Data correlation between different machines in an electronic component production line

Abstract

Data sets associated with conventional PCBs are correlated by: (a) providing a first data set from a first machine, the first data set comprising: first position information and first characteristic information related to characteristic target characteristics of PCB product characteristic structures at multiple positions on the printed circuit board; (b) providing a second data set from a second machine, the second data set comprising: second position information and second characteristic information related to characteristic target characteristics of PCB product characteristic structures at multiple positions on the PCB; (c) geometrically superimposing the first position information on the second position information; and (d) repositioning the first position information and / or the second position information to reduce the total distance between two interrelated position information starting from the same position on the PCB, i.e., the first position information and the associated second position information.

Description

Technical Field

[0001] The invention relates to the technical field of producing electronic assemblies in a production line having a plurality of machines, such as, in particular, assembly machines for assembling electronic components on printed circuit boards, and inspection machines for determining the quality of preceding processing steps. The invention relates in particular to a method for analyzing process data of such a production line and to a method for optimizing a manufacturing process for electronic assemblies. Background Art

[0002] Typically, an electronic assembly has a printed circuit board and a plurality of electronic components which are attached to the printed circuit board and are electrically connected to one another by means of conductor tracks. Such electronic assemblies are manufactured in a production line having a plurality of machines for manufacturing or processing which are connected to one another via conveyor belts, as well as machines for (optical) inspection of intermediate products. Such machines typically include:

[0003] (a) a solder paste printer for selectively applying solder paste to component connection areas or connection areas formed on the surface of an associated printed circuit board;

[0004] (b) a solder paste inspection machine, which is used to verify whether the solder paste is properly applied;

[0005] (c) at least one assembly machine for assembling electronic components onto the surface of the printed circuit board having solder paste;

[0006] (d) an assembly inspection machine for verifying whether the assembly on the printed circuit board is correct;

[0007] (e) a soldering machine or oven for melting solder paste between the component connection areas of the mounted printed circuit board and the electrical connection contacts of the associated components; and

[0008] (f) A weld inspection machine, which is used to verify whether components are correctly welded.

[0009] It is not absolutely necessary to use all three of the above inspection machines to determine if there may be a loss in quality. All that is required is one inspection machine, although this does not necessarily have to be the welding inspection machine mentioned above.

[0010] In currently known production lines for electronic assemblies, at least one inspection machine is used to sort out defective or poorly processed printed circuit boards from the production process or to direct them to repair. This sorting is carried out at a certain point in the production line with the aid of a suitable unloading device, which is descriptively referred to in this article as a gate. Obviously, for cost-effective reasons, such sorting should be carried out as early as possible.

[0011] Sorting can occur for two different reasons. The first reason could be that the processed printed circuit boards (also referred to in this article as products or intermediate products) are actually defective or of (very) poor quality. The second reason could be that the products or intermediate products fully meet the requirements, but the associated inspection machine reports an error. For the sorting of products with the aid of an inspection machine, it is therefore very meaningful to select a threshold value for detecting errors so that, on the one hand, defective products are reliably detected and, on the other hand, as few errors as possible are output.

[0012] The sorted products or the sorted processed printed circuit boards can be manually inspected by an experienced operator and reworked if necessary. Based on the results of such an evaluation, process parameters such as the scraper speed in the solder paste printer can be improved or optimized for future printing processes. In addition, the above-mentioned thresholds for detecting errors can be adjusted.

[0013] However, such manual optimization of process parameters and appropriate adjustment of thresholds for detecting errors are both very difficult in practice. Both factors depend in particular on the ability and experience of the operator involved to optimize process parameters and adjust such thresholds.

[0014] The invention is based on the object of making it easier to optimize process parameters and / or to adjust threshold values ​​for detecting errors during the production of electronic components. Summary of the invention

[0015] This object is achieved by the subject matter of the independent claims. Advantageous embodiments of the invention are described in the dependent claims.

[0016] According to a first aspect of the invention, a method for correlating different data sets is described, the different data sets being associated with a same printed circuit board on which an electronic assembly having a plurality of electronic components is built by means of automated production on a production line. The described method comprises: (a) providing a first data set from a first machine, wherein the first data set (a1) is associated with the first machine, (a2) controlling the operation of the first machine, and (a3) ​​comprising:

[0017] first location information and first feature information related to feature target characteristics of a product feature structure of a 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 (b1) is associated with the second machine, (b2) controls the operation of the second machine and (b3) includes:

[0018] (c) geometrically superimposing the first position information on the second position information; and (d) repositioning the first position information and / or the second position information to reduce the total distance between two interrelated position information starting from the same position on the printed circuit board, i.e., the first position information and the associated second position information.

[0019] The method described is based on the knowledge that by means of a suitable geometric repositioning of a first coordinate system of the first position information and / or a second coordinate system of the second position information relative to one another, process data of various machines can be compared or correlated with one another with respect to product characteristic results of an intermediate product or an end product (finished component). Such a repositioning represents, for example, a 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 (combined) effect of a plurality of process parameters associated with different processing machines can also be evaluated with respect to the characteristic properties or quality of an intermediate product and in particular of an end product. Advantageously, this enables an automated optimization of various different process parameters with respect to intermediate products and end products of the best possible quality.

[0020] By using a common database with mutually related data sets shared by multiple machines and / or inspection machines, appropriate adjustment of process parameters of the processing machine and / or appropriate adjustment of thresholds of the inspection machine or inspection device for sorting (gating) can improve the manufacturing process of electronic components in two ways. First, the quality of the produced electronic components or final products can be improved. Alternatively or in combination, the proportion of defect-free (final) products that are incorrectly sorted from the manufacturing process can be reduced.

[0021] The described relative repositioning of the two (different) coordinate systems is carried out according to the invention so that after the repositioning, the overlap of the product-characteristic structures of the printed circuit board in the two coordinate systems is as large as possible, which product-characteristic structures are of course identical for the (same) printed circuit board but are detected, processed or handled by the various machines only in different coordinate systems. This means, for example, that the (two) geometrical descriptions of the product-characteristic printed circuit board structures are adjusted to one another by means of the described repositioning so that a correct geometrical correlation of the two data sets can be carried out.

[0022] In this context, the term "correlation" may be understood to mean any type of geometric association of coordinates from different coordinate systems, which ensures that one and the same structure of a printed circuit board is also described as the same structure in both coordinate systems (and in both data sets). For example, a specific pad on a printed circuit board, which pad is provided for a specific electrical connection contact of a specific component of an electronic assembly, must be described as the same pad in both data sets. Obviously, a correct geometric repositioning is of utmost importance.

[0023] The correlation of the various data sets can be carried out in any appropriately programmed data processing device in which the data sets are at least temporarily located. It is immaterial whether these data sets are obtained from the corresponding machines of the production line by means of appropriate data transfer or whether both data sets are already stored in the relevant data processing device and are transferred from there to the relevant machine.

[0024] The correlation (i.e. the result of the correlation) can be recorded, for example, in the form of a table, which can also be referred to as a correlation table. Such a correlation table represents a particularly simple but effective way to describe or record the association between various contents or elements of various data sets. In the case of the description of the product feature information of the printed circuit board here, the component connection contacts of the component and the component connection areas of the component to be mounted on the printed circuit board can be associated with each other, for example, as described in detail below.

[0025] In this document, the term "machine" may be understood to mean any type of equipment that contributes to the production of electronic components. The machine may be a processing machine or an inspection machine. The processing machine of the described production line is, for example, a solder paste printer, an assembly machine or a soldering machine, such as 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 various different positions in the production line.

[0026] (a) In the case of being arranged in the conveying direction, downstream of the solder paste printer and upstream of the assembly machine, the result of the solder paste printing process can be inspected. Such an inspection machine is referred to herein as a "solder paste inspection machine".

[0027] (b) In the case of an arrangement downstream of an assembly machine and upstream of a welding machine, the result of the assembly process can be inspected. Such an inspection machine is referred to herein as an "assembly inspection machine".

[0028] (c) In the case of downstream arrangement of the soldering machine, the (reflow) soldering results of the components assembled on the various component connection areas or pads of the printed circuit board can be inspected. Such inspection machines are referred to as "assembly inspection machines" in this article, and are generally used to inspect the final products of the production line.

[0029] In this context, the term "position information" may be understood to mean any position-specific indication of a point or a position on a printed circuit board. In particular, the position information is the position of a component connection area or pad on the surface of the printed circuit board, which component connection area or pad is in electrical contact with the connection contact of the component when the printed circuit board is mounted with the component. Position information about the same printed circuit board position naturally has different values ​​in different coordinate systems (of different machines).

[0030] In this document, the term "characteristic information" may be understood to mean any information related to the spatial physical, optical and / or electrical conditions or characteristics of a specific location on a printed circuit board or a specific (small) area of ​​a printed circuit (such as a pad). Spatial physical characteristic information may be geometric two-dimensional information, such as an indication of the position, size and / or shape of a pad. Alternatively or in combination, spatial physical characteristic information may be three-dimensional information, such as an indication of the amount of solder paste applied to a specific pad. Optical characteristic information may be, for example, information related to the color and / or reflectivity of a pad, which may be an indication of possible corrosion of, for example, a pad or an indication of a cold solder joint. Electrical characteristic information may be, for example, an indication of the conductivity of a conductor track on the surface of a printed circuit board.

[0031] In this document, the term "product characteristic structure" may be understood to mean all structural or spatial physical features that are characteristic of a certain type of printed circuit board. In particular, one type of printed circuit board may be distinguished from another type of printed circuit board based on (a) one or more product characteristic structures. Such features may be, for example, the location, size and / or shape of a pad.

[0032] In this document, the term "repositioning" may be used to describe any type of geometric change of a coordinate system of related data sets. In particular, the repositioning may be a displacement, a rotation and / or in some applications also a deformation of at least one of the two coordinate systems, which are respectively associated with one of the two data sets.

[0033] In the described "repositioning", the two data sets, both based on coordinate systems, are geometrically changed so that the position information in the two data sets of the selected position on the printed circuit board in question is closer to each other than before the repositioning. Preferably, the position information is as close to each other as possible or even overlaps. For example, the two coordinate systems are thus adjusted to each other by means of a suitable coordinate transformation. As mentioned above, the coordinate transformation can include a displacement, a rotation and / or a deformation.

[0034] The described "repositioning" can be realized with the aid of known mathematical geometric calculations. Like all other calculations or algorithms, this can be carried out in any data processing device on the production line of the electronic assembly concerned. The data processing device can be associated with a specific machine. Alternatively or in combination, the data processing device can also be a central or higher-level data processing device that is directly or indirectly communicatively coupled to the individual machines.

[0035] In this context, the term "the total number of distances between two mutually related position information" may be understood to mean the sum of the distances between two corresponding position information in different coordinate systems, wherein the two position information are coordinate points associated with the same position on the printed circuit board. The sum is obtained by adding the absolute values ​​of the distances of the different positions on the printed circuit board. The total number may also be the sum of all squared distances between mutually related position information associated with the same position on the printed circuit board. Thus, the repositioning may be similar to the best fit ("best fit") of a mathematical function to a plurality of measurement points, which have a (statistical) distribution and are distance values ​​in the described method.

[0036] At this point, it should be emphasized again in different expressions that both data sets described control the relevant machine. This means that the actual operation of the machine in question depends on the data set associated with it. According to the invention, the data set therefore not only contains information about the product characteristic structure of the relevant printed circuit board, but the data set also contains instructions or information about how the relevant machine must perform its work. This applies to all mentioned machines, which can be processing machines or inspection machines, as described below.

[0037] In particular, 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 an assembly machine, this is the precise positioning of the components on the printed circuit board. In the case of an inspection machine, the relevant data set is not, or not entirely, a measurement data set with the results of previously performed inspections. Rather, the relevant data set (also) represents an inspection data set that controls the operation of the relevant inspection machine. Thus, a data set or inspection data set for an inspection machine is a work plan (usually with a plurality of individual work instructions) for the relevant inspection machine, just as a process data set is a work plan for a processing machine.

[0038] In this context, it is obvious that the operation of the inspection machine must also be controlled. For reasons of efficiency, this is because it would not be reasonable, for example, to inspect all areas of the (intermediate) product (i.e., at least partially processed printed circuit boards) with the same accuracy. In practice, this would significantly extend the time taken to perform the inspection. For example, those particularly relevant areas of the inspected object may be inspected with particular accuracy, while other areas may be inspected with less accuracy or even not at all.

[0039] According to an exemplary embodiment of the present invention, the first machine is a first processing machine, which physically changes a product including a printed circuit board and a product characteristic structure by means of a processing process. The physical change includes adding a product characteristic structure and / or changing the characteristics of the product characteristic structure. The product characteristic structure can be, for example, a volume of solder paste that is being or has been applied to (at least) one component connection area or pad by means of solder paste printing, and the component connection area or pad is formed on the surface of the printed circuit board in question. The product characteristic structure can also be an electronic component or the spatial position of an electronic component in two or three dimensions, which is being or has been assembled on a printed circuit board by means of an assembly machine.

[0040] 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 printer, which is used to selectively apply solder paste to a component connection area of ​​a printed circuit board; (ii) an assembly machine, which is used to assemble electronic components on a printed circuit board; and (iii) a welding machine, which is used to melt the solder paste, which is located between the component connection area of ​​the printed circuit board and the electrical connection contacts of the component assembled on the printed circuit board.

[0041] The described selection of processing machines has the advantage that it includes all typical processing machines of a production line for electronic components. In principle, the described method can therefore be used for data correlation between all types of processing machines in a production line. This applies to all machines that work with position-specific information or that provide position-specific information as part of a measurement.

[0042] According to another exemplary embodiment of the invention, the second machine is a first inspection machine, which detects product features by means of an inspection process. The first inspection machine, or more precisely a data processing device contained in the first inspection machine or connected downstream of the first inspection machine, can compare the detected actual product features with corresponding predetermined target product features and thereby determine a quality value for the manufactured and detected product features. This quality value can be used to appropriately adjust process parameters of the processing machine and / or at least one threshold value of the first inspection machine or of the further inspection machine.

[0043] Preferably, the first inspection machine detects not only a single product characteristic structure, but also a plurality of product characteristic structures. The data processing device can then compare more than one or at least some of the detected actual product characteristic structures with the corresponding predetermined target product characteristic structures and thereby determine a plurality of quality values ​​and / or higher-level quality values ​​for the produced and detected product characteristic structures.

[0044] In this context, the term "quality value" may be understood to mean any parameter or parameter value which determines or at least contributes to determining the quality of the manufactured electronic assembly. Such parameters include, for example, the location and amount (volume) of the individual solder paste applications, the exact assembly location, and the visual appearance of the solder after soldering, which may be an indication of, for example, a "cold solder joint". This list is by no means exhaustive and can be supplemented almost at will by a person skilled in the art of assembly technology.

[0045] As described in detail below, the above parameters can be the position and height of the assembled or soldered components and of course also the amount of solder paste used for the corresponding solder connection. In this context, these parameters are obviously related to the quality of the produced electronic components. Otherwise, these parameters do not even have to be detected by the relevant inspection machine.

[0046] The first inspection machine described may be an optical inspection machine, which detects product feature structures in one dimension, preferably in two dimensions, and more preferably in three dimensions. This has the advantages of fast inspection speed and high accuracy.

[0047] 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, which is used to detect the applied solder paste; (ii) an assembly inspection machine, which is used to detect assembled components; and (iii) a welding inspection machine, which is used to detect welded components.

[0048] The inspection of the solder paste may include, for example, the inspection of the position, volume and / or shape of the solder paste smear. All these observable quantities naturally have a (significant) influence on the contact quality of the components still to be assembled.

[0049] The detection of the mounted component may include, for example, the type of component, its mounted position in the plane of the printed circuit board and / or the height position of the component above the surface of the printed circuit board (the component depends on the volume of solder paste before subsequent soldering). Obviously, all these observable quantities will have a significant impact on the subsequent soldering process and thus on the final electrical contact of the component.

[0050] The detection of the welded components may also include the type of welded components, their final position in the plane of the printed circuit board and / or their height position above the surface of the printed circuit board (after welding, the components depend on the volume of the solder paste that temporarily melts and then solidifies). In particular, it is possible to detect whether the component connection contacts (of the components) are correctly welded to the corresponding component connection areas (of the printed circuit board) and therefore correctly electrically contacted. Obviously, all these observable quantities will have a significant impact on the quality of the final product (i.e., the electronic components produced). Therefore, the detection of the described welding inspection machine can become 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 optional other inspection machines by means of a suitable learning process.

[0051] It should be noted that in embodiments in which the first machine is a (first) processing machine and the second machine is a (first) inspection machine, the measurement data and the process data can be advantageously merged by the described method. In particular, this can achieve the purpose of optimizing the process data with the help of the measurement data. This can enable a particularly precise analysis advantageously for automated production.

[0052] The described selection of inspection machines has the advantage of including all typical inspection machines in an electronic component production line. In principle, the described method can therefore be used for data correlation between all types of inspection machines in a production line and optionally also for data correlation between all processing machines and all inspection machines in an electronic component production line.

[0053] According to another exemplary embodiment of the present invention, the method further comprises: (a) providing a third data set from a third machine, wherein the third data set (a1) is associated with the third machine, (a2) controls the operation of the third machine and (a3) ​​comprises: third position information and third feature information related to feature target characteristics of the product feature structure of the printed circuit board at multiple positions on the printed circuit board; wherein the geometric superposition further comprises the geometric superposition of the third position information with the first position information and / or the second position information; and wherein the repositioning further comprises the repositioning of the third position information, thereby reducing the total sum of the sums of the three distances between each of the three interrelated position information of the same point on the printed circuit board, that is, the total sum of the sums of the following items:

[0054] (i) a first distance between the first position information and the associated second position information,

[0055] (ii) a second distance between the associated second location information and third location information, the third location information being associated with the first location information and the second location information, and

[0056] (iii) A third distance between the third position information and the first position information.

[0057] The advantage of the correlation between the three (machine-specific) data sets described is that the production process of electronic components is jointly analyzed not only on two machines, but also on three different machines (processing machines and / or testing machines), and the analysis results can be used to improve the process parameters of the processing machine and / or the adaptation of the thresholds of the first testing machine and optionally other testing machines.

[0058] Depending on the specific application, the third machine can be a processing machine or an inspection machine, wherein in principle all types of processing machines mentioned above are possible. In the case of a processing machine, the third machine should be a machine of one type, so that there are not two solder paste printers nor two soldering machines in a production line. However, a production line can contain two or more assembly machines. In the case of an inspection machine, the same applies to the type of inspection machine.

[0059] According to another exemplary embodiment of the present invention, the third machine is a second processing machine that performs further physical changes on the product including the printed circuit board and the product feature structure by means of a processing procedure.

[0060] Further physical changes may also include adding product feature structures and / or changing the characteristics of product feature structures. As mentioned above, product feature structures may be, for example, electronic components that are being assembled or have been assembled on a printed circuit board by means of an assembly machine. Product feature structures may be related to the state before welding or the state after welding.

[0061] It should be noted that the above-mentioned second machine implemented as the first inspection machine can be arranged between the two processing machines relative to the conveying direction of the production line. In this case, the first inspection machine detects the processing of the first processing machine, but does not detect the processing of the second processing machine.

[0062] The first inspection machine is preferably arranged downstream of the two processing machines. This means that the "work" of the two processing machines can be jointly inspected.

[0063] Further preferably, no further processing machines are arranged downstream of the first inspection machine. This means that the first inspection machine inspects the final product of the production line. The inspection of the final product and the appropriate feedback of the inspection results to the two processing machines have the advantage that the process parameters of the processing machines can be adapted or optimized with respect to the final desired product characteristics of the manufactured electronic components.

[0064] According to another exemplary embodiment of the present invention, the method further comprises: (a) providing a fourth data set from a fourth machine, wherein the fourth data set (a1) is associated with the fourth machine, (a2) controls the operation of the fourth machine and (a3) ​​comprises:

[0065] The fourth position information and the fourth characteristic information related to the characteristic target characteristics of the product characteristic structure of the printed circuit board at multiple positions on the printed circuit board. In addition, the geometric superposition also includes the geometric superposition of the fourth position information with the first position information, the second position information and / or the third position information. In addition, the repositioning also includes the repositioning of the fourth position information, thereby reducing the total sum of the sums of the six distances between each of the four interrelated position information of the same point on the printed circuit board, that is, the total sum of the sums of: (i) the first distance, (ii) the second distance,

[0066] (iii) a third distance, (iv) a fourth distance between the fourth position information and the third position information, (v) a fifth distance between the fourth position information and the second position information, and (vi) a sixth distance between the fourth position information and the first position information.

[0067] It should be noted that more than four data sets (each associated with a certain machine of an electronic assembly production line) can also be related to each other using the described method. This creates a larger database in order to optimize the assembly production process even better.

[0068] Depending on the specific application, the fourth machine can be a processing machine or a testing machine. Regarding the type of machine, the fourth machine is the same as the third machine, which has been explained above for the other machines.

[0069] 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, which detects the product characteristic structure at a first inspection point along the production line; the third machine is a second processing machine, which is arranged downstream of the first processing machine relative to the conveying direction of the production line; and the fourth machine is a second inspection machine, which detects the product characteristic structure at a second inspection point along the production line.

[0070] With respect to the conveying 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 of the first processing machine and (b) the second processing position of the second processing machine.

[0071] The preferred configuration of the production line according to this exemplary embodiment is characterized by the arrangement and distribution of the various types of machines, wherein four different machines are arranged in the following order along the conveying direction of the production line:

[0072] Position 1: The first machine or the first processing machine is a solder paste printer;

[0073] Position 2: The fourth machine or the second inspection machine is a solder paste inspection machine;

[0074] Position 3: The third machine or the second processing machine is a placement machine; and

[0075] Position 4: The second machine or the first inspection machine is an assembly inspection machine or a welding inspection machine.

[0076] If the second machine or the first inspection machine is a welding inspection machine, the third processing machine (i.e., welding machine) is located upstream as the fifth machine. In addition, in this case, the assembly inspection machine implemented as the third inspection machine that directly inspects the assembly result can be optionally located between the welding machine and the second processing machine implemented as an assembly machine.

[0077] In the above embodiment with a total of six machines, the various types of machines are preferably arranged in the following order:

[0078] Position 1: The first machine or the first processing machine is a solder paste printer;

[0079] Position 2: The fourth machine or the second inspection machine is a solder paste inspection machine;

[0080] Position 3: The third machine or the second processing machine is an assembly machine;

[0081] 4th position: The sixth machine or the third inspection machine is the assembly inspection machine;

[0082] 5th position: the fifth machine or the third processing machine is a welding machine; and

[0083] Position 6: The second machine or the first inspection machine is a welding inspection machine.

[0084] In many embodiments, the assembly machine is a system consisting of two or more assembly devices. The assembly devices can each have one or more assembly heads, which can be moved in a known manner by means of a portal system and which, during an assembly operation, pick up components from a component supply device and assemble the components on a printed circuit board currently located in an assembly area of ​​the assembly device.

[0085] According to another aspect of the invention, a method for adjusting process parameters for a process for producing electronic components by means of automated production on a production line is described. The method comprises: (a) performing the above method, provided that the method is performed by at least three machines, wherein (a1) the first machine is a first processing machine and the first data set comprises a first process data set; wherein (a2) the second machine is a first inspection machine and the second data set comprises a first inspection data set; wherein (a3) ​​the third machine is a second processing machine and the third data set comprises a second process data set. The process parameter adjustment method further comprises (b) determining, by means of the first inspection machine, a first deviation between a target characteristic and an actual characteristic of a product feature structure in a first area of ​​a printed circuit board, the first area being associated with a first (spatial) area of ​​the printed circuit board; (c) creating a first combined data set based on (i) in each case at least a first part of the first process data set, a first part of the second process data set and a first part of the first inspection data set, wherein the first part is associated with the first area of ​​the printed circuit board, and further based on (ii) the relocated first position information and / or the relocated second position information and / or the relocated third position information. The described method for adjusting process parameters further comprises: (d) adjusting a first process parameter of the first processing machine and / or a second process parameter of the second processing machine based on the created first combined data set and the determined first deviation.

[0086] The described method for adjusting process parameters is based on the knowledge that a better adjustment of process parameters can be achieved by jointly considering the relevant causes of undesired (first) deviations of actual characteristics of a plurality of possible and different processing machines, product feature structures from the desired target characteristics. This is because such an adjustment leads to significantly better results or improves production compared to a conventional adjustment that only considers the process data set of a single processing machine. The cause of such undesired deviations is a suboptimal setting of the process parameters of the processing machines involved in the production.

[0087] In order to be able to carry out such a joint consideration with the help of a combined data set, it is essential to create a combined data set using data or information associated with 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 (formatted) descriptions and different coordinate systems, it is first necessary to carry out a positionally correct correlation of the various data sets mentioned above. This is the only way to ensure that the information sets contained in the various data sets are positionally correctly related to each other with respect to the corresponding positions or corresponding areas of the printed circuit board. The described correlation can therefore also be understood as a positionally correct combination of information.

[0088] By way of example, the above method for correlating different data sets ensures a positionally correct translation of different machine-specific data sets (process data sets and / or inspection data sets) using the described adjustment of process parameters. During this "translation", the "language" and / or "data format" of the various data sets is translated, making possible a positionally correct correlation of the information contained in the various data sets.

[0089] The combined data set described here represents a positionally correct combination of information from the output data sets associated with each different area of ​​the printed circuit board. For example, this means that the information contained in the two process data sets and the inspection data set is correctly merged in position relative to the actual printed circuit board.

[0090] The above-mentioned repositioning and the flow of data sets to the combined data set are related to each other as follows: For the correct positional merging of feature information related to the feature target characteristics of the product feature structure of the printed circuit board, it is first necessary to transform the different coordinate systems of the relevant data sets so that the information can be correctly merged in position. As mentioned above, the repositioning, which may include displacement, rotation and / or deformation, represents such a transformation. The transformation is performed so as to reduce or minimize the total number of specified distances.

[0091] According to another exemplary embodiment of the present invention, a first (spatial) region of the printed circuit board is a region of the printed circuit board in which a first deviation between an actual characteristic of a product feature structure and a target characteristic is greater than a second deviation between an actual characteristic of a product feature structure and a target characteristic in a second region of the printed circuit board, the second region being associated with a second position on the surface of the printed circuit board. Here, the second position or the second region is different from the first position or the first region.

[0092] For example, a first area is more difficult or more critical with respect to the quality of the component to be manufactured than a second area. This may be because, for example, in the first area there are smaller printed circuit board structures, in particular smaller component connection areas or smaller solder pads, which are also spaced closer to each other. In this context, it is obvious that such "finer" structures are more difficult to process correctly than larger structures (in the second area). If these areas are areas of the printed circuit board that cannot be repaired after soldering, it may be particularly advantageous to optimize the process parameters, in particular to target or focus on difficult or critical areas.

[0093] Another advantage of exclusive or prioritizing such critical areas is that for the adjustment of process parameters, data that have little or no influence on the optimal process parameter adjustment do not need to be processed unnecessarily. As a result, the described method has lower requirements on the required computing power. In addition, with a certain amount of available computing power, the method can be executed significantly faster.

[0094] The selection of different areas of the printed circuit board can be based on the prior knowledge and / or experience of the operator. In addition, the selection can also be based on an at least approximately complete (i.e., full area) inspection of the printed circuit board (which is rarely performed), wherein the degree of deviation is determined for different locations or areas of the printed circuit board.

[0095] According to another exemplary embodiment of the present invention, the method further comprises: (a) determining, by means of the first inspection machine, a second deviation between an actual characteristic and a target characteristic of a product feature structure in a second (spatial) region of the printed circuit board; (b) creating a second combined data set based on (b1) in each case 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, wherein the second part is associated with the second region of the printed circuit board, and further based on (b2) the relocated first position information and / or the relocated second position information and / or the relocated third position information; and (c) adjusting a first process parameter of the first processing machine and / or a second process parameter of the second processing machine further based on the created second combined data set and the determined second deviation. Taking into account one or more deviations in the second region allows a more precise adaptive adjustment of the process parameters according to an optimal quality of the finished end product.

[0096] It should be noted that the adjustment of the process parameters described here can also be carried out in production lines with more than two processing machines and / or in production lines with more than one testing machine. For this purpose, it is only necessary to create suitable combined data sets, wherein of course it must always be ensured that the information contained in the various process data sets and test data sets must always be correctly merged with one another in terms of position or correctly combined with one another in terms of position.

[0097] According to another exemplary embodiment of the invention, the adjustment of the first process parameter of the first processing machine and / or the second process parameter of the second processing machine is performed iteratively with the aid of at least one learning algorithm. This has the advantage that the process parameters can be improved, for example, with the aid of artificial intelligence. For this purpose, it makes sense if the described method is performed for each individual or at least for a large number of component productions within the framework of the production of a specific type of electronic component. Therefore, the data processing device on which the required learning algorithm is executed receives a large amount of learning data. This enables a particularly good adaptive adjustment of the process parameters according to the optimal quality of the final product electronic component.

[0098] According to another aspect of the invention, a production line for the automated production of electronic components is described, the production line having a printed circuit board and a plurality of electronic components attached to the printed circuit board and electrically connected to each other by means of conductor tracks. The production line has: (a) a first machine for processing a product, the product comprising a 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 (d) a data processing device, the data processing device being communicatively coupled to the first machine, the second machine and the third machine and being arranged to perform the above-mentioned method for adjusting process parameters.

[0099] According to another aspect of the invention, a computer program for adjusting process parameters for a process of producing electronic components by means of automated production on a production line is described. The computer program, when executed by a data processing device of the production line, is arranged to perform the above-described method for adjusting process parameters.

[0100] According to this document, the nomenclature of such computer programs is equivalent to the terms program element, computer program product and / or computer-readable medium containing instructions for controlling a computer system in order to control the working method or method of the system in an appropriate manner so as to achieve the effects associated with the method according to the invention.

[0101] The computer program may be implemented as a computer-readable instruction code in any suitable programming language. The computer program may be stored on a computer-readable storage device (CD-ROM, DVD, Blu-ray disc, removable drive, volatile or non-volatile memory, built-in memory / processor, etc.). The instruction code may program a computer or other programmable device to perform the desired functions. In addition, a network (such as the Internet) may provide the computer program, from which a user may download the computer program when desired.

[0102] The invention can be implemented by means of a computer program (ie software), and by means of one or more specific electronic circuits (ie hardware or any other hybrid form), ie by means of software elements and hardware elements.

[0103] Further advantages and features of the invention emerge from the following exemplary description of currently preferred embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0104] Figure 1 A production line for electronic components is shown with higher-level data processing equipment for correlating process data and inspection data coming from various processing or inspection equipment of the production line.

[0105] Figure 2The correlation of process data and test data is shown, in particular for the subsequent optimization of process parameters of a processing machine designed as a solder paste printer.

[0106] Figure 3 It shows that the correlation data set is implemented as a correlation table for two different types of printed circuit boards.

[0107] Figure 4 The optimization of process data for assembly is shown using a block diagram.

[0108] Figure 5 The relocation of the position data is shown.

[0109] Description of reference numerals:

[0110] 100 production lines

[0111] 102 Input Station

[0112] 104 Apparatus for marking printed circuit boards using laser radiation

[0113] 110 Solder paste printer

[0114] 120 Solder Paste Inspection Machine / SPI Machine

[0115] 130 Assembly Machine

[0116] 140 Assembly inspection machine / AOI machine

[0117] 150 Soldering Machine / Reflow Oven

[0118] 152 PCB Buffer

[0119] 160 Welding Inspection Machine / AOI Machine

[0120] 162 Output Station

[0121] T Conveying direction

[0122] μP Data Processing Devices

[0123] DB database

[0124] S1 Obtaining a work plan

[0125] S2 Correlation between positions of different machines

[0126] S3 Get Results

[0127] S4 applies location correlation to machine results

[0128] S5 stores the relevant machine results

[0129] S6 real-time feedback of relevant machine results

[0130] 370a Printed circuit board (first category)

[0131] 370b Printed circuit boards (second category)

[0132] 375 Related Datasets / Related Tables

[0133] 470 Printed Circuit Board

[0134] 481-487 Box

[0135] 570 printed circuit board. DETAILED DESCRIPTION

[0136] It should be noted that in the following detailed description, features or components of different embodiments that are identical or at least functionally identical to corresponding features or components of another embodiment have the same reference numerals, or have reference numerals that are identical to the last two digits of the reference numerals of the corresponding identical or at least functionally identical features or components. To avoid unnecessary repetition, features or components that have already been described based on previously described embodiments will not be described in detail at subsequent points.

[0137] In addition, please note that the embodiments described below represent only a limited selection of possible variations of the embodiments of the present invention. In particular, the features of the various embodiments may be combined in an appropriate manner so that a large number of different embodiments may be considered to be clearly disclosed together with the embodiments explicitly described herein for those skilled in the art.

[0138] Figure 1 A production line 100 for electronic components is shown. The production line has various devices arranged along a conveying path for printed circuit boards. The conveying direction of the conveying path for the printed circuit boards is in the direction Figure 1 Indicated by the arrow marked "T".

[0139] Along the conveying direction T, the production line 100 has in a known manner an input station 102, into which prefabricated but not yet printed circuit boards are fed in. Downstream of the input station 102, there is a device 104 for marking the printed circuit boards using a laser beam.

[0140] Next is the solder paste printer 110 as the first processing machine, which selectively applies solder paste to specific points on the printed circuit board by means of a known screen printing method. These points are usually 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, because the solder paste must be applied to each component connection area in a precise position and in a precise amount. To achieve this, a plurality of process parameters of the solder paste printer 110 must be correctly set. These process parameters include, for example, the speed of the scraper, which is guided along the surface of the so-called printing screen and ensures that the viscous solder paste is transferred to the opening of the printing screen in the correct amount.

[0141] Downstream of the solder paste printer 110 there is a solder paste inspection machine 120, by means of which it can be optically verified whether the solder paste print is of a sufficiently good quality to make further processing of the printed circuit board sensible. The solder paste inspection machine 120 is also referred to as an SPI machine.

[0142] The assembly system then follows in the conveying direction T. According to the exemplary embodiment shown in the figures, the assembly system comprises a total of three assembly machines 130 , by each of which a certain number of (different) components are assembled at component positions defined by the previously applied solder paste bank.

[0143] Downstream of the assembly system, there follows an assembly inspection machine 140, by means of which it is verified whether the assembly of the printed circuit boards performed by the three assembly machines 130 is correct. According to the exemplary embodiment shown here, the assembly inspection machine 140 performs optical inspection of the assembled components in two dimensions (2D) and three dimensions (3D). The assembly inspection machine 140 is a known automatic optical inspection (AOI) machine.

[0144] Downstream of the AOI machine 140 there is a soldering machine 150 which is designed in a known manner as a so-called reflow oven. The viscous solder paste is melted in the reflow oven 150 so that after the solder paste has cooled down a short time ago, the components are in firm electrically conductive contact with the corresponding component connection areas.

[0145] Downstream of the reflow oven 150 there follows another printed circuit board buffer 152 in which a certain number of soldered printed circuit boards can be stored or buffered.

[0146] According to the exemplary embodiment shown in the figure, there follows (downstream) a soldering inspection machine 160, by means of which it is verified whether the soldering process carried out in the reflow oven 150 is successful (in terms of quality). The soldering inspection machine 160 is also known here as an AOI machine.

[0147] Following the AOI machine 160 is an output station 162. The fully processed electronic components may be removed from the output station by an operator.

[0148] In production lines known in the prior art, the process parameters of the individual processing machines (solder paste printer 110, assembly machine 130, reflow oven 150) are usually set based on the inspection data of the inspection machines (solder paste inspection machine 120, assembly inspection machine 140, welding inspection machine 160) directly associated with the corresponding inspection machine or downstream thereof. It is unknown to optimize the process parameters in conjunction with process technology aspects, and these process parameters are certainly not completely independent of each other in terms of the final quality of the manufactured electronic components.

[0149] In the production line 100 described here, a higher-level data processing device μP is provided, which in particular collects the inspection data from the different inspection machines 120, 140 and 160 and jointly evaluates them. In addition, current process data from the processing machines 110, 130 and 150, in particular from the solder paste inspection machine 120, are collected and jointly evaluated using the inspection data according to the highest possible quality of the final product (i.e., the electronic components produced). For this purpose, methods or algorithms of artificial intelligence are preferably used. This evaluation then results in optimized process parameters, which can be stored in a database DB.

[0150] However, the joint evaluation of the data sets provided by the various machines is not so simple. In terms of content, the various data sets relate to all (relevant) positions on the corresponding printed circuit board. However, each machine usually uses its own data format for this purpose. These data formats differ in particular in the different process-specific position descriptions of different positions and components on the printed circuit board. Therefore, it is necessary to reposition the corresponding position information of the various data sets and geometrically superimpose them so that they "coincide" as much as possible. The corresponding method for relating the various data sets is explained in further detail below, which method is performed in the data processing device μP and represents a central aspect of the invention described in this document.

[0151] The essence of the invention described herein is to correlate the functions of the various machines of the production line 100 with one another. This is referred to below as a so-called "Inter-Device Data Correlation Function" (IDDCF). With such an IDDCF, it is possible to optimize the process sequence of the entire production line 100. For this purpose, measurement data from the various inspection machines and process data from at least one of the various processing machines are collected and correlation data are determined therefrom so that all machines figuratively "speak the same language". The correlation data contained in the correlation data sets can then be used to (jointly) optimize the entire manufacturing process by setting optimized process parameters for the various processing machines.

[0152] In other words, the data processing device μP is connected to at least some of the machines and retrieves detailed working data from them, which working data is also referred to as "working recipes" in this article. These working recipes contain instructions or information about how the machines should complete their work. To clarify: this applies not only to processing machines, but also to testing machines.

[0153] The working scheme for the solder paste printer 110 includes, for example (but not limited to), the size and format of the relevant printed circuit board, the location on the printed circuit board where the solder paste will be applied, process parameters such as the speed of the scraper mentioned above, the cleaning cycle of the scraper, etc.

[0154] The working scheme for the solder paste inspection machine 120 includes, for example, a layout description of the locations of the expected solder paste piles and how these piles should look in 2D and 3D of the solder paste inspection machine 120. In addition, the layout description may also include information about the expected or desired solder paste volume and optionally its allowed tolerances.

[0155] The working scheme for the assembly machine 130 includes, for example, corresponding assembly positions and process information such as the vacuum value of negative pressure caused by adsorption of the clamping element, the pressure or force when assembling the element on the printed circuit board, the travel speed of the assembly head, etc.

[0156] The work plans for the AOI machines 140 and 160 include, for example, information about the (selected) solder connections to be inspected (upstream and downstream of the reflow oven 150), target positions and target heights of mounted or soldered components, and the like.

[0157] The above exemplary working schemes are correlated to each other using the above IDDCF. In particular, the position information of all components and their electrical connections are correctly position analyzed (ie, with the correct geometrical overlay of the product features of the printed circuit board).

[0158] It should be noted that for the IDDCF described here, the removal of defective (intermediate) products from the production process at so-called gates is by no means excluded. However, within the framework of an optimized process flow, the internal thresholds of the inspection machine for classifying the (intermediate) products as defective can be adjusted in order to reduce the probability of incorrect error messages. In addition, as already described above, based on the measurement results of the inspection machine, the process parameters of the various processing machines can be adjusted, thereby improving the quality of the entire production. In particular, by suitable adjustment of the internal thresholds, the number of false error messages can be reduced, which advantageously achieves an overall quality improvement of the production process and a reduction in the cycle time.

[0159] Using the known PCB tracking within the production line and using the above mentioned IDDCF, in particular the following correlations are achieved:

[0160] (A) Which printed circuit board identification number of the AOI machine corresponds to which printed circuit board identification number of the assembly machine;

[0161] (B) Which component detected by the AOI machine corresponds to which component assembled by the assembly machine;

[0162] (C) Which connection or pin identification number of the AOI machine corresponds to which component connection area identification number used by the SPI machine.

[0163] In addition, the assembly positions used by the assembly machines 130 can be correlated with component receiving positions, which can be obtained from the process data management of the corresponding assembly machines 130. These position correlations or correlations with identification numbers should be re-determined at any time when at least one working plan of at least one machine involved in the production line 100 is changed.

[0164] Once available, these correlations can be used to optimize the subsequent process flow of printed circuit boards.

[0165] Figure 2 The correlation of process data and test data is shown, in particular for the subsequent optimization of process parameters of a processing machine designed as a solder paste printer.

[0166] According to the exemplary embodiment shown in the figure, the process starts with work plans for solder paste inspection, for assembly inspection and for the assembly process, which are collected in step S1 by the assembly machine 130. The work plans contain, among other things, detailed information about the layout of the corresponding printed circuit board, the components to be assembled thereon (position and size) and their component connection contacts.

[0167] In the next step S2, the correlation of the above-mentioned position data is then carried out with the help of IDDCF. The component positions and component connection contact positions between the working schemes used by each machine are correlated to each other, so that all component connection contacts contained in each working scheme are correctly associated with each other. The result of this correlation is a correlation table, which correctly associates component connection contacts and component connection areas (pads) with each other for all machines involved. This association is not only based on the position on the printed circuit board of the corresponding type, but also based on the identification number of the component, the identification number of the component connection area and / or the identification number of the component connection contact. Therefore, sometimes the different component names and identification names of each machine involved in the production process can be correctly associated with its working scheme. In particular, the correlation table can be used to make (a) the working scheme from the solder paste detection machine and at least one AOI inspection machine correlate with the working scheme of (b) the solder paste printing machine and the assembly machine, and these working schemes contain current process parameters.

[0168] Then, in the next step S3, the results from each inspection machine are waited for. These results are all related to a specific printed circuit board.

[0169] Once the results of the individual testing machines are available, the previously determined position assignments are used in the next step S4 in order to correlate these results with one another. The correlation table determined in step S2 is used for this purpose.

[0170] In the next step S5, the relevant results, the (current) working plan and the relevant data are stored in a database DB. The database DB is a database that is stored by the processor ( Figure 2 The "big data" analysis can be used, for example, to find the basic causes (so-called "root causes") of defects in electronic components at the end of a production line.

[0171] In addition, such “big data” analysis can be used to adjust the inspection machine’s thresholds for sorting out defective intermediate products, thereby reducing the probability of false error messages.

[0172] In step S6, the relevant results are transmitted to the corresponding inspection machine or processing machine. In the case of a solder paste inspection machine, locations on the printed circuit board that are particularly relevant for the application of solder paste can then be identified with regard to possible defects. In the case of a solder paste printer, at least some process parameters can then be set to reduce the probability of solder paste application defects, thereby automatically reducing the scrap rate of printed circuit boards printed with solder paste, even before assembling components.

[0173] Figure 3 It is shown that the correlation data set is 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 the working scheme of the assembly machine, the first printed circuit board 370a is called panel 1, and the second printed circuit board 370b is called panel 2. In the working scheme of the AOI machine, the first printed circuit board 370a is called panel A, and the second printed circuit board 370b is called panel B. According to the exemplary embodiment shown in the figure, the association is stored in the first two rows of the correlation table 375. In addition, other correlations about different types of components are stored in the correlation table 375. Unique identification numbers are used for this purpose. According to the exemplary embodiment shown here, these are ID DR100, R101, ..., R100_a, R101_a, ..., etc. for resistors, ID C100, C101, ..., C100_b, C101_c for capacitors, ID D100, R101, D100_c, D101_c for diodes and ID Q2 and Q2_x for the ball grid array.

[0174] Figure 4 The optimization of the process data for assembly is shown using a block diagram. As has already been explained several times above, the optimization is based on the correct positional superposition of the descriptions of the same printed circuit board in different machines or different work plans. Figure 4 In the upper left corner, the layout of the printed circuit board 470 is clearly visible in the coordinate system of the working plan or assembly machine. In the upper right corner, the same layout of the printed circuit board 470 is clearly visible in the coordinate system of the working plan or AOI machine.

[0175] As can be seen from the block diagram shown below the two printed circuit board layouts, optimizing the process data for assembly requires the correct superposition of the position descriptions of the two layouts in position, that is, the description 482 of the assembly position and the description 483 of the component position in the coordinate system or the corresponding work plan of the AOI machine. Here, the position description 482 for assembly depends on the work plan for assembly (assembly work plan 481). According to the assembly work plan 481, the description 482 and the description 483, a data set 484 is created as a correlation table, which associates the component positions in the various coordinate systems or work plans with each other. Based on (i) a data set 485 containing assembly process data and (ii) a correlation table 484 for component positions, another correlation table 486 is generated, which describes the correlation between (i) the assembly position and (ii) the component pick-up position of the corresponding component from the component feeder. Based on this other correlation table 486, the optimized process data 487 is then determined for the component pick-up and component assembly associated with the lowest possible rate of incorrectly assembled components. As already described above, incorrectly assembled components will be identified as component defects by the AOI machine (hopefully correctly).

[0176] As already explained above, different working schemes from different machines cannot be simply correlated using reference names (such as printed circuit board IDs), because the corresponding descriptions for different machines are different. At least for now there is no agreement (between manufacturers of different machines) to use the same reference names for different machines in a production line of electronic components. Even the origins of different coordinate systems may be different. The only reliable data that can be used for correct correlation in position are the distances between the (centers) of the various components. In order to reliably establish such positional correlations, the relative distances between (the center points of) the components and the component connection contacts of the corresponding components can be used. With the correct positional correlation, different layouts can be superimposed so that the overlap between the product feature structures, component connection areas and component connection contacts between the two layouts is as large as possible.

[0177] By way of example, a plurality of center point positions can be considered as a "fingerprint" for a specific product or a specific printed circuit board. This fingerprint must be at least very similar for different data sources (from different machines). That is because, if it were not so, it would not be the same product. According to a preferred embodiment, such a fingerprint is used for two different layout descriptions of a printed circuit board to perform a positionally correct superposition, wherein at least one of the two layout descriptions is shifted so that the total number of distances between two mutually associated positions of component connection contacts and / or component connection areas is minimized. For example, a known so-called "nearest neighbor" algorithm can be used for this purpose.

[0178] Figure 5 Schematically shows the relocation of position data used by different machines for the same printed circuit board 570. The open circles represent component connection contacts used for the AOI machine (see Figure 1 The solid circle represents the component connection area when used for the SPI machine (see Figure 1 120 in the figure) or the center point when used by it.

[0179] It should be noted that the repositioning may also be performed iteratively using multiple cycles. For example, after a first repositioning method fails to provide 100% consistency, a second method for improving the repositioning may be performed.

Claims

1. A method for adjusting process parameters for a process for producing electronic components by means of automated production on a production line (100), the method comprising: A) performing a correlation method for correlating different data sets, said data sets being associated with a single printed circuit board (470) on which an electronic assembly having a plurality of electronic components is built by means of said automated production, said correlation method comprising: 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 comprising: first position information and first feature information related to feature target characteristics of a product feature structure of the printed circuit board (470) at a plurality of positions on the printed circuit board (470); providing a second data set from a second machine, wherein the second data set is associated with the second machine and used to control the operation of the second machine and includes: second location information and second feature information related to the 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); geometrically superimposing the first position information on the second position information; repositioning at least one of the first position information and the second position information so as to reduce the total distance between two mutually associated position information, namely the first position information and the associated second position information, starting from a single position on the printed circuit board (470); and 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 comprising third position information and third feature information related to the feature target characteristic of the product feature structure of the printed circuit board (470) at the plurality of positions on the printed circuit board (470); Wherein the geometric superposition further comprises the geometric superposition of the third position information and the first position information and / or the second position information; And wherein the repositioning also includes repositioning of the third position information, thereby reducing the total sum of the sums of three distances between each of the three interrelated position information of a single point on the printed circuit board (470), that is, the total sum of the sums of: (i) a first distance between the first position information and the associated second position information, (ii) a second distance between the associated second location information and the third location information, the third location information being associated with the first location information and the second location information, and (iii) a third distance between the third position information and the first position information; wherein the first machine is a first processing machine and the first data set comprises a first process data set; wherein the second machine is a first inspection machine and the second data set comprises a first inspection data set; wherein the third machine is a second processing machine and the third data set comprises a second process data set; and The method for adjusting process parameters further comprises: B) determining, by means of the first inspection machine, a first deviation between an actual characteristic and a target characteristic of the product feature structure in a first area of ​​the printed circuit board (470), the first area being associated with a first position on the surface of the printed circuit board (470); C) Creating a first combined data set (375) comprising (i) at least a first portion of the first process data set, the second process data set, and the first inspection data set, wherein the first portion is associated with the first area of ​​the printed circuit board (470), and at least one of the following: (ii) the relocated first position information, the relocated second position information or the relocated third position information; To reduce the first deviation, a first process parameter of the first processing machine and a second process parameter of the second processing machine are adjusted based on the created first combined data set (375) and the determined first deviation.

2. The method of claim 1, wherein the first handler physically changes a product including the printed circuit board (470) and the product feature structure by means of a processing process.

3. The method of claim 2, wherein the first processing machine is a machine selected from the group consisting of: (i) a solder paste printer (110), the solder paste printer being used to apply solder paste to a component connection area of ​​the printed circuit board (470); (ii) an assembly machine (130) for assembling electronic components on the printed circuit board (470); and (iii) a soldering machine (150) for melting the solder paste, the soldering machine being located between the component connection area of ​​the printed circuit board (470) and the electrical connection contact of the component mounted on the printed circuit board (470).

4. The method according to claim 1, wherein the first inspection machine detects a characteristic structure of the product by means of an inspection process.

5. The method of claim 4, wherein the first inspection machine is a machine selected from the group consisting of: (i) a solder paste inspection machine (120), the solder paste inspection machine being used to inspect the applied solder paste; (ii) an assembly inspection machine (140) for inspecting assembled components; and (iii) A welding inspection machine (160) for inspecting welded components.

6. The method of claim 1, wherein the second handler further physically changes the product including the printed circuit board (470) and the product feature structure by means of a processing process.

7. The method according to claim 6, further comprising: providing a fourth data set from a fourth machine, wherein the fourth data set is associated with the fourth machine and is used to control operation of the fourth machine, and comprising: fourth position information and fourth feature information related to the feature target characteristic of the product feature structure of the printed circuit board (470) at the plurality of positions on the printed circuit board (470); wherein the geometric superposition further comprises a geometric superposition of the fourth position information and at least one of the first position information, the second position information and the third position information; and wherein the repositioning further comprises repositioning the fourth position information so as to reduce the total sum of the six distances between each of the four interrelated position information of a single point on the printed circuit board (470), That is, the total of the sums of: (i) the first distance, (ii) the second distance, (iii) the third distance, (iv) a fourth distance between the fourth position information and the third position information, (v) a fifth distance between the fourth position information and the second position information, and (vi) a sixth distance between the fourth position information and the first position information.

8. The method according to claim 7, wherein The first inspection machine detects the product characteristic structure at a first inspection point along the production line (100); The second processing machine is arranged downstream of the first processing machine relative to the conveying direction (T) of the production line (100); and The fourth machine is a second inspection machine that detects the product feature structure at a second inspection point along the production line (100).

9. The method of claim 1, wherein the first area of ​​the printed circuit board (470) is an area of ​​the printed circuit board (470) in which the first deviation between the actual characteristic of the product feature structure and the target characteristic is greater than a second deviation between the actual characteristic of the product feature structure and the target characteristic in a second area of ​​the printed circuit board (470), the second area being associated with a second location on the surface of the printed circuit board (470), wherein The second position is different from the first position.

10. The method according to claim 9, further comprising: Determining, by means of the first inspection machine, a second deviation between an actual characteristic and a target characteristic of the product feature structure in a second area of ​​the printed circuit board (470); Create a second combined dataset based on (i) in each case the first process data set, the second process data set and at least a second portion of the first inspection data set, wherein the second portion is associated with the second area of ​​the printed circuit board (470), and further based on (ii) at least one of the relocated first position information, the relocated second position information, and the relocated third position information; as well as At least one of the first process parameter of the first processing machine and the second process parameter of the second processing machine is adjusted further based on the created second combined data set and the determined second deviation.

11. The method of claim 1, wherein adjusting at least one of the first process parameter of the first processing machine and the second process parameter of the second processing machine is performed iteratively with the aid of at least one learning algorithm.

12. A production line (100) for the automated production of electronic components, the production line having a printed circuit board (470) and a plurality of electronic components, the electronic components being attached to the printed circuit board (470) and being electrically connected to each other by means of conductor tracks, the production line (100) having a first machine for processing a product, the product comprising the printed circuit board and a product feature structure; a second machine for inspecting the characteristic structure of the product; a third machine for processing said product; as well as A data processing device is communicatively coupled to the first machine, the second machine and the third machine and is arranged to perform the method according to claim 1.

13. A computer-readable storage medium having stored thereon a computer program for adjusting process parameters for a process for producing electronic components by means of automated production on a production line (100), wherein the computer program, when executed by a data processing device of the production line (100), is arranged to perform the method according to claim 1.

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