KR20220143938A - Correlation of data between different machines on a production line for electronic components - Google Patents

Abstract

The data set associated with the common PCB includes: (a) first data including first location information and first feature information for feature target properties of a product-feature structure of the printed circuit board at a plurality of locations on the printed circuit board providing the set from the first machine; (b) providing from the second machine a second data set comprising second positional information and second characteristic information for characteristic target characteristics of a product-feature structure of the printed circuit board at a plurality of positions on the printed circuit board to do; (c) geometrically superimposing the first location information on the second location information; and (d) the first location information and/or the second location information such that the sum of the distances between the two correlated pieces of location information, ie, the first location information and the associated second location information, from one and the same location on the printed circuit board is reduced. It is correlated by the step of rearranging the location information.

Description

Correlation of data between different machines on a production line for electronic components

The present invention relates in particular to a technology for the production of electronic assemblies in a production line having a plurality of machines, such as a placement machine for placing an electronic component on a printed circuit board and an inspection machine for determining the quality of a previous process step. It's about the field. The present invention relates in particular to methods of analyzing process data of such production lines and methods of optimizing manufacturing processes for electronic assemblies.

An electronic assembly generally has 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. Such electronic assemblies are manufactured on a production line having a plurality of machines interconnected via a conveyor belt for manufacturing or processing and a machine for (optical) inspection of intermediate products. These machines typically include:

(a) a solder paste printing machine for selectively applying solder paste to component connection areas or connection areas formed on the surface of the associated printed circuit board;

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

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

(d) placement inspection machines for verifying the correct placement of printed circuit boards;

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

(f) Soldering inspection machines to verify correct soldering of components.

It is not necessary to use all three inspection machines mentioned above for quality determination, which can be somewhat degraded. All you need is an inspection machine, but not necessarily the soldering inspection machine mentioned earlier.

In production lines currently known for electronic assembly, at least one inspection machine is used to separate defective or poorly handled printed circuit boards from the production process or to direct repairs. This separation occurs at certain points in the production line by means of an appropriate evacuation device, technically referred to in this document as a gate. For cost-benefit reasons, this separation should occur as soon as possible.

Separation can have two different reasons. The first reason may be that the processed printed circuit board, also referred to in this document as the product or intermediate product, is actually defective or (very) poor quality. The second reason may be that the product or intermediate product is completely normal, but the relevant inspection machine incorrectly reports an error. Therefore, in the case of product classification through the inspection machine, it is reasonable to select a threshold for error detection so as to reliably detect defective products on the one hand and minimize the outputting of false errors as much as possible on the other hand.

Separated products or separated printed circuit boards can be manually inspected by skilled operators 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. Also, the above-mentioned thresholds for error detection can be adapted.

However, manual optimization of these process parameters and proper adjustment of thresholds for error detection is actually very difficult. These two factors depend, inter alia, on the ability and experience of the operator to optimize process parameters and adjust these thresholds.

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

This object is achieved by the subject matter of the independent claim.

Advantageous embodiments of the invention are described in the dependent claims.

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

providing the first data set comprising first positional information and first characteristic information for characteristic target characteristics of a product-feature structure of the printed circuit board at a plurality of positions on the printed circuit board; (b) providing a second set of data from a second machine, wherein the second set of data is (b1) associated with the second machine, (b2) controls operation of the second machine, and 2 data sets (b3):

providing the second data set comprising second positional information and second characteristic information for characteristic target characteristics of a product-feature structure of the printed circuit board at a plurality of positions on the printed circuit board; (c) geometrically superimposing the first location information on the second location information; and

(d) the first location information and/or the sum of the distances between the two correlated pieces of location information from one and the same location on the printed circuit board, ie the first location information and the associated second location information, is reduced. and rearranging the second location information.

The described method allows the process data of various machines to be converted into intermediate products or final products (finished assemblies) by appropriate geometrical repositioning of the first coordinate system of the first position information and/or the second coordinate system of the second position information relative to each other. -based on the knowledge that characteristic outcomes can be compared or correlated with each other For illustrative purposes, this relocation represents a basis for comparing or correlating data from different machines. This means that it is possible to examine as well as the influence of process parameters on the processing results of a single machine. Rather, the (combinatorial) effect of a plurality of process parameters associated with different processing machines can be evaluated on characteristic properties or qualities of an intermediate product, in particular a final product. This advantageously enables automatic optimization of the most diverse process parameters in relation to intermediate and final products of the highest quality.

In a common database shared by a plurality of machines and/or inspection machines, databases with mutually correlated data sets, appropriate adjustment of process parameters of processing machines and/or appropriate adjustment of threshold values of inspection machines or devices for (gate) separation can improve the manufacturing process of electronic assemblies in two ways. First, the quality of the produced electronic assembly or final product may be improved. Alternatively or in combination, it is possible to reduce the proportion of defective (final) products that are incorrectly separated in the manufacturing process.

The described relative repositioning of the two (different) coordinate systems is carried out according to the invention to the (one and the same) printed circuit board, as well as products of the printed circuit board which are detected and processed or processed by various machines in the same and different coordinate systems - The feature structures overlap as much as possible in the two coordinate systems after relocation. To explain, this means that the (two) geometrical descriptions of the product-specific printed circuit board structures are adapted to each other by the described rearrangement so that an exact geometrical correlation of the two data sets can be performed.

In this document, the term "correlation" may be understood to mean any type of geometrical association to coordinates in different coordinate systems, which association means that the same structure of a printed circuit board has two coordinate systems (and two data All sets) are described in the same structure. For example, a specific pad on a printed circuit board that is provided for a specific electrical connection contact of a specific component of an electronic assembly should be described as the same pad in both data sets. It is clear that accurate geometrical rearrangement is paramount.

Correlation of the various data sets may occur in an appropriately programmed data processing device in which the data sets are located at least temporarily. It does not matter whether these data sets have been obtained from each machine on the production line through appropriate data transmission or whether the two data sets have already been stored in the relevant data processing unit and transmitted to the relevant machine.

The correlation, that is, the result of the correlation, may be recorded, for example, in the form of a table also called a correlation table. Such correlation tables represent a particularly simple but effective way to describe or record associations between different content or elements of different data sets. When described herein with product-feature information of a printed circuit board, the component connection contact of the component and the component connection area of the printed circuit board to which the component is to be mounted can be associated with each other, for example as detailed below.

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

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

(b) In case of arrangement downstream of the placement machine and upstream of the soldering machine, the results of the placement process can be inspected. Such an inspection machine is referred to herein as a "placement inspection machine".

(c) In the case of arranging downstream of the soldering machine, the (reflow) soldering result of each component connection area or pad placed on the printed circuit board can be inspected. Such an inspection machine that generally inspects the final product on a production line is referred to in this document as a "placement inspection machine".

In this document, the term “location information” may be understood to mean any location specific indication of a point or location on a printed circuit board. Positional information is the location of a component connection area or pad on the surface of a printed circuit board that makes electrical contact with the connection contacts of the component, particularly when the component is mounted on the printed circuit board. Positional information for one and the same printed circuit board position will of course have different values in different coordinate systems (on different machines).

In this document, the term “characteristic information” refers to 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 a specific (small) area of a printed circuit board. can be understood to mean The spatial physical characteristic information may be geometrical two-dimensional information, such as an indication of the position, size and/or shape of the 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 particular pad. The optical characteristic information can be, for example, information about the color and/or reflectivity of the pad, which can be, for example, an indication of possible corrosion of the pad or a cold solder joint. The electrical characteristic information may indicate, for example, the electrical conductivity of a conductor track on the surface of a printed circuit board.

In this document, the term “product-characteristic structure” may be understood to mean any structural or spatial physical characteristic characteristic of a particular 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) product-feature structure(s). Such characteristics may be, for example, the location, size and/or shape of the pad.

In this document, the term "repositioning" can be any type of geometric change of a coordinate system used in the description of the relevant data set. In particular, the rearrangement may be displacement, rotation and/or distortion of at least one of the two coordinate systems respectively associated with one of the two data sets in some applications.

In the "relocation" described, the two data sets based on the coordinate system are geometrically changed so that the position information of the two data sets for the selected position on the printed circuit board in question is closer to each other than before the relocation. Preferably, the location information is as close to each other as possible or even overlaps. To illustrate, the two coordinate systems are adapted to each other through appropriate coordinate transformations. As noted above, this coordinate transformation may include displacement, rotation and/or distortion.

The described "relocation" can be implemented through known mathematical and geometric calculations. As with any other calculation or algorithm, it can occur in any data processing unit on an associated production line for an electronic assembly. This data processing device may be associated with a particular machine. Alternatively or in combination, it may also be a central or higher-level data processing unit communicatively coupled, directly or indirectly, to an individual machine.

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

At this point, it should be emphasized again, in other words, that the two data sets described control the machines involved. This means that the actual operation of the machine in question depends on the data set associated with it. Thus, according to the present invention, the data set not only contains information about the product-feature structure of the relevant printed circuit board, but rather, the data set also contains instructions or information on 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 processing machines, suitable controllers ensure processing of the relevant printed circuit boards. In the case of a placement machine, for example, this is the precise positioning of a part on a printed circuit board. For inspection machines, the relevant data set is not or is not exclusive to the measurement data set with the results of a previously performed inspection. Rather, the relevant data set (also) represents the inspection data set that controls the operation of the relevant inspection machine. Thus, a data set for an inspection machine or an inspection data set is a work recipe (typically comprising a plurality of individual work instructions) for an associated inspection machine just as a process data set is a work recipe for a processing machine.

In this context, it is obvious that the operation of the inspection machine must also be controlled. This is because, for reasons of efficiency, it cannot be justified, for example, to inspect all areas of the (intermediate) product, ie at least partially processed printed circuit boards, with one and the same accuracy. This significantly increases the time it takes to actually perform the inspection. For example, regions of the object to be inspected that are particularly relevant may be inspected with particular precision, and different regions may be inspected with poor accuracy or not at all.

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

According to another exemplary embodiment of the present invention, a first processing machine comprises: (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 said solder paste located between component connection areas of said printed circuit board and electrical connection contacts of components placed on said printed circuit board. to be.

The described processing machine selection has the advantage that all common processing machines of the electronic component production line are covered. In principle, the described method can be used for data correlation between all types of processing machines on a production line. This applies to any machine that works with location-specific information or provides location-specific information as part of its measurement.

According to another exemplary embodiment of the present invention, the second machine is a first inspection machine that detects a product-feature structure by an inspection process. The first inspection machine, or more precisely, a data processing device 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, from Determine quality values for manufactured and detected product-feature structures. This quality value can be used to suitably adapt a process parameter of the processing machine and/or at least one threshold value of the first or further inspection machine.

The first inspection machine preferably detects a single product-feature structure as well as a plurality of product-feature structures. The data processing device is then configured to compare more than one or at least a portion of the detected actual product-feature structure to a corresponding predetermined target product-feature structure, and a plurality of quality values for the product-feature structure produced and detected therefrom; /or determine a higher-level quality value.

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

As detailed below, the parameters described above may be the location and height of the placed or soldered component, which of course also relates to 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 electronic assembly produced. Otherwise, it is not necessary 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 that the inspection can be performed quickly and with high accuracy.

According to another exemplary embodiment of the present invention, the first inspection machine comprises (i) a solder paste inspection machine for detecting applied solder paste; (ii) a placement inspection machine for detecting placed parts; and (iii) a soldering inspection machine for detecting soldered parts.

Detection of solder paste may include, for example, detection of the location, volume and/or shape of the solder paste application. All these observables have a natural (strong) effect on the contact quality of the part that still has to be placed.

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

Detection of a soldered component may also include the type of component being soldered, its final position in the plane of the printed circuit board, and/or its height position above the surface of the printed circuit board (after soldering, the component is temporarily melted and then solidified with a certain volume of solder It settles on the paste). In particular, it can be detected whether the component connection contact (of the component) has been accurately soldered to the corresponding component connection area (of the printed circuit board) and is in electrical contact correctly. It is clear that all these observables have a significant impact on the quality of the final final product, namely the electronic assembly produced. Therefore, detection by the described soldering inspection machine can be an important part of the final quality analysis of the finished (final) product. Optionally, the final quality analysis in conjunction with the at least one non-final quality analysis may be used to optimize process parameters of the processing machine and/or threshold values of the first and optionally further inspection machines through an appropriate learning process.

It should be noted that in an embodiment 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 advantageously be merged by the described method. This can be done in particular for the purpose of optimizing process data with the aid of measurement data. This may advantageously enable particularly accurate analysis of automated production.

The described selection of inspection machines has the advantage that all common inspection machines of the electronic component production line are included. In principle, the described method can thus 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 (al) associated with the third machine, (a2 ) control the operation of the third machine, and (a3) the third data set comprises:

providing the third data set comprising third positional information and third characteristic information for characteristic target characteristics of a product-feature structure of the printed circuit board at a plurality of positions on the printed circuit board including as

The geometric overlapping step is

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

The relocation step

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

of one and the same point on the 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) a sum of a third distance between the third location information and the first location information is reduced;

It further includes rearrangement of the third location information.

The described correlation between the three (specific machine's) data sets indicates that the production process of the electronic assembly is jointly analyzed on two as well as three different machines (processing machine and/or inspection machine) and the results of the analysis are determined by the process of the processing machine. It has the advantage that it is used for improved adaptation of parameters and/or threshold values of the first and optionally further inspection machines.

Depending on the particular application, the third machine can be a processing machine or an inspection machine, in principle all types of processing machines described above are possible. For the processing machine, the third machine should be one type of machine so that the production line does not have two solder paste printing machines and two soldering machines. However, a production line may contain more than one placement machine. For inspection machines, the type of inspection machine is the same.

According to another exemplary embodiment of the present invention, the third machine is a second processing machine that makes 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 product-feature structures. As already described above, the product-feature structure may be an electronic component placed or placed on a printed circuit board, for example by means of a placement machine. The product-feature structure may relate to a pre-soldered state or a post-soldered state.

It should be noted that the above-described second machine embodied as the first inspection machine may be arranged between the two processing machines in relation to the conveying direction of the production line. In this case, the first inspection machine detects the processing by the first processing machine, but not the 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 further processing machines are arranged downstream of the first inspection machine. This means that the first inspection machine inspects the final product on the production line. Inspection of the final product and proper feedback of the inspection results to the two processing machines have the advantage that the processing 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) control the operation of the fourth machine, and (a3) the fourth data set comprises:

providing the fourth data set comprising fourth positional information and fourth characteristic information for characteristic target characteristics of a product-feature structure of the printed circuit board at a plurality of positions on the printed circuit board include as

Also, the geometrically 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. Further, the relocating step may be the sum of six distances between each of the four correlated pieces of location information, i.e., (i) the first distance, (ii) the second distance, of one and the same point on the printed circuit board. , (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 and (vi) rearranging the fourth location information so that a sum of 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 on a production line for electronic assembly may be correlated using the described method. This creates a larger database for optimization of the assembly production process.

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

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 conveying direction of the production line; The fourth machine is a second inspection machine that detects the product-feature structure at a second inspection point along the production line.

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

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

Position 1: The first machine or the 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 the second processing machine is a placement machine; and

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

When the second machine or the first inspection machine is a soldering inspection machine, the third processing machine, ie the soldering machine, is located upstream as the fifth machine. Also, in this case, the placement inspection machine embodied as a third inspection machine that directly inspects the assembly result may be optionally located between the second processing machine embodied as the placement machine and the soldering machine.

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

Position 1: The first machine or the 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 the second processing machine is a placement machine;

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

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

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

In many embodiments, the placement machine is a system comprised of two or more placement devices. The placement devices may each have one or more placement heads, which can be moved in a known manner through a portal system and a printing job that picks up a part from a part feeder and is currently positioned in the placement area of the placement device. placed on the circuit board.

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

The described method for adapting the process parameters is based on the knowledge by joint consideration of several possible different processing machines relating to the causes for the undesired (first) deviations of the in fact actual properties from the desired target properties of the product-feature structure(s). On this basis, the process parameters can be particularly well adjusted. This is because these adaptations lead to significantly better results or improved production compared to traditional adaptations that only consider process data sets from a single processing machine. The cause of these undesirable deviations is the process parameters set to the suboptimal of the processing machines involved in production.

In order to be able to carry out this joint consideration with the aid of the combinatorial data set, it is essential to generate the combinatorial data set using data or information relating to the first relevant region of the printed circuit board. Since data sets from different machines (processing machines and/or inspection machines) are usually based on different (formal) descriptions and different coordinate systems, it is necessary to first perform a positionally accurate correlation of the various data sets described above. . This is the only way to ensure that the sets of information contained in the various data sets are positionally accurately correlated with respect to each location or each region of the printed circuit board. Accordingly, the described correlation may be understood as a positionally correct information combination.

To illustrate, with the adaptation of the described process parameters, the above-described method for correlating different data sets ensures accurate positional 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 various data sets is transformed to enable positionally accurate correlation of the information contained in the various data sets.

The combined data sets described herein represent a positionally correct combination of information in the output data sets with respect to each different region of the printed circuit board. To put it bluntly, this means that the information contained in the two process data sets and the inspection data set is positionally accurately merged with respect to the actual printed circuit board.

The relocation and combination of data sets described above flow into the data set are interrelated as follows: In order to positionally accurately merge the characteristic information regarding the characteristic target characteristics of the product-feature structure of the printed circuit board, the information is It is necessary to first transform the different coordinate systems of the relevant data sets so that they can be merged positionally accurately. As already mentioned above, repositioning, which may include rotation and/or distortion, represents such a transformation. This is done so that the total of the specified distance is reduced or minimized.

According to another embodiment of the present invention, a first (spatial) region of the printed circuit board is such that a first deviation between an actual property and a target property of the product-feature structure is related to a second location on the surface of the printed circuit board. An area of the printed circuit board that is greater than a second deviation between the target property and the actual property of the product-feature structure in a second (spatial) area of . Here, the second location or second area is different from the first location or first area.

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

A further advantage of the exclusive or preferential consideration of these critical areas can be seen in the fact that adaptation of process parameters does not require unnecessary processing of 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. Also, this method can perform much faster with the specific computing power available.

The selection of different regions of the printed circuit board may be based on the a priori knowledge and/or experience of the operator. Moreover, the selection may also be based on at least a nearly complete inspection (rarely performed) of the entire area of the printed circuit board, i.e. the degree of deviation relative to other locations or areas of the printed circuit board is determined.

According to another exemplary embodiment of the present invention, the method comprises (a) between an actual characteristic and a target characteristic of the product-feature structure in a second (spatial) region of the printed circuit board, by the first inspection machine. determining a second deviation of ; (b) in each case (bl) at least a second portion of a first process data set, a second portion of a second process data set, and a second portion of a first inspection data set, wherein the second portion comprises said based on said at least second portion, associated with a second region of the printed circuit board, and in addition to (b2) relocated first location information and/or relocated second location information and/or relocated third location information generating a second combined data set based on the; and (c) adapting first process parameters of the first processing machine and/or second process parameters of the second processing machine further based on the generated second combined data set and the determined second deviation. further comprising steps. Taking into account the deviation(s) of the second area, it is possible to adapt the process parameters even more precisely in relation to the best possible quality of the finished final product.

It should be noted that the process parameter adaptation described herein can also be performed on a production line with more than two processing machines and/or on a production line with more than one inspection machine. To this end, it is only necessary to generate suitable combinatorial data sets, where of course it must always be ensured that the information contained in the various process data sets and inspection data sets must be either positionally precisely merged or positionally precisely combined with each other.

According to another exemplary embodiment of the present invention, the adapting of the first process parameters of the first processing machine and/or the second process parameters of the second processing machine is performed iteratively by the at least one learning algorithm. This has the advantage that process parameters can be improved, for example through artificial intelligence. For this purpose, it makes sense if the described method is carried out for each individual or at least for the production of a large number of assemblies within the framework of the production of a particular type of electronic assembly. As a result, the data processing device on which the necessary learning algorithm is performed 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 final product electronic assembly.

According to another aspect of the present invention, there is provided a production line for the automated production of an electronic assembly, 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. This is described. The described production line comprises (a) a first machine for processing a 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 said product; and a data processing device communicatively coupled 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 to a process for the production of an electronic assembly by automated production on a production line. The computer program is arranged to perform the method described above for adapting the process parameters when executed by the data processing device of the production line.

According to this document, the name of such a computer program is a program element comprising instructions for controlling a computer system to control a method or method of operation of the system in a suitable manner to achieve the effects associated with the method according to the present invention, computer equivalent to the terms program product and/or computer readable medium.

The computer program may be implemented as computer readable instruction code in any suitable programming language. The computer program may be stored on a computer readable memory device (CD-ROM, DVD, Blu-ray Disc, removable drive, volatile or non-volatile memory, internal memory/processor, etc.). The instruction code may program a computer or other programmable device to perform a desired function. In addition, the computer program may be provided on a network, such as the Internet, from which users can download as needed.

The invention can be realized not only by means of a computer program, ie software, but also by one or a plurality of special electronic circuits, ie by hardware or in any other hybrid form, ie by software parts and hardware parts.

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

1 depicts a production line for an electronic assembly with high level data processing devices for correlating inspection data with process data from various processing or inspection devices of the production line.
FIG. 2 shows the correlation of process data and inspection data for subsequent optimization of process parameters of a processing machine embodied in particular as a solder paste printing machine.
3 shows a correlation data set implemented as a correlation table for two different types of printed circuit boards.
Figure 4 shows the optimization of process data for a placement using a block diagram.
5 shows the rearrangement of position data.

In the following detailed description, to a feature or part of a different embodiment that is identical or at least functionally identical to a corresponding feature or part of another embodiment, the last two digits of the reference sign of the corresponding identical or at least functionally identical feature or part are designated by like reference numerals. Or it should be noted that the same reference numbers are provided. In order to avoid unnecessary repetition, features or components already described based on the embodiments described above will not be described in detail at hereinafter points any further.

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

1 shows a production line 100 for an electronic assembly. A production line has various devices arranged along the transport path of a printed circuit board. The transport direction of the printed circuit board transport path is indicated by the arrow marked "T" in FIG. 1 .

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

Next, as a first processing machine, a solder paste printing machine 110 that selectively applies solder paste to specific points on a printed circuit board by a known screen printing method is followed. These points are typically component connection areas or pads on the associated printed circuit board surface. The application of solder paste is not actually a simple process, as the solder paste must be applied in the correct location and in the correct amount for each component connection area. To this end, a plurality of process parameters of the solder paste printing machine 110 must be accurately set. These process parameters include, for example, the speed of the squeegee which is guided along the surface of the so-called printing screen and causes the viscous solder paste to be delivered in the correct amount to the openings of the printing screen.

Downstream of the solder paste printing machine 110 is a solder paste inspection machine 120, which optically verifies that the solder paste printing is of sufficient quality to make sense for further processing of the printed circuit board. Solder paste inspection machine 120 is also referred to as an SPI machine.

The placement system then follows along the traversing direction T. According to the exemplary embodiment shown here, the assembly system includes a total of three placement machines 130 , each with a solder paste depot onto which a certain number of (different) parts have been previously applied. is placed in the position of the part defined by

Downstream of the assembly system, a placement inspection machine 140 validates whether the placement of the printed circuit boards performed by the three placement machines 130 is correct. According to the exemplary embodiment shown herein, the placement inspection machine 140 optically detects placed parts 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 is a soldering machine 150 implemented in a manner known as a so-called reflow oven. After the viscous solder paste is melted in this reflow oven 150 and the solder paste is later cooled, the components are in firm and electrically conductive contact with each component connection area.

Downstream of the reflow oven 150 is another printed circuit board buffer 152 in which a certain number of soldered printed circuit boards may be stored or buffered.

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

The AOI machine 160 is followed by an output station 162 . The fully processed electronic assembly may be removed therefrom by an operator.

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

The production line 100 described herein is provided, inter alia, with a higher level data processing unit (μP) that collects inspection data from various inspection machines 120 , 140 , 160 and jointly evaluates them. In addition, current process data from processing machines 110 , 130 , 150 , in particular solder paste inspection machine 120 , are collected and evaluated along with inspection data regarding the highest possible quality of the final product, ie the electronic assembly produced. For this, it is preferable to use an artificial intelligence method or algorithm. This evaluation leads to optimized process parameters that can be stored in a database (DB).

However, joint evaluation of data sets provided by various machines is not so straightforward. In terms of content, the various data sets relate to every (relevant) location on each printed circuit board. However, each system typically uses its own data format for this purpose. These data formats are different, particularly in the different locations descriptions for different locations on the printed circuit board and different locations for each component on the printed circuit board. Therefore, it is necessary to rearrange the corresponding position information of the various data sets and to overlap them geometrically to "match" them as much as possible. Corresponding methods for correlating the various data sets performed in a data processing unit (μP) and representing the central aspect of the invention described in this document are described in more detail below.

The essence of the invention described in this document is to correlate the functions of the various machines of the production line 100 with each other. This is hereinafter referred to as the so-called "inter-device data correlation function" (IDDCF). Using such an IDDCF, the process sequence of the entire production line 100 can be optimized. To this end, measurement data of the various inspection machines and process data of at least one of the various processing machines are collected and the correlation data is determined such that all machines figuratively "speak the same language". The correlation data contained in the correlation data set can be used to optimize the entire manufacturing process (collectively) by setting optimized process parameters for various processing machines.

In other words, the data processing unit (μP) connects at least some of the machines and retrieves detailed job data, also referred to in this document as “job recipes”. These work recipes contain instructions or information on how the machine involved will do the work. For the sake of clarity: This applies to inspection machines as well as processing machines.

The working recipe for the solder paste printing machine 110 may include (without limitation) the size and type of the relevant printed circuit board, the location on the printed circuit board to apply the solder paste, the speed of the squeegee mentioned above, the cleaning cycle of the squeegee, etc. Includes process parameters.

The working recipe for the solder paste inspection machine 120 includes, for example, a layout description of where solder paste reservoirs are expected and how these reservoirs should look in 2D and 3D with respect to the solder paste inspection machine 120 . In addition, the layout description may also include information about expected or desired amounts of solder paste and optionally tolerances.

The working recipe for the placement machine 130 may include, 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 placement head It includes process information such as the movement speed of

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

The exemplary working recipes described above are correlated with each other using the IDDCF described above. In particular, the location information of all parts and their electrical connections are analyzed with location accuracy. That is, it is analyzed through the precise geometric overlap of the product-feature structure of the printed circuit board.

It should be noted that with the IDDCF described here, the removal of defective (intermediate) products from the production process at the so-called gate is by no means excluded. However, within the framework of an optimized process flow it is possible to adapt the inspection machine's internal thresholds to classify (intermediate) products as defective so as to reduce the likelihood of false error messages. In addition, as already described above, based on the measurement results of the inspection machine, process parameters for various processing machines can be applied to improve the quality of the overall production. This advantageously results in an overall qualitatively improved production process and reduced cycle times, especially since the number of false error messages can be reduced by appropriate adaptation of the internal threshold.

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

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

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

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

Further, the placement position used by the placement machine 130 may be correlated with the part receiving position, which may be obtained from process data management of each placement machine 130 . The correlation to the location correlation or identification number may be re-determined whenever at least one work recipe for at least one machine related to the production line 100 is changed.

When these correlations become available, they can be used to optimize the process flow of subsequent printed circuit boards.

FIG. 2 shows the correlation of process data and inspection data for subsequent optimization of process parameters of a processing machine embodied in particular as a solder paste printing machine.

According to the exemplary embodiment shown herein, the process begins with a solder paste inspection, a placement inspection, and a working recipe for the placement process, which are collected by the placement machine 130 in step SI. The working recipe specifically contains detailed information about the layout of each printed circuit board, the parts (position and size) that will be placed on it, and the contacts that connect those parts.

In the next step S2, the above-mentioned correlation of position data takes place with the aid of IDDCF. The position of the part connection contact and the part position among the work recipes used by the various machines are correlated with each other so that all the part connection contacts included in the various work recipes are correctly associated with each other. The result of this correlation is a correlation table that accurately correlates the part connection contact and the part connection area (pad) to each other for all machines involved. This association is based not only on the location on each type of printed circuit board, but also on the identification number of the part, the identification number of the part connection area and/or the identification number of the part connection contact. As a result, the identification names of various machines involved in the production process and other names of parts and work recipes can sometimes be accurately associated. In particular, this correlation table may be used to correlate (a) a working recipe of at least one AOI inspection machine and a solder paste inspection machine and (b) a working recipe of a solder paste printing machine and a placement machine, wherein the working recipe includes: Current process parameters are included.

In the next step S3, the results of various inspection machines are awaited. All of these results are related to a specific printed circuit board.

As soon as 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 result, the (current) job recipe and the correlation data are stored in the database (DB). The database DB is the basis for the so-called "big data" analysis performed by a processor not shown in FIG. 2, and allows the "big data" analysis results to be displayed to the operator through appropriate visualization. For example, “big data” analysis can be used to find the root cause (the so-called “root cause”) of a defect in an electronic assembly at the end of a production line.

This “big data” analysis can also be used to adapt the thresholds of inspection machines to isolate defective intermediate products so that the likelihood of false error messages is reduced.

In step S6, the correlation result is transmitted to each inspection machine or processing machine. In the case of a solder paste inspection machine, the location of a printed circuit board, particularly in relation to solder paste application, can be identified with respect to possible defects. In the case of a solder paste printing machine, at least some process parameters can be set to reduce the possibility of defective application of the solder paste, so that the defect rate of a printed circuit board printed with the solder paste can be automatically reduced even before the parts are placed.

3 shows 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 the working recipe for the 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 the working recipe for the 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 shown here, this association is stored in the first two lines of the correlation table 375 . Further correlations for different types of parts are stored in the correlation table 375 .

A unique identification number is used for this purpose. According to the exemplary embodiment shown here, they are

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

IDs for capacitors C100, 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.

Figure 4 shows the optimization of process data for a placement using a block diagram. As already explained several times above, optimization is based on positionally accurately superimposing descriptions of one and the same printed circuit board by different machines or different working 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 working recipe or placement machine. In the upper right, the same layout of the printed circuit board 470 is clearly visualized in the working recipe or coordinate system of the AOI machine.

As can be seen in the block diagram shown below the two printed circuit board layouts, the optimization of the process data for placement involves the location description of the two layouts, namely the description of the placement location (482) and the coordinate system or of each AOI machine. Requires positionally accurate superimposition of descriptions 483 of part locations in working recipes. Here, the location description 482 for the placement depends on the job recipe for the placement (placement job recipe 481 ). A data set 484 from placement work recipe 481 , description 482 , and description 483 is generated as a correlation table correlating part positions in various coordinate systems or work recipes with each other. Based on (i) a data set 485 containing process data for the assembly, and (ii) a correlation table 484 for part positions, (i) an additional correlation table with correlations between placement positions (486) is created and (ii) the part pickup location of each part from the part feeder is described. From the additional correlation table 486, optimized process data 487 is then determined for part pickup and part placement with respect to the lowest possible percentage of incorrectly placed parts. Misplaced parts are recognized (to be precise) as part defects in the AOI machine, as already described above.

As already explained above, it is not possible to simply correlate different working recipes of different machines using reference designations such as printed circuit board IDs because the corresponding descriptions for different machines are different. At least for now, there has been no agreement (between different machine manufacturers) to use the same reference designation for different machines on a production line for electronic assembly. The origins of different coordinate systems may also be different. The only reliable data that can be used for positionally accurate correlation is the distance between the various parts (centers). In order to reliably establish this positional correlation, the relative distance between the parts (center point) and the part connecting contacts of each part can be used. Through accurate positional correlation, different layouts can be superimposed so that the product-feature structure between the two layouts, the overlap between the part connection area and the part connection contact point are as large as possible.

To illustrate, the plurality of center point locations may be viewed as a “fingerprint” for a particular product or particular printed circuit board. These fingerprints should be at least very similar for different data sources (on different machines). This is because otherwise it is not the same product. According to a preferred embodiment, positionally correct superposition is performed using these fingerprints for two different layout descriptions of the printed circuit board, wherein at least one of the two layout descriptions comprises two interrelated component connection contacts and/or components. Displaced so that the total distance between the connection areas is minimized. For this purpose, for example, the known so-called "nearest neighbor" algorithm can be used.

5 exemplarily shows the relocation of position data used by different machines for one and the same printed circuit board 570 . The open circle indicates the center point of the part connecting contact used in or by the AOI machine (reference numeral 140 in FIG. 1 ). The solid circle indicates the center point of the part connection area used for or by the SPI machine (see reference number 120 in FIG. 1 ).

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

100 production lines
102 input station
104 Apparatus 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 feed direction
μP data processing unit
DB database
51 Job Recipe Acquisition
52 Positional correlation between different machines
53 Get results
54 Applying 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 Datasets/Correlation Tables
470 Printed Circuit Board
481-487 blocks
570 Printed Circuit Board

Claims (15)

A method of correlating different data sets associated with one and the same printed circuit board (470) on which an electronic assembly having a plurality of electronic components is built by automated production in a production line (100), the method comprising:
providing a first data set from a first machine (110), wherein the first data set is associated with the first machine (110), controls operation of the first machine (110), and 1 data set is:
the first data set comprising first positional information and first characteristic information for characteristic 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;
providing a second data set from a second machine (160), wherein the second data set is associated with the second machine (160), controls operation of the second machine (160), and 2 data sets are:
the second data set, including second positional information and second characteristic information for characteristic 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;
geometrically superimposing the first location information on the second location information; and
the first location information and/or such that the sum of the distances between the two correlated pieces of location information from one and the same location on the printed circuit board 470, ie the first location information and the associated second location information, is reduced. and relocating the second location information. According to claim 1,
wherein the first machine is a first processing machine (110) for applying a physical change to a product including the printed circuit board (470) and the product-feature structure by a processing process. 3. The method of claim 2,
the first processing machine
(i) a solder paste printing machine (110) for selectively 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 soldering machine 150 for melting the solder paste located between component connection regions of the printed circuit board 470 and electrical connection contacts of components placed on the printed circuit board 470; A method, which is a machine selected from the group consisting of 4. The method according to any one of claims 1 to 3,
wherein the second machine is a first inspection machine (160) that detects a product-feature structure by an inspection process. 5. The method of claim 4,
the 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 machine selected from the group consisting of a soldering inspection machine (160) for detecting soldered components. 6. The method according to any one of claims 1 to 5,
providing a third data set from a third machine (160), wherein the third data set is associated with the third machine (130), controls operation of the third machine (130), and The 3 data sets are:
the third data set, comprising third positional information and third characteristic information for characteristic target characteristics of a product-feature structure of the printed circuit board (470) at a plurality of positions on the printed circuit board (470) Further comprising the step of providing
The geometric overlapping step is
further comprising geometrically overlapping the third location information with the first location information and/or the second location information; and
The relocation step
the sum of the three distances between each of the three correlated location information fragments, i.e.
of one and the same 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) a sum of a third distance between the third location information and the first location information is reduced;
and relocating the third location information. 7. The method of claim 6,
wherein the third machine is a second processing machine (130) that further causes a physical change to the printed circuit board (470) and a product comprising the product-feature structure by a processing process. 8. The method of claim 7,
providing a fourth data set from a fourth machine (120), wherein the fourth data set is associated with the fourth machine (120), controls operation of the fourth machine (120), and The 4 data sets are:
the fourth data set, comprising fourth positional information and fourth characteristic information for characteristic target characteristics of the product-feature structure of the printed circuit board (470) at a plurality of positions on the printed circuit board (470) Further comprising the step of providing
The geometric overlapping step is
further comprising geometrically overlapping the fourth location information with the first location information, the second location information, and/or the third location information; and
The relocation step
the sum of the six distances between each of the four correlated location information fragments, i.e.
of one and the same point on the printed circuit board,
(i) said first distance;
(ii) said second distance;
(iii) said 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) the sum of the sixth distance between the fourth location information and the first location information is reduced;
and relocating the fourth location information. According to claim 2, 4 and 7, according to claim 8,
the first machine is the first processing machine 110;
the second machine is the first inspection machine (160) for detecting the product-feature structure at a first inspection point along the production line (100);
the third machine is the second processing machine 130 arranged downstream of the first processing machine 110 with respect to the conveying direction T of the production line 100 ; and
and the fourth machine is the second inspection machine (120) for detecting the product-feature structure at a second inspection point along the production line (100). A method for adapting process parameters for a process for producing electronic assemblies by automated production in a production line ( 100 ), said method comprising:
10. Carrying out the method according to any one of claims 6 to 9, wherein the first machine is a first processing machine (110), the first data set comprises a first process data set, and a second machine is a first inspection machine 160 and the second data set includes a first inspection data set, the third machine is a second processing machine 130, and the third data set includes a second process data set. the performing step;
between an actual characteristic and a target characteristic of the product-feature structure in a first area of the printed circuit board 470 associated with a first position on the surface of the printed circuit board 470 by the first inspection machine 160 . determining a first deviation;
(i) in each case, 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 comprises a second portion of the printed circuit board (470). based on said at least a first portion associated with a region and
(ii) generating a first combined data set (375) further based on the relocated first location information and/or the relocated second location information and/or the relocated third location information;
First process parameters of the first processing machine 110 and/or second process parameters of the second processing machine 130 based on the generated first combined data set 375 and the determined first deviation A method comprising the step of adapting them. 11. The method of claim 10,
A first region of the printed circuit board 470 is such that a first deviation between an actual characteristic and a target characteristic of the product-feature structure is associated with a second location on the surface of the printed circuit board 470 . ) is an area of the printed circuit board (470) that is greater than a second deviation between an actual property and a target property of the product-feature structure in a second area;
wherein the second location is different from the first location. 11. The method of claim 10,
determining, by the first inspection machine (160), a second deviation between an actual characteristic and a target characteristic of the product-feature structure in a second region of the printed circuit board (470);
(i) in each case at least a second portion of a first process data set, a second process data set, and a first inspection data set, the second portion comprising a second region of the printed circuit board (470); associated, based on the at least second part, and
(ii) generating a second combined data set further based on the relocated first location information and/or the relocated second location information and/or the relocated third location information; and
first process parameters of the first processing machine 110 and/or second process parameters of the second processing machine 130 further based on the generated second combined data set and the determined second deviation The method further comprising the step of adapting. 13. The method according to any one of claims 10 to 12,
The step of adapting the first process parameters of the first processing machine (110) and/or the second process parameters of the second processing machine (130) is performed iteratively by at least one learning algorithm. A production line (100) for the automated production of an electronic assembly, the production line having 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 method of (100),
a first machine 110 for processing products including printed circuit boards and product-feature structures;
a second machine (160) for inspecting the product-feature structure;
a third machine 130 for processing the product; and
14. A method according to any one of claims 10 to 13, communicatively connected to the first machine (110), the second machine (160) and the third machine (130) and for adapting process parameters. A production line having a data processing unit (μP) arranged to perform A computer program for adapting process parameters to a process for the production of an electronic assembly by automated production on a production line (100), the computer program comprising:
The computer program, when executed by a data processing unit (μP) of the production line (100), is arranged to perform the method according to any one of claims 10 to 13.

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