Classifications

• • H—ELECTRICITY
  • H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
  • H05K—PRINTED CIRCUITS; CASINGS OR CONSTRUCTIONAL DETAILS OF ELECTRIC APPARATUS; MANUFACTURE OF ASSEMBLAGES OF ELECTRICAL COMPONENTS
  • H05K13/00—Apparatus or processes specially adapted for manufacturing or adjusting assemblages of electric components
  • H05K13/08—Monitoring manufacture of assemblages
  • H05K13/083—Quality monitoring using results from monitoring devices, e.g. feedback loops
• • H—ELECTRICITY
  • H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
  • H05K—PRINTED CIRCUITS; CASINGS OR CONSTRUCTIONAL DETAILS OF ELECTRIC APPARATUS; MANUFACTURE OF ASSEMBLAGES OF ELECTRICAL COMPONENTS
  • H05K13/00—Apparatus or processes specially adapted for manufacturing or adjusting assemblages of electric components
  • H05K13/04—Mounting of components, e.g. of leadless components
  • H05K13/0404—Pick-and-place heads or apparatus, e.g. with jaws
  • H05K13/0413—Pick-and-place heads or apparatus, e.g. with jaws with orientation of the component while holding it; Drive mechanisms for gripping tools, e.g. lifting, lowering or turning of gripping tools

Definitions

• the present invention relates to the technical field of the production of electronic assemblies in a production line which has a plurality of machines, such as, in particular, a placement machine for placing electronic components on a printed circuit board, and an inspection machine for determining the quality of preceding process steps.
• the present invention relates in particular to a method for analysing process data of such a production line as well as a method for optimising a manufacturing process for electronic assemblies.
• Electronic assemblies typically have 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 production lines which have a plurality of machines connected to one another via a conveyor belt for manufacturing or processing and machines for (optical) inspection of intermediate products.
• Such machines typically comprise
• solder paste printing machine for applying solder paste selectively to component connection areas or connection areas which are formed on a surface of the relevant printed circuit board
• solder paste inspection machine for verifying correct application of solder paste
• soldering machine or an oven for melting on the solder paste, which is located between component connection areas of the fitted printed circuit board and electrical connection contacts of the relevant components;
• the at least one inspection machine is used to separate out faulty or poorly processed printed circuit boards from the production process or to direct them to repair.
• the separation takes place at a certain point in the production line by means of a suitable device for discharging, which in this document is descriptively referred to as a gate. It is obvious that, for cost-benefit reasons, such a separation should take place as early as possible.
• a separation can have two different reasons.
• a first reason can be that the processed printed circuit board, also called product or intermediate product in this document, is actually defective or of (very) poor quality.
• a second reason can be that the product or intermediate product is completely in order but the relevant inspection machine has incorrectly reported an error.
• the threshold values for error detection such that, on the one hand, defective products are reliably detected and, on the other hand, as few incorrect errors as possible are output.
• a separated product or a separated processed printed circuit board can be examined manually by an experienced operator and, if necessary, reworked. Based on the result of such an assessment, process parameters such as a squeegee speed in a solder paste printing machine can then be improved or optimised for future printing processes. In addition, the aforementioned threshold values for error detection can be adapted.
• the invention is based on the object of making it easier to optimise process parameters and/or to adjust threshold values for error detection when producing electronic assemblies.
• a method for correlating different data sets which are associated with one and the same printed circuit board on which an electronic assembly with a plurality of electronic components is built by means of automated production on a production line.
• the method described includes (a) providing a first data set from a first machine, wherein the first data set (al) is associated with the first machine, (a2) controls an operation of the first machine, and (a3) includes: first position information and first characteristic information about characteristic target properties of a product-characteristic structure of the printed circuit board at a plurality of positions on the printed circuit board; (b) providing a second data set from a second machine, wherein the second data set (bl) is associated with the second machine, (b2) controls an operation of the second machine, and (b3) includes: second position information and second characteristic information about characteristic target properties of the product-characteristic structure of the printed circuit board at the plurality of positions on the printed circuit board; (c) geometrically superimposing the first position information on the second position information; and (d) reposition
• the method described is based on the knowledge that by means of suitable geometric repositioning of a first coordinate system of the first position information and/or a second coordinate system of the second position information in relation to one another, the process data of the various machines can be compared with one another or can be correlated with one other with regard to product-characteristic results of an intermediate product or an end product (finished assembly).
• this repositioning represents the basis for comparing or correlating the data from different machines. This means that not only the effect of process parameters on the processing result of a single machine can be examined. Rather, the (combinatorial) effect of a plurality of process parameters that are associated with different processing machines can be evaluated for characteristic properties or the quality of the intermediate product, and in particular the end product.
• a suitable adjustment of process parameters of the processing machines and/or suitable adjustment of threshold values of the inspection machines or devices for separating (gates) can improve the manufacturing process of electronic assemblies in two ways. Firstly, the quality of the electronic assemblies or end products produced can be improved. Alternatively or in combination, the proportion of non-defective (end) products incorrectly separated from the manufacturing process can be reduced.
• the described relative repositioning of the two (different) coordinate systems is carried out according to the invention such that the product-characteristic structures of the printed circuit board, which are of course the same for the (one and the same) printed circuit board and are merely detected and processed or treated by the various machines in different coordinate systems will have as large an overlap as possible in the two coordinate systems after repositioning.
• correlation can be understood to mean any type of geometric association of coordinates from different coordinate systems, which association ensures that one and the same structure of the printed circuit board is also described as the same structure in both coordinate systems (and in both data sets).
• a specific pad on the printed circuit board which pad is provided for a specific electrical connection contact of a specific component of the electronic assembly, must be described as the same pad in both data sets. It is obvious that a correct geometric repositioning is of primary importance.
• the correlation of the various data sets can take place in any suitably programmed data processing device in which the data sets are located at least temporarily. It does not matter whether these data sets are obtained from the respective machine of the production line by means of suitable data transmission or whether the two data sets are already stored in the relevant data processing device and are transmitted from it to the relevant machine.
• the correlation i.e. the result of the correlating
• a correlation table represents a particularly simple, yet effective way of describing or recording an association between the various contents or elements of the various data sets.
• the component connection contacts of components and the component connection areas of printed circuit boards to be fitted with the components can be associated with one another, for example, as described in detail below.
• machine can be understood to mean any type of device which contributes to the production of the electronic assembly.
• a machine can be a processing machine or an inspection machine.
• a processing machine of the production line described is, for example, a solder paste printing machine described in the introduction, a placement machine, or a soldering machine, such as a reflow oven.
• An inspection machine can be an optical inspection machine which detects the intermediate product or the end product in two or three dimensions. The inspection machine can be arranged at the most varied locations in the production line.
• solder paste inspection machine In the case of an arrangement along a transport direction, downstream of the solder paste printing machine and upstream of the placement machine, the results of a solder paste printing process can be inspected. Such an inspection machine is referred to in this document as a "solder paste inspection machine".
• position information can be understood to mean any position-specific indication of a point or a location on the printed circuit board.
• Position information is in particular the positions of the component connection areas or pads on the surface of the printed circuit board which come into electrical contact with the connection contacts of the components when the printed circuit board is fitted with components.
• the position information with regard to one and the same printed circuit board position naturally has different values in different coordinate systems (of different machines).
• the term "characteristic information" can be understood to mean any information about the spatial physical, optical and/or electrical condition or property of a specific location on the printed circuit board or a specific (small) area of the printed circuit board, such as a pad.
• Spatial physical characteristic information can be geometrical two-dimensional information, for example an indication of the position, the size and/or the shape of a pad.
• spatial physical characteristics information can be three-dimensional information, for example an indication of the volume of a solder paste application on a specific pad.
• Optical characteristic information can be, for example, information about the colour and/or the reflectivity of a pad, which can be an indication of, for example, possible corrosion of a pad or an indication of a cold solder joint.
• Electrical characteristics information can be, for example, an indication of the electrical conductivity of a conductor track on the surface of the printed circuit board.
• product-characteristic structure can be understood to mean all structural or spatial physical features which are characteristic of a certain type of printed circuit board.
• one type of printed circuit board can be differentiated from another type of printed circuit board on the basis of (a) product-characteristic structure(s).
• Such features can be, for example, the position, the size, and/or the shape of pads.
• repositioning in this document can be any type of geometric change of a coordinate system which is used for the description of the relevant data set.
• repositioning can be a displacement, rotation and/or, in some application cases, also distortion of at least one of the two coordinate systems which are each associated with one of the two data sets.
• the two data sets are changed geometrically such that the position information in both data sets for selected locations on the printed circuit board in question is closer to one another than before the repositioning.
• the position information lies as close to one another as possible or even overlaps.
• the two coordinate systems are thus adapted to one another by means of a suitable coordinate transformation.
• this coordinate transformation can comprise a displacement, a rotation and/or a distortion.
• the "repositioning" described can be implemented by means of a known mathematical geometric calculation. Like all other calculations or algorithms, this can take place in any data processing device on the relevant production line for electronic assemblies.
• This data processing device can be associated with a specific machine. Alternatively or in combination, it can also be a central or higher-level data processing device that is directly or indirectly communicatively coupled to the individual machines of the.
• the term "totality of the distances between two mutually associated pieces of position information” can be understood to mean a sum of distances between two respective pieces of position information in different coordinate systems, wherein the two pieces of position information are coordinate points that relate to one and the same location on the printed circuit board. The sum is formed by adding up the absolute values of the distances for different locations on the printed circuit board. The totality can also be the sum of all square distances between position information associated with one another in relation to one and the same location on the printed circuit board.
• the repositioning can therefore be analogous to a best fit ("best fit") of a mathematical function to a plurality of measurement points which have a (statistical) spread and which, in the method described, are distance values.
• a data set therefore not only contains information about the product-characteristic structures of the relevant printed circuit board, but rather the data set also contains instructions or information on how the relevant machine has to perform its work. This applies to all of the machines mentioned, which, as described below, can be processing machines or inspection machines.
• a suitable controller ensures processing of the relevant printed circuit board.
• the relevant data set is not, or is not exclusively, a measurement data set with results of a previously performed inspection. Rather, the relevant data set (also) represents an inspection data set that controls an operation of the relevant inspection machine.
• a data set for an inspection machine or an inspection data set is therefore a work recipe (typically with a plurality of individual work instructions) for the relevant inspection machine, just as a process data set is a work recipe for a processing machine.
• an inspection machine must also be controlled. That is because, for reasons of efficiency, it would not be justifiable to inspect, for example, all areas of an (intermediate) product, i.e. of an at least partially processed printed circuit board, with one and the same accuracy. This would in fact significantly increase the time it takes to carry out an inspection. For example, those areas of the object to be inspected that are particularly relevant can be inspected particularly accurately, and other areas can be inspected with less accuracy or even not at all.
• the first machine is a first processing machine which, by means of a processing process, makes a physical change to a product which comprises the printed circuit board and the product-characteristic structure.
• the physical change can comprise adding a product-characteristic structure and/or changing the properties of the product- characteristic structure.
• the product-characteristic structure can be, for example, a volume of solder paste which is being or has been applied, by means of solder paste printing, to (at least) one component connection area or pad, which is formed on a surface of the printed circuit board in question.
• the product- characteristic structure can also be an electronic component or the spatial position, in two or three dimensions, of an electronic component which is being or has been placed on the printed circuit board by means of a placement machine.
• the first processing machine is a machine which is selected from the group, consisting of (i) a solder paste printing machine for applying solder paste selectively to component connection areas of the printed circuit board; (ii) a placement machine for placing electronic components on the printed circuit board; and (iii) a soldering machine for melting the solder paste, which is located between component connection areas of the printed circuit board and electrical connection contacts of components placed on the printed circuit board.
• the described selection of processing machines has the advantage that all typical processing machines of a production line for electronic components are included.
• the method described can thus be used for a data correlation between all types of processing machines in a production line. This applies to all machines that work with position-specific information or provide position-specific information as part of a measurement.
• the second machine is a first inspection machine which detects a product-characteristic structure by means of an inspection process.
• the first inspection machine or, more precisely, a data processing device which is contained in the first inspection machine or connected downstream of the first inspection machine, can compare a detected actual product-characteristic structure with a corresponding predetermined target product-characteristic structure and therefrom determine a quality value for the manufactured and detected product-characteristic structure.
• This quality value can be used to suitably adapt process parameters of a processing machine and/or at least one threshold value of the first inspection machine or of a further inspection machine.
• the first inspection machine preferably detects not just a single product- characteristic structure but a plurality of product-characteristic structures. Then said data processing device can compare more than one or at least some of the detected actual product-characteristic structures with a corresponding predetermined target product-characteristic structure and therefrom determine a plurality of quality values and/or a higher-level quality value for the produced and detected product-characteristic structure.
• the term "quality value” can be understood to mean any parameter or parameter value which determines, or at least helps determine, the quality of a manufactured electronic assembly.
• Such parameters include, for example, the position and the quantity (volume) of individual solder paste applications, the exact placement positions, and the visual appearance of solder after soldering, which can be an indication of a "cold solder joint", for example. This list is by no means exhaustive and can be supplemented almost arbitrarily by a person skilled in the art of placement technology.
• the aforementioned parameters can be the positions and the heights of placed or soldered components, which are of course also related with the amount of solder paste used for the respective solder connection. In this context it is obvious that these parameters are related with the quality of the electronic assembly produced. Otherwise these parameters would not even have to be detected by the relevant inspection machine.
• the first inspection machine described can be an optical inspection machine which detects the product-characteristic structure in one dimension, preferably in two dimensions, and more preferably in three dimensions. This has the advantage that the inspection can be carried out quickly and with a high degree of accuracy.
• the first inspection machine is a machine selected from the group, consisting of (i) a solder paste inspection machine for detecting applied solder paste; (ii) placement inspection machine for detecting placed components; and (iii) a soldering inspection machine for detecting soldered components.
• the detection of the solder paste can include, for example, detection of the position, the volume and/or the shape of a solder paste application. All of these observables naturally have a (strong) effect on the quality of the contacting of the components that are still to be placed.
• the detection of placed components can include, for example, the type of component, its placement 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 rests on the volume of the solder paste before subsequent soldering). It is obvious that all of these observables have a significant effect on the subsequent soldering process and thus on the final electrical contacting of the components.
• the detection of the soldered components can also include the type of soldered component, 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 rests on the volume of the temporarily melted and then solidified solder paste).
• it can be detected whether the component connection contacts (of the components) are correctly soldered to the corresponding component connection areas (of the printed circuit board) and are thus correctly electrically contacted. It is obvious that all of these observables have a significant impact on the quality of the final end product, namely the electronic assembly produced.
• the detection by the soldering inspection machine described can therefore be an important part of a final quality analysis of the finished (end) product.
• the final quality analysis optionally together with at least one non-final quality analysis, can be used to optimise the process parameters of processing machines and/or threshold values of the first inspection machine and optionally of further inspection machines by means of a suitable learning process.
• measurement data and process data can advantageously be merged by the described method. This can be done in particular with the aim of optimising the process data with the aid of the measurement data. This can advantageously enable a particularly precise analysis of the automated production.
• the described selection of inspection machines has the advantage that all typical inspection machines in a production line for electronic components are included.
• the method described can thus be used for a data correlation between all types of inspection machines in a production line and optionally also between all processing machines and all inspection machines in a production line for electronic assemblies.
• the method further includes (a) providing a third data set from a third machine, wherein the third data set (al) is associated with the third machine, (a2) controls an operation of the third machine and (a3) includes: third position information and third characteristic information about characteristic target properties of the product-characteristic structure of the printed circuit board at the plurality of positions on the printed circuit board; where the geometric superimposing further includes a geometric superimposing of the third position information with the first position information and/or the second position information; and wherein the repositioning further includes a repositioning of the third position information such that a totality of the sum of the three distances between each of three mutually associated pieces of position information, i.e. the sum of
• the described correlation between three (machine-specific) data sets has the advantage that the production process of an electronic assembly is analysed jointly not only on two, but on three different machines (processing machines and/or inspection machines) and the analysis result can be used for an improved adaptation of process parameters of the processing machines and/or threshold values of the first inspection machine and optionally further inspection machines.
• the third machine can be a processing machine or an inspection machine, wherein in principle all of the types of processing machines described above are possible.
• the third machine should be one type of machine so that there are not two solder paste printing machines and not two soldering machines on the production line.
• the production line can contain two or more placement machines.
• the third machine is a second processing machine which, by means of a processing process, makes a further physical change to a product which comprises the printed circuit board and the product-characteristic structure.
• the further physical change can also comprise adding a product-characteristic structure and/or changing the properties of the product-characteristic structure.
• the product-characteristic structure can be, for example, an electronic component which is being or has been placed on the printed circuit board by means of a placement machine.
• the product- characteristic structure can relate to a state before soldering or to a state after soldering.
• the second machine described above embodied as a first inspection machine, can be arranged between the two processing machines in relation to a transport direction of the production line.
• 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 both processing machines. This means that the "work" of both processing machines can be inspected jointly.
• no further processing machine is arranged downstream of the first inspection machine.
• the first inspection machine inspects the final product of the production line.
• An inspection of the end product and a suitable feedback of the inspection result to the two processing machines has the advantage that the process parameters of the processing machine(s) can be adapted or optimised with regard to the final desired product characteristics of the manufactured electronic assembly.
• the method further includes (a) providing a fourth data set from a fourth machine, wherein the fourth data set (al) is associated with the fourth machine, (a2) controls an operation of the fourth machine and (a3) includes: fourth position information and fourth characteristic information about characteristic target properties of the product-characteristic structure of the printed circuit board at the plurality of positions on the printed circuit board.
• the geometric superimposing further includes a geometric superimposing of the fourth position information with the first position information, the second position information and/or the third position information.
• the repositioning further includes a repositioning of the fourth position information such that a totality of the sum of the six distances between each of four mutually associated pieces of position information, i.e. the sum of (i) the first distance, (ii) the second distance,
• the fourth machine can be a processing machine or an inspection machine.
• the first machine is the first processing machine; the second machine is the first inspection machine which detects the product-characteristic structure at a first inspection point along the production line; the third machine is the second processing machine which is arranged downstream of the first processing machine with respect to a transport direction of the production line; and the fourth machine is the second inspection machine which detects the product-characteristic structure at a second inspection point along the production line.
• the second inspection is preferably upstream of the first inspection point and more preferably between (a) a first processing location by the first processing machine and (b) a second processing location by the second processing machine.
• 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 second machine or the first inspection machine is a placement inspection machine or a soldering inspection machine.
• a third processing machine namely a soldering machine
• a placement inspection machine which directly inspects the assembly result, can optionally be located between the soldering machine and the second processing machine, embodied as a placement machine.
• 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.
• Position 6 The second machine or the first inspection machine is a soldering inspection machine.
• the placement machine is a system that consists of two or more placement devices.
• a placement device can each have one or more placement heads, which can be moved in a known manner by means of a portal system and which, in a placement operation, pick up components from a component feeding device and place them on a printed circuit board which is currently located in a placement area of the placement device.
• a method for adapting process parameters for a process for the production of electronic assemblies by means of automated production on a production line.
• This method includes (a) carrying out the method described above, provided it is carried out with at least three machines, wherein (al) the first machine is a first processing machine and the first data set contains a first process data set; wherein (a2) the second machine is a first inspection machine and the second data set contains a first inspection data set; wherein (a3) the third machine is a second processing machine and the third data set contains a second process data set.
• This process parameter adaptation method further includes (b) determining, by means of the first inspection machine, a first deviation between an actual property and a target property of the product-characteristic structure in a first area of the printed circuit board which is associated with a first (spatial) area of the printed circuit board; (c) creating a first combination 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 repositioned first position information and/or the repositioned second position information and/or the repositioned third position information.
• the process parameter adaptation method described further includes (d) adapting first process parameters of the first processing machine and/or second process parameters of the second processing machine based on the created first combination data set and the determined first deviation.
• the described method for adapting process parameters is based on the knowledge that, by joint consideration of a plurality of possible and different processing machines, associated causes for undesired (first) deviations of real actual properties from desired target properties of product-characteristic structure(s), a particularly good adjustment of process parameters can be carried out. That is because such an adaptation leads to significantly better results or improved production compared to a conventional adaptation in which only the process data set of a single processing machine is taken into account.
• the causes of such undesired deviations are sub-optimally set process parameters of the processing machines involved in production.
• the data or information that is associated with the relevant first area of the printed circuit board is used to create the combination data set. Since the data sets from different machines (processing machines and/or inspection machines) are usually based on different (formats of) descriptions and different coordinate systems, it is first necessary to perform the positionally correct 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 correlated with one another positionally correct with regard to the respective location or the respective area of the printed circuit board. The described correlation can therefore also be understood as a positionally correct combination of information.
• the above- described 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).
• machine-specific data sets process data sets and/or inspection data sets.
• “translation”, "languages” and/or “data formats” of the various data sets are translated such that a positionally correct correlation of the information contained in the various data sets becomes possible.
• the combination data set described here represents a positionally correct combination of the information from the output data sets in relation to each different area of the printed circuit board. To illustrate, this means that the information contained in the two process data sets and the inspection data set is merged positionally correct with respect to the real printed circuit board.
• the repositioning described above and the flow of the data sets into the combination data set are related to one another as follows: For a positionally correct merging of the characteristic information about characteristic target properties of the product-characteristic structure of the printed circuit board, it is necessary to first transform the different coordinate systems of the relevant data sets so that the information can be merged positionally correct.
• the repositioning which, as already mentioned above, can comprise a displacement, a rotation and/or a distortion, represents this transformation. This is carried out such that the totality of the specified distances is reduced or minimised.
• the first (spatial) area of the printed circuit board is an area of the printed circuit board in which the first deviation between the actual property and the target property of the product- characteristic structure is greater than a second deviation between an actual property and a target property of the product-characteristic structure in a second (spatial) area of the printed circuit board which is associated with a second location on the surface of the printed circuit board.
• the second location or the second area is/are different from the first location or the first area.
• the first area is more problematic or critical than the second area with regard to the quality of the assembly to be manufactured.
• a selection of the different areas of the printed circuit board can be based on a priori knowledge and/or experience of an operator. Furthermore, the selection can also be made on the basis of at least approximately complete, i.e. full-area, inspections of the printed circuit board (performed only rarely), in which the degree of deviations is determined for different locations or areas of the printed circuit board.
• the method further includes (a) determining, by means of the first inspection machine, the second deviation between an actual property and a target property of the product-characteristic structure in the second (spatial) area of the circuit board; (b) creating a second combination data set based on (bl) 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 area of the printed circuit board and further based on (b2) the repositioned first position information and/or the repositioned second position information and/or the repositioned third position information; and (c) adapting the first process parameters of the first processing machine and/or the second process parameters of the second processing machine further based on the created second combination data set and the determined second deviation. Taking into account the deviation(s) in the second area allows for the process parameters to be adapted even more precisely with regard to the best possible quality of the finished end product.
• process parameter adaptation 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 inspection machine.
• it is only necessary to create suitable combination data sets wherein it must of course always be ensured that the information contained in the various process data sets and the inspection data sets must always be merged with one another positionally correct or combined with one another positionally correct.
• adapting the first process parameters of the first processing machine and/or the second process parameters of the second processing machine is carried out iteratively by means of at least one learning algorithm.
• This has the advantage that the process parameters can be improved, for example, by means of artificial intelligence.
• it makes sense if the described method is carried out, within the framework of the production of a certain type of electronic assembly, for each individual or at least for a large number of assembly productions.
• a data processing device on which the required learning algorithms are carried out receives a large amount of learning data. This enables a particularly good adaptation of the process parameters with regard to the best possible quality of the end product electronic assembly.
• a production line for the automated production of an electronic assembly, having a printed circuit board and a plurality of electronic components which are attached to the printed circuit board and are electrically interconnected by means of conductor tracks.
• the production line described has (a) a first machine for processing a product comprising the printed circuit board and a product-characteristic structure; (b) second machine for inspecting the product-characteristic structure; (c) a third machine for processing the product; and (d) a data processing device which is communicatively coupled to the first machine, the second machine, and the third machine and which is arranged to carry out the method described above for adapting process parameters.
• a computer program for adapting process parameters for a process for the production of electronic assemblies by means of automated production on a production line.
• the computer program when it is executed by a data processing device of the production line, is arranged to carry out the method described above for adapting process parameters.
• the computer program can be implemented as computer-readable instruction code in any suitable programming language.
• the computer program can be saved on a computer-readable memory device (CD-ROM, DVD, Blu-ray disc, removable drive, volatile or non-volatile memory, built-in memory/processor, etc.).
• the instruction code can program a computer or other programmable devices such that the desired functions are executed.
• the computer program can be provided in a network, such as the internet, from which it can be downloaded by a user when required.
• the invention can be realised by means of a computer program, i.e. software, as well as by means of one or a plurality of special electronic circuits, i.e. in hardware or any other hybrid form, i.e. by means of software components and hardware components.
• Figure 1 shows a production line for electronic assemblies with a higher-level data processing device for correlating process data and inspection data from various processing or inspection devices of the production line.
• Figure 2 illustrates a correlation of process data and inspection data, among other things for the subsequent optimisation of process parameters of a processing machine embodied as a solder paste printing machine.
• Figure 3 shows a correlation data set implemented as a correlation table for two different types of printed circuit boards.
• Figure 4 uses a block diagram to show an optimisation of process data for a placement.
• Figure 5 shows a repositioning of position data.
• Figure 1 shows a production line 100 for electronic assemblies.
• the production line has various devices which are arranged along a transport path for printed circuit boards.
• the direction of transport of the printed circuit board transport path is indicated in Figure 1 by an arrow labelled "T".
• the production line 100 Along the transport direction T, the production line 100, in a known manner, has an input station 102 in which prefabricated but not yet printed circuit boards are fed. Downstream of the input station 102, there is a device 104 for marking printed circuit boards by means of laser beams.
• solder paste printing machine 110 which selectively applies solder paste to specific points on the printed circuit board by means of a known screen printing method. These points are typically the component connection areas or pads on the surface of the relevant printed circuit board.
• the application of the solder paste is not a simple process in practice because the solder paste must be applied in a precise position and precise quantity for each component connection area.
• a plurality of process parameters of the solder paste printing machine 110 must be set correctly. These process parameters comprise, for example, the speed of a squeegee, which is guided along the surface of a so-called printing screen and ensures that the viscous solder paste is transferred into an opening in the printing screen in the correct amount.
• solder paste inspection machine 120 Downstream of the solder paste printing machine 110, there is a solder paste inspection machine 120, by means of which it is optically verified whether the solder paste print is of sufficient quality so that it makes sense to further process the printed circuit board.
• the solder paste inspection machine 120 is also referred to as an SPI machine.
• the assembly system comprises a total of three placement machines 130, by each of which a certain number of (different) components are placed on the component positions defined by the previously applied solder paste depots.
• the placement inspection machine 140 Downstream of the assembly system, there follows a placement inspection machine 140, by means of which it is verified whether the placement of the printed circuit boards carried out by the three placement machines 130 was correct.
• the placement inspection machine 140 optically detects the placed components in two dimensions (2D) and in three dimensions (3D).
• the placement inspection machine 140 is a known automatic optical inspection (AOI) machine.
• soldering machine 150 Downstream of the AOI machine 140, there is a soldering machine 150, which is embodied in a known manner as a so-called reflow oven. The viscous solder paste is melted in this reflow oven 150 so that, after the solder paste has cooled down later, the components are in firm and electrically conductive contact with the respective component connection areas.
• a soldering inspection machine 160 follows (downstream), by means of which it is verified whether the soldering process carried out in the reflow oven 150 was (qualitatively) successful.
• the soldering inspection machine 160 is also a known AOI machine here.
• the AOI machine 160 is followed by an output station 162.
• the fully processed electronic assemblies can be removed from there by an operator.
• a higher-level data processing device mR which in particular collects the inspection data from the various inspection machines 120, 140 and 160 and evaluates them jointly. Furthermore, current process data from the processing machines 110, 130 and 150, in particular from the solder paste inspection machine 120, are collected and evaluated jointly with the inspection data with regard to the highest possible quality of the final product, i.e. the electronic assemblies produced. For this purpose, methods or algorithms of artificial intelligence are preferably used. This evaluation then leads to optimised process parameters which can be stored in a database DB.
• a joint evaluation of the data sets provided by the various machines is not that simple, however. In terms of content, the various data sets relate to all (relevant) positions on the respective printed circuit board.
• each machine typically uses its own data format for this purpose.
• These data formats differ in particular in the process-specifically different position descriptions of the various locations and the components on the printed circuit board. It is therefore necessary to reposition the corresponding position information of the various data sets and to superimpose them geometrically such that they "coincide” as well as possible.
• the corresponding method for correlating the various data sets which is carried out in the data processing device mR and which represents a central aspect of the invention described in this document, is explained in detail further below.
• IDDCF inter device data correlation functionality
• the data processing device mR connects at least some of the machines and retrieves detailed work data therefrom, which in this document is also referred to as "work recipes".
• work recipes contain instructions or information on how the relevant machine is to do its job. For clarification: This not only applies to the processing machines, but also to the inspection machines.
• a work recipe for the solder paste printing machine 110 includes, for example (and without limitation) the size and format of the relevant printed circuit board, the locations on the printed circuit board where to apply the solder paste, process parameters, such as the speed of the above-mentioned squeegee, cleaning cycles for the squeegee, etc.
• a work recipe for the solder paste inspection machine 120 includes, for example, a layout description of where the solder paste depots are to be expected and how these depots should look in 2D and 3D for the solder paste inspection machine 120. Furthermore, a layout description can also comprise information about the expected or desired volumes of solder paste and, optionally, their tolerable tolerances.
• a work recipe for the placement machines 130 includes, for example, the respective placement positions as well as process information, such as vacuum values for the negative pressure with which components are held by a suction gripper, the pressure or force when the components are placed on the printed circuit board, travel speeds of a placement head, etc.
• a work recipe for both AOI machines 140 and 160 includes, for example, information about (selected) solder connections that are to be inspected (upstream and downstream of the reflow oven 150), target positions and target heights of placed or soldered components, etc.
• the above-mentioned exemplary work recipes are correlated with one another using the above-mentioned IDDCF.
• the position information of all components and their electrical connections are analysed positionally correctly, i.e. with a correct geometric superimposition of the product-characteristic structures of the printed circuit board.
• connection or pin identification number for an AOI machine corresponds to which component connection area identification number that is used by the SPI machine.
• placement positions used by the placement machines 130 can be correlated with the component receiving positions, which can be obtained from process data management of the respective placement machine 130. These position correlations, or correlations with respect to the identification numbers, should be re-determined any time that at least one work recipe for at least one of the machines involved in the production line 100 is changed.
• Figure 2 illustrates a correlation of process data and inspection data, among other things for the subsequent optimisation of process parameters of a processing machine embodied as a solder paste printing machine.
• this process begins with the work recipes for the solder paste inspection, for the placement inspection and for the placement process being collected by the placement machines 130 in a step SI.
• the work recipes contain, among other things, detailed information about the layout of the respective printed circuit board, the components to be placed thereon (positions and sizes) and their component connection contacts.
• a correlation table which correctly associates the component connection contacts and the component connection areas (pads) with one another for all machines involved. This association takes place not only on the basis of positions on the respective type of printed circuit board, but also on the basis of identification numbers of components, identification numbers of component connection areas and/or identification numbers of component connection contacts. As a result, different designations of components and identification names of the various machines involved in the production process and their work recipes can sometimes be correctly associated.
• this correlation table can be used to correlate (a) the work recipes from at least one AOI inspection machine and the solder paste inspection machine and (b) the work recipes of the solder paste printing machine and the placement machine, which work recipes contain the current process parameters.
• step S3 there is then a wait for results from the various inspection machines. These results all relate to a specific printed circuit board.
• step S4 the previously determined position assignment is used in a next step S4 in order to correlate these results with one another.
• the correlation table determined in step S2 is used for this purpose.
• a next step S5 the correlated results, the (current) work recipes and the correlation data are stored in a database DB.
• the database DB is the basis for a so-called “big data” analysis to be carried out by a processor, not shown in Figure 2, and so that the results of the "big data” analysis can be displayed to an operator by means of a suitable visualisation.
• the "Big Data” analysis can be used to find out fundamental reasons (so-called "root causes”) for defects in electronic assemblies at the end of the production line.
• Such a "big data” analysis can also be used to adapt threshold values of the inspection machines for separating defective intermediate products such that the probability of false error messages is reduced.
• a step S6 the correlation results are transmitted to the respective inspection machine or processing machine.
• locations on the printed circuit board that are particularly relevant for an application of solder paste can then be identified with regard to possible defects.
• at least some process parameters can then be set such that the probability of defective applications of solder paste is reduced, and thus automatically the reject rate of printed circuit boards printed with solder paste, even before components are placed.
• Figure 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.
• the first printed circuit board 370a is referred to as panel 1
• the second printed circuit board 370b is referred to as panel 2.
• the first printed circuit board 370a is referred to as panel A
• the second printed circuit board 370b is referred to as panel B.
• this association is stored in the first two lines of the correlation table 375.
• further correlations with regard to different types of component are stored in the correlation table 375.
• Unique identification numbers are used for this purpose. According to the exemplary embodiment shown here, these are the IDs R100, R101, ..., R100_a, R101_a, ..., etc. for resistors, the IDs CIOO, C101, ..., C100_b, C101_c for capacitors, the IDs D100, R101, D100_c, D101_c for diodes and the IDs Q2 and Q2_x for ball grid arrays.
• Figure 4 uses a block diagram to show an optimisation of process data for a placement. As already explained several times above, the optimisation is based on a positionally correct superimposition of the descriptions of one and the same printed circuit board by different machines or in different work recipes.
• the layout of a printed circuit board 470 is clearly visualised in the work recipe or the coordinate system for a placement machine.
• the same layout of the printed circuit board 470 is clearly visualised in the work recipe or the coordinate system for an AOI machine.
• the optimisation of process data for the placement requires a positionally correct superimposition of the position descriptions of the two layouts, i.e. the description 482 of the placement positions and the description 483 of component positions in the coordinate system or the work recipe of the respective AOI machine.
• the position description 482 for the placement depends on the work recipe for the placement (placement work recipe 481).
• a data set 484 is created as a correlation table, which associates the component positions in the various coordinate systems or work recipes with one another.
• a further correlation table 486 is generated, in which a correlation between (i) the placement positions and (ii) the component pick-up positions of the respective components from a component feeder is described.
• optimised process data 487 is then determined for a component pick up and a component placement in relation to the lowest possible rate of incorrectly placed components. Incorrectly placed components would, as already described above, be recognised by an AOI machine as component defects (hopefully correctly).
• a plurality of centre point positions can be viewed as a "fingerprint" for a specific product or for 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 was not, it would not be the same product.
• a positionally correct superimposition is carried out using such a fingerprint for two different layout descriptions of a printed circuit board, with at least one of the two layout descriptions being displaced such that a totality of the distances between two mutually associated positions of component connection contacts and/or component connection areas is minimised.
• a known so-called “nearest neighbour” algorithm can be used for this purpose.
• Figure 5 illustratively shows a repositioning of position data that is used by different machines for one and the same printed circuit board 570.
• the open circles represent the centre points of component connection contacts as they are used for or by an AOI machine (cf. reference numeral 140 in Figure 1).
• the solid circles represent the centre points of component connection areas as they are used for or by an SPI machine (cf. reference numeral 120 in Figure 1).
• repositioning can also be performed iteratively with a plurality of loops. For example, after a first method for repositioning which does not provide 100% agreement, a second method for improved repositioning can be carried out.

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• 2020
  • 2020-02-27 DE DE102020105185.9A patent/DE102020105185A1/de active Pending
• 2021
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  • 2021-02-23 CN CN202180016247.0A patent/CN115136750A/zh active Pending
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