is done so that the total of the specified distance is reduced or minimized.

According to another embodiment of the present invention, the first (space) region of the printed circuit board is a region of the printed circuit board in which a first deviation between an actual characteristic and a target characteristic of the product-feature structure is greater than a second deviation between the actual characteristic and the target characteristic of the product-feature structure in a second (space) region of the printed circuit board associated with a second location on a surface of the printed circuit board, wherein the second location or the second region is different from the first location or the first region.

For example, the first area is more problematic or critical with respect to the quality of the assembly to be manufactured than the second area. This can be due, for example, to the fact that the first area contains smaller printed circuit board structures, in particular also smaller component connection areas or smaller pads that are less spaced from each other. In this context, it is clear that such "fine" structures are much more difficult to process accurately than larger structures (in the second area). Optimizing the process parameters by focusing on particularly problematic or critical areas can be particularly advantageous, especially if these areas are areas of the printed circuit board that cannot be repaired after soldering.

An additional advantage of the exclusive or preferential consideration of these critical areas is that there is no need to unnecessarily process data that has little or no effect on the most optimal process parameter adaptation. As a result, the implementation of the described method becomes less demanding with respect to the required computing power. In addition, the method can be performed much faster with the specific computing power available.

The selection of different areas of the printed circuit board can be based on the a priori knowledge and/or experience of the operator. Furthermore, the selection can also be based on an at least almost complete inspection (which is rarely performed) of the entire area of the printed circuit board, i.e. the degree of deviation is determined for different locations or areas of the printed circuit board.

According to another exemplary embodiment of the present invention, the method further comprises the steps of: (a) determining, by the first inspection machine, a second deviation between an actual characteristic and a target characteristic of the product-feature structure in a second (spatial) area of the printed circuit board; (b) generating a second combined data set based on at least a second part of the first process data set, a second part of the second process data set, and a second part of the first inspection data set, in each case, the second part being associated with a second area of the printed circuit board, and (b2) further based on the relocated first position information and/or the relocated second position information and/or the relocated third position information; and (c) adapting the first process parameters of the first processing machine and/or the second process parameters of the second processing machine further based on the generated second combined data set and the determined second deviation. Taking into account the deviation(s) in the second area, the process parameters can be adapted much more precisely with regard to the best possible quality of the finished end product.

It should be noted that the process parameter adaptation described here can also be performed on production lines with more than two processing machines and/or on production lines with more than one inspection machine. To do this, it is only necessary to create suitable combined data sets, where it must of course always be ensured that the information contained in the various process data sets and inspection data sets is positionally correctly merged or positionally correctly combined with one another.

According to another exemplary embodiment of the present invention, the adaptation of the first process parameters of the first processing machine and/or the second process parameters of the second processing machine is carried out repeatedly by means of at least one learning algorithm. This has the advantage that the process parameters can be improved, for example, by means of artificial intelligence. For this purpose, it makes sense if the described method is carried out individually or at least for the production of a large number of assemblies within the framework of the production of a specific type of electronic assembly. As a result, the data processing device on which the required learning algorithm is carried out receives a large amount of learning data. This makes it possible to adapt the process parameters particularly appropriately with regard to the best possible quality of the end product electronic assembly.

According to another aspect of the present invention, a production line for the automated production of an electronic assembly is described, the production line having a printed circuit board and a plurality of electronic components attached to the printed circuit board and electrically interconnected by conductor tracks. The described production line has (a) a first machine for processing a product including the printed circuit board and a product-feature structure; (b) a second machine for inspecting the product-feature structure; (c) a third machine for processing the product; and a data processing device communicatively connected to the first machine, the second machine, and the third machine and arranged to perform the above-described method for adapting process parameters.

According to another aspect of the present invention, a computer program is described for adapting process parameters for a process for producing electronic assemblies by automated production in a production line. The computer program is arranged to perform the method described above for adapting process parameters when executed by a data processing device of the production line.

According to this document, the naming of such a computer program is equivalent to the term of a program element, a computer program product and/or a computer-readable medium including commands for controlling a computer system to control the operation method or methods of the system in an appropriate manner to achieve the effects associated with the method according to the present invention.

The computer program can be implemented as computer-readable instruction codes in any suitable programming language. The computer program can be stored in a computer-readable memory device (such as a CD-ROM, DVD, Blu-ray disc, removable drive, volatile or nonvolatile memory, internal memory/processor, etc.). The instruction codes can program a computer or other programmable device to perform a desired function. Additionally, the computer program can be provided on a network such as the Internet, where the user can download it as needed.

The present invention can be realized not only by a computer program, i.e. software, but also by one or more special electronic circuits, i.e. hardware or any other hybrid form, i.e. software components and hardware components.

Additional advantages and features of the present invention arise from the following exemplary description of a presently preferred embodiment.

Figure 1 illustrates a production line for electronic assemblies having a high-level data processing unit for correlating process data and inspection data from various processing or inspection devices on the production line.
Figure 2 illustrates the correlation of process data and inspection data for subsequent optimization of process parameters of a processing machine, particularly implemented as a solder paste printing machine.
Figure 3 illustrates a correlation data set implemented as a correlation table for two different types of printed circuit boards.
Figure 4 illustrates the optimization of process data for placement using a block diagram.
Figure 5 illustrates the relocation of location data.

In the following detailed description, it should be noted that features or components of different embodiments that are identical or at least functionally identical to corresponding features or components of other embodiments are provided with like reference numerals or identical reference numerals for the last two digits of the reference symbol of the corresponding identical or at least functionally identical feature or component. In order to avoid unnecessary repetition, features or components that have already been described based on the previously described embodiments are not described in detail any further at a later point.

It should also be noted that the following described embodiments represent only a limited selection of possible variations of the embodiments of the present invention. In particular, it is possible to combine features of the individual embodiments in a suitable manner so that a plurality of different embodiments will be apparent to those skilled in the art together with the embodiments explicitly described herein.

Figure 1 illustrates a production line (100) for electronic assemblies. The production line has various devices arranged along a transport path of printed circuit boards. The transport direction of the printed circuit board transport path is indicated by an arrow marked "T" in Figure 1.

Along the transport direction (T), the production line (100) has an input station (102) into which prefabricated but not yet printed circuit boards are supplied, in a known manner. Downstream of the input station (102), there is a device (104) for marking the printed circuit boards using a laser beam.

Next, as a first processing machine, a solder paste printing machine (110) is followed, which selectively applies solder paste to specific points on the printed circuit board by a known screen printing method. These points are typically component connection areas or pads on the surface of the relevant printed circuit board. The application of solder paste is not a simple process in practice, since solder paste must be applied to each component connection area at an exact location and in an exact amount. For this purpose, a plurality of process parameters of the solder paste printing machine (110) must be set precisely. These process parameters include, for example, the speed of a squeegee, which is guided along the surface of the so-called printing screen and which delivers the viscous solder paste to the openings of the printing screen in an exact amount.

Downstream of the solder paste printing machine (110), there is a solder paste inspection machine (120) which optically verifies that the solder paste printing is of sufficient quality to warrant further processing of the printed circuit board. The solder paste inspection machine (120) is also referred to as an SPI machine.

The placement system then follows the transport direction T. According to the exemplary embodiment illustrated here, the assembly system comprises a total of three placement machines (130), each of which places a certain number of (different) components into component positions defined by previously applied solder paste depots.

Downstream of the assembly system, a placement inspection machine (140) is followed, through which the placement of the printed circuit boards performed by the three placement machines (130) is verified for correctness. According to the exemplary embodiment illustrated here, the placement inspection machine (140) optically detects the placed components in two dimensions (2D) and three dimensions (3D). The placement inspection machine (140) is a known automatic optical inspection (AOI) machine.

Downstream of the AOI machine (140), there is a soldering machine (150) implemented in a manner known as a so-called reflow oven. The viscous solder paste is melted in this reflow oven (150) and after the solder paste has cooled, the components make solid and electrically conductive contact with each component connection area.

Downstream of the reflow oven (150), another printed circuit board buffer (152) follows, in which a certain number of soldered printed circuit boards can be stored or buffered.

According to the exemplary embodiment illustrated herein, a soldering inspection machine (160) follows (downstream), through which it is verified whether the soldering process performed in the reflow oven (150) is (qualitatively) successful. The soldering inspection machine (160) is also an AOI machine known herein.

The AOI machine (160) is followed by an output station (162). Completely processed electronic assemblies can be removed from there by an operator.

In production lines known in the art, it is customary to set the process parameters of individual processing machines (solder paste printing machine (110), placement machine (130), reflow oven (150)) which are directly associated with each inspection machine or downstream of each inspection machine, based on the inspection data of the inspection machines (solder paste inspection machine (120), placement inspection machine (140), soldering inspection machine (160)). Optimization of the coupled process parameters in terms of process technologies which are not completely independent of each other with regard to the final quality of the manufactured electronic assembly is not known.

The production line (100) described here is provided with a higher-level data processing device (μP), which collects inspection data from various inspection machines (120, 140, 160) in particular and jointly evaluates them. Furthermore, current process data from the processing machines (110, 130, 150), in particular the solder paste inspection machine (120), are collected and evaluated together with inspection data regarding the highest possible quality of the end product, i.e. the produced electronic assembly. For this purpose, it is preferable to use methods or algorithms of artificial intelligence. This evaluation leads to optimized process parameters, which can be stored in a database (DB).

However, the joint evaluation of data sets provided by different machines is not so simple. In terms of content, the different data sets relate to all (relevant) locations on each printed circuit board. However, each system typically uses its own data format for this purpose. These data formats differ, in particular, in the process-specific location descriptions for the different locations and components on the printed circuit board. Therefore, it is necessary to re-arrange the corresponding location information of the different data sets and to geometrically superimpose them so that they "match" as much as possible. A corresponding method for correlating the different data sets, which is performed in a data processing device (μP) and represents a central aspect of the invention described in this document, is described in more detail below.

The core of the present invention described in this document is to correlate the functions of various machines of a production line (100) with each other. This is hereinafter referred to as a so-called "Inter-Device Data Correlation Function" (IDDCF). Using this IDDCF, the process sequence of the entire production line (100) can be optimized. To this end, measurement data of various inspection machines and process data of at least one of various processing machines are collected, and correlation data is determined so that all machines metaphorically "speak the same language". The correlation data included in the correlation data set can be used to set optimized process parameters for various processing machines, thereby optimizing the entire manufacturing process (collectively).

In other words, the data processing unit (μP) connects at least some of the machines and retrieves detailed job data, also called "job recipes" in this document. These job recipes contain instructions or information on how the relevant machines should perform the job. For clarity: this applies to inspection machines as well as processing machines.

A job recipe for a solder paste printing machine (110) includes process parameters such as (without limitation) the size and format of the printed circuit board involved, the location on the printed circuit board where the solder paste is to be applied, the speed of the squeegee mentioned above, and the cleaning cycle of the squeegee.

A job recipe for a solder paste inspection machine (120) includes, for example, a layout description of where solder paste reservoirs are expected to be located and how these reservoirs should appear in 2D and 3D to the solder paste inspection machine (120). Additionally, the layout description may also include information about the expected or desired amount of solder paste and optionally a tolerance.

The work recipe for the placement machine (130) includes process information such as, for example, the vacuum value for each placement position, as well as the negative pressure at which the part is held by the suction gripper, the pressure or force at which the part is placed on the printed circuit board, the movement speed of the placement head, etc.

The job recipes for both AOI machines (140 and 160) include information such as the (selected) solder connections to be inspected (upstream and downstream of the reflow oven (150), target locations and target heights for placed or soldered components, etc.

The above-described exemplary work recipes are correlated with each other using the above-described IDDCF. In particular, the positional information of all components and their electrical connections are analyzed positionally precisely, i.e. through the precise geometrical superposition of the product-feature structure of the printed circuit board.

It should be noted that using the IDDCF described here, the elimination of defective (intermediate) products from the production process at the so-called gate is by no means excluded. However, it is possible to adapt the internal threshold values of the inspection machines in order to classify (intermediate) products as defective in order to reduce the possibility of false error messages within the framework of an optimized process flow. Furthermore, as already described above, it is possible to adapt the process parameters for the various processing machines based on the measurement results of the inspection machines to improve the quality of the overall production. This advantageously leads to an overall qualitatively improved production process and a reduced cycle time, since the number of false error messages can be reduced, in particular by appropriate adaptation of the internal threshold values.

Using known printed circuit board traceability within the production line and the IDDCF mentioned above, the following correlations emerge in particular:

(A) The printed circuit board identification number for the AOI machine corresponds to the printed circuit board identification number for the placement machine.

(B) Parts detected by the AOI machine correspond to parts placed by the placement machine.

(C) Any connection or pin identification number of the AOI machine corresponds to a component connection area identification number used by the SPI machine.

Additionally, the placement positions used by the placement machines (130) may be correlated with part receiving positions that may be obtained from process data management of each placement machine (130). Such position correlation or correlation to identification numbers may be re-determined whenever at least one work recipe for at least one machine involved in the production line (100) is changed.

Once these correlations are available, they can be used to optimize the process flow for subsequent printed circuit boards.

Figure 2 illustrates the correlation of process data and inspection data for subsequent optimization of process parameters of a processing machine, particularly implemented as a solder paste printing machine.

According to the exemplary embodiment illustrated herein, the process starts with a work recipe for solder paste inspection, placement inspection and placement process, which is collected by a placement machine (130) at step (SI). The work recipe contains detailed information, in particular, about the layout of each printed circuit board, the components to be placed thereon (position and size), and the connection contacts of the components.

In the next step (S2), the correlation of the above-mentioned position data takes place with the help of the IDDCF. The positions of the component connection contacts and the component positions between the work recipes used by the various machines are correlated with each other so that all the component connection contacts included in the various work recipes are accurately correlated with each other. The result of this correlation is a correlation table which accurately correlates the component connection contacts and the component connection areas (pads) for all the machines involved. This correlation is based not only on the positions on the respective type of printed circuit board, but also on the identification numbers of the components, the identification numbers of the component connection areas and/or the identification numbers of the component connection contacts. As a result, the identification names of the various machines involved in the production process and the different designations of the components and the work recipes can sometimes be accurately correlated. In particular, this correlation table can be used to correlate (a) the work recipes of at least one AOI inspection machine and a solder paste inspection machine and (b) the work recipes of a solder paste printing machine and a placement machine, said work recipes containing the current process parameters.

In the next step (S3), the results of various inspection machines are waited for, all of which are related to a specific printed circuit board.

As soon as the results from the various inspection machines are available, the previously determined position assignments are used in the next step (S4) to correlate these results with each other. For this purpose, the correlation table determined in step (S2) is used.

In the next step (S5), the correlation results, the (current) work recipe and the correlation data are stored in a database (DB). The database (DB) serves as the basis for so-called "big data" analyses, which are performed by a processor not shown in Fig. 2, and allows the results of the "big data" analyses to be presented to the operator via suitable visualizations. For example, the "big data" analyses can be used to find the root cause (so-called "root cause") of a defect in an electronic assembly at the end of a production line.

Additionally, this “big data” analysis can also be used to adapt the thresholds of inspection machines to isolate defective intermediate products, reducing the likelihood of false error messages.

In step (S6), the correlation results are transmitted to the respective inspection machine or processing machine. In the case of a solder paste inspection machine, in particular, the positions of the printed circuit board in relation to the application of the solder paste can be identified in relation to possible defects. In the case of a solder paste printing machine, at least some process parameters can be set so as to reduce the possibility of defective application of the solder paste, so that the defect rate of the printed circuit board printed with solder paste can be automatically reduced even before the components are placed.

FIG. 3 illustrates a correlation data set implemented as a correlation table (375) for two different types of printed circuit boards, a first printed circuit board (370a) and a second printed circuit board (370b). In a job recipe for a placement machine, the first printed circuit board (370a) is referred to as Panel 1 and the second printed circuit board (370b) is referred to as Panel 2. In a job recipe for an AOI machine, the first printed circuit board (370a) is referred to as Panel A and the second printed circuit board (370b) is referred to as Panel B. According to the exemplary embodiment illustrated herein, these correlations are stored in the first two lines of the correlation table (375). Additionally, additional correlations for different types of components are stored in the correlation table (375).

For this purpose, a unique identification number is used. According to the exemplary embodiment shown here, these are

IDs for resistors R100, R101, ..., R100_a, R101_a, ..., etc.

IDs for capacitors C1OO, C101, ..., C100_b, C101_c,

IDs for diodes D100, R101, D100_c, D101_c

and IDs Q2 and Q2_x for the ball grid array.

Fig. 4 illustrates the optimization of process data for placement using a block diagram. As already explained several times above, the optimization is based on the positionally precise superposition of descriptions of one and the same printed circuit board by different machines or different work recipes. In the upper left of Fig. 4, the layout of the printed circuit board (470) is clearly visualized in the coordinate system of the work recipe or the placement machine. In the upper right, the same layout of the printed circuit board (470) is clearly visualized in the coordinate system of the work recipe or the AOI machine.

As can be seen in the block diagram illustrated below for the two printed circuit board layouts, optimization of the process data for the placement requires positionally accurate superposition of the location descriptions of the two layouts, i.e. the descriptions of the placement locations (482) and the descriptions of the component locations (483) in the coordinate system or work recipe of each AOI machine. Here, the location descriptions (482) for the placements are dependent on the work recipe for the placements [placement work recipe (481)]. From the placement work recipe (481), the descriptions (482) and the descriptions (483), a data set (484) is generated as a correlation table that correlates the component locations in the various coordinate systems or work recipes. Based on (i) the data set (485) containing the process data for the assembly and (ii) the correlation table (484) for the component locations, an additional correlation table (486) is generated that (i) contains correlations between the placement locations and (ii) describes the component pick-up locations of each component from the component feeder. From the additional correlation table (486), optimized process data (487) are then determined for part pick-up and part placement with respect to the lowest possible percentage of incorrectly placed parts. Misplaced parts are (correctly) recognized as part defects by the AOI machine as already described above.

As already explained above, since the corresponding descriptions for different machines are different, it is not possible to simply correlate different work recipes of different machines using reference designations such as printed circuit board IDs. At least for now, there is no agreement (between different machine manufacturers) to use the same reference designations for different machines in a production line for electronic assemblies. The origins of the different coordinate systems may also be different. The only reliable data that can be used for positionally accurate correlation are the distances between the various components (centers). In order to reliably establish this positional correlation, the relative distances between the components (centers) and the component connection contacts of each component can be used. Through accurate positional correlation, different layouts can be superimposed such that the overlap between the product-feature structures, the component connection areas and the component connection contacts between the two layouts is as large as possible.

To illustrate, the multiple center point locations can be viewed as a "fingerprint" for a particular product or a particular printed circuit board. This fingerprint should be at least very similar for different data sources (different machines), since otherwise it would not be the same product. In a preferred embodiment, a positionally accurate superimposition is performed using this fingerprint for two different layout descriptions of the printed circuit board, at least one of the two layout descriptions being displaced such that the total distance between the two mutually associated component connection contacts and/or component connection areas is minimized. For example, the known so-called "nearest neighbor" algorithms can be used for this purpose.

Figure 5 illustrates an example of a re-arrangement of position data used by different machines for one and the same printed circuit board (570). The open circles represent center points of component connection contacts used for or by an AOI machine (reference numeral 140 in Figure 1). The solid circles represent center points of component connection areas used for or by an SPI machine (reference numeral 120 in Figure 1).

It should be noted that the reordering can also be performed iteratively using multiple loops. For example, a second method for improved reordering can be performed after a first method for reordering that does not provide 100% agreement.

100 production lines
102 Input Station
104 Device for marking printed circuit boards with laser radiation
110 solder paste printing machine
120 Solder Paste Inspection Machine/SPI Machine
130 Placement Machine
140 Placement Inspection Machine/AOI Machine
150 Soldering Machine/Reflow Oven
152 Printed Circuit Board Buffer
160 Soldering Inspection Machine/AOI Machine
162 Output Station
T transfer direction
μP data processing unit
DB database
Obtain 51 work recipes
52 Positional correlation between different machines
53 Results Obtained
54 Apply position correlation to machine results
55 Storage of correlated machine results
56 Real-time feedback of correlated machine results
370a printed circuit board (type 1)
370b printed circuit board (type 2)
375 Correlation Data Sets/Correlation Tables
470 printed circuit board
Blocks 481-487
570 printed circuit board

Claims (15)

A method for adapting process parameters for a process for producing electronic assemblies by automated production in a production line (100), the method comprising:
A) comprising a step of executing a correlation method for correlating different data sets associated with one and the same printed circuit board (470) from which an electronic assembly having a plurality of electronic components is constructed by the automated production;
The above correlation method is,
A step of providing a first data set from a first machine, wherein the first data set is associated with the first machine and is used to control operation of the first machine, and wherein the first data set:
A step of providing a first data set, which includes first location information and first feature information for feature target characteristics of a product-feature structure of the printed circuit board (470) at a plurality of locations on the printed circuit board (470);
A step of providing a second data set from a second machine, wherein the second data set is associated with the second machine and is used to control the operation of the second machine, and wherein the second data set:
Providing a second data set, which includes second location information and second feature information for feature target characteristics of the product-feature structure of the printed circuit board (470) at the plurality of locations on the printed circuit board (470);
A step of geometrically superimposing the first location information on the second location information;
A step of rearranging at least one of the first position information and the second position information such that the sum of distances between two pieces of correlated position information from one identical position on the printed circuit board (470), i.e., the first position information and the associated second position information, is reduced; and
A step of providing a third data set from a third machine, wherein the third data set is associated with the third machine and is used to control the operation of the third machine, and wherein the third data set:
A step of providing a third data set, which includes third location information and third feature information for feature target characteristics of the product-feature structure of the printed circuit board (470) at the plurality of locations on the printed circuit board (470);
The step of geometrically overlapping further comprises the step of geometrically overlapping the third location information with at least one of the first location information and the second location information; and
The above repositioning step is the sum of three distances between each of the three correlated position information fragments, i.e., one identical point on the printed circuit board (470).
(i) a first distance between the first location information and the associated second location information;
(ii) a second distance between the third location information associated with the first location information and the second location information and the associated second location information, and
(iii) further comprising a step of rearranging the third location information so that the sum of the third distances between the third location information and the first location information is reduced;
The first machine is a first processing machine and the first data set includes a first process data set;
The second machine is a first inspection machine and the second data set includes the first inspection data set;
The third machine is a second processing machine and the third data set includes a second process data set;
The above method for adapting the above process parameters is,
B) a step of determining a first deviation between an actual characteristic of the product-feature structure and a target characteristic in a first area of the printed circuit board (470) associated with a first location on a surface of the printed circuit board (470) by the first inspection machine;
C) A step of generating a first combination data set (375), wherein the first combination data set (375) is:
(i) at least a first portion of the first process data set, the second process data set, and the first inspection data set, the first portion being associated with a first area of the printed circuit board (470), and
(ii) generating the first combined data set (375) including at least one of the relocated first location information, the relocated second location information, or the relocated third location information; and
D) A method further comprising the step of adapting at least one of the first process parameters of the first processing machine and the second process parameters of the second processing machine to reduce the first deviation based on the generated first combination data set (375) and the determined first deviation. In the first paragraph,
A method in which the first processing machine applies a physical change to the product including the printed circuit board (470) and the product-feature structure by a processing process. In the second paragraph,
The above first processing machine
(i) a solder paste printing machine for applying solder paste to component connection areas of the printed circuit board (470);
(ii) a placement machine (130) for placing electronic components on the printed circuit board (470); and
(iii) A method, wherein the machine is selected from the group consisting of a soldering machine (150) for melting the solder paste positioned between the component connection areas of the printed circuit board (470) and the electrical connection contacts of the components placed on the printed circuit board (470). In the first paragraph,
The above first inspection machine is a method for detecting a product-feature structure by an inspection process. In paragraph 4,
The above first inspection machine
(i) a solder paste inspection machine (120) for detecting applied solder paste;
(ii) a placement inspection machine (140) for detecting placed parts; and
(iii) a method, wherein the machine is selected from the group consisting of a soldering inspection machine for detecting soldered components. In the first paragraph,
A method wherein the second processing machine creates additional physical changes in the product including the printed circuit board (470) and the product-feature structure by the processing process. In Article 6,
A step of providing a fourth data set from a fourth machine (120), wherein the fourth data set is associated with the fourth machine (120) and is used to control the operation of the fourth machine (120), and wherein the fourth data set:
Further comprising the step of providing a fourth data set, the fourth data set including fourth location information and fourth feature information for feature target characteristics of the product-feature structure of the printed circuit board (470) at the plurality of locations on the printed circuit board (470);
The step of geometrically overlapping further comprises the step of geometrically overlapping the fourth location information with at least one of the first location information, the second location information, and the third location information; and
The above repositioning step is the sum of six distances between each of the four correlated position information fragments, i.e., one identical point on the printed circuit board.
(i) the first distance above,
(ii) the second distance above,
(iii) the third distance above,
(iv) the fourth distance between the fourth location information and the third location information;
(v) a fifth distance between the fourth location information and the second location information, and
(vi) a method further comprising the step of rearranging the fourth location information such that the sum of the sixth distances between the fourth location information and the first location information is reduced. In Article 7,
The above first inspection machine detects the product-feature structure at a first inspection point along the production line (100);
The second processing machine is arranged downstream of the first processing machine with respect to the transport direction (T) of the production line (100); and
The method according to claim 1, wherein the fourth machine is a second inspection machine (120) that detects the product-feature structure at a second inspection point along the production line (100). In the first paragraph,
The first region of the printed circuit board (470) is a region of the printed circuit board (470) in which a first deviation between the actual characteristic and the target characteristic of the product-feature structure is greater than a second deviation between the actual characteristic and the target characteristic of the product-feature structure in a second region of the printed circuit board (470) associated with a second location on the surface of the printed circuit board (470),
A method wherein the second position is different from the first position. In Article 9,
A step of determining a second deviation between the actual characteristics and the target characteristics of the product-feature structure in a second area of the printed circuit board (470) by the first inspection machine;
(i) in each case, at least a second portion of the first process data set, the second process data set, and the first inspection data set, the second portion being based on the at least a second portion associated with a second area of the printed circuit board (470), and
(ii) generating a second combined data set based on at least one of the rearranged first location information, the rearranged second location information, and the rearranged third location information; and
A method further comprising the step of adapting at least one of the first process parameters of the first processing machine and the second process parameters of the second processing machine based further on the generated second combined data set and the determined second deviation. In the first paragraph,
A method wherein the step of adapting at least one of the first process parameters of the first processing machine and the second process parameters of the second processing machine is performed repeatedly by at least one learning algorithm. A production line (100) for automated production of an electronic assembly, wherein the electronic assembly has a printed circuit board (470) and a plurality of electronic components attached to the printed circuit board (470) and electrically interconnected by conductor tracks, the production line (100),
A first machine for processing a product comprising the printed circuit board and the product-feature structure;
A second machine for examining the above product-feature structure;
A third machine for processing the above product; and
A production line having a data processing device (μP) communicatively connected to the first machine, the second machine, and the third machine and arranged to perform the method of claim 1. A computer-readable recording medium storing a computer program for adapting process parameters for a process for producing electronic assemblies by automated production in a production line (100),
A computer-readable recording medium, wherein the computer program is arranged to perform the method according to claim 1 when executed by a data processing device (μP) of the production line (100). delete delete

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