Method for generating a coating route, computer program product, route generating device and coating device

Abstract

The present application proposes a method for generating a coating route, according to which a plurality of protective strips are applied to a device on a circuit board by an application device, the coating route being generated on the basis of a genetic algorithm, in which two respective end points of the plurality of protective strips are differently identified, each individual of the population contains identifications of all endpoints of all guard bars and characterizes a potential coating route of the plurality of guard bars in the order of the identifications, respectively, a pair of identifications of two endpoints of each guard bar forming a gene of the individual, respectively. The invention also relates to a corresponding computer program product, a route generation device and a coating device. The method has the advantages that the application mode of the genetic algorithm in the scene of coating the protection strip is provided, and the relatively optimal coating route in the global direction can be found in limited time through the genetic algorithm.

Description

Technical Field

[0001] This application relates to a method for generating coating patterns, a computer program product, a pattern generation apparatus, and a coating device. In particular, this application relates to the field of applying protective strips to devices on a circuit board. Background Technology

[0002] Circuit board assemblies are frequently used in the field of electronics. A circuit board assembly consists of a circuit board and the components, especially electronic components, mounted on it. To protect these components from external environmental factors, protective strips are applied. Traditionally, the application path for these protective strips is designed manually. This is wasteful of manpower and time, and the quality of the application path largely depends on the designer's experience and skill. Summary of the Invention

[0003] The purpose of this application is to provide a method for generating coating routes, which enables the machine to quickly and automatically generate globally optimal coating routes.

[0004] According to a first aspect of this application, a method for generating coating routes is provided, wherein a coating device applies multiple protective strips to devices on a circuit board according to the coating routes, wherein the coating routes are generated based on a genetic algorithm, in which each of the two endpoints of the multiple protective strips is given a different identifier, each individual in the population contains identifiers of all endpoints of all protective strips and represents a potential coating route of the multiple protective strips in the order of the identifiers, and a pair of identifiers of the two endpoints of each protective strip forms a gene of the individual.

[0005] According to a second aspect of this application, a computer program product is provided, comprising computer program instructions that, when executed by one or more processors, enable the processors to perform the aforementioned method for generating coating routes.

[0006] According to a third aspect of this application, a route generation apparatus is provided, the route generation apparatus including a processor and a memory, the memory storing computer program instructions, which, when executed by the processor, enable the processor to perform the aforementioned method for generating coating routes.

[0007] According to a fourth aspect of this application, a coating apparatus is provided, the coating apparatus comprising a coating device for applying a protective strip and the aforementioned route generation device.

[0008] At least in some embodiments, the positive effect of this application is that it provides a way to apply genetic algorithms in the scenario of applying protective strips: through genetic algorithms, a relatively optimal application route can be found globally within a limited time. Attached Figure Description

[0009] The principles, features, and advantages of this application will be better understood below with reference to the accompanying drawings. The drawings include:

[0010] Figure 1 An example of the coating apparatus of this application is illustrated schematically.

[0011] Figure 2 The illustration shows an example of a protective strip layout generated based on the device's placement on the circuit board.

[0012] Figure 3 An example is shown based on Figure 2 The four individuals were generated based on the identifier.

[0013] Figure 4 An exemplary flow of the method for generating coating routes according to this application is illustrated schematically.

[0014] Figure 5 An example of multiple individuals generated in the initial population generation step is illustrated.

[0015] Figure 6 An example of a crossover step is illustrated.

[0016] Figure 7 An example of a mutation step is illustrated. Detailed Implementation

[0017] To make the technical problems to be solved, the technical solutions, and the beneficial technical effects of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and several exemplary embodiments. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit the scope of protection of this application.

[0018] Figure 1An example of the coating apparatus of this application is schematically illustrated. The coating apparatus includes a coating device 200 for applying a protective strip 206 and a route generation device 201. The coating device 200 is specifically used to apply the protective strip 206 onto devices 203 on a circuit board 202 using a coating head 205. The circuit board 202 and devices 203 together can be referred to as a circuit board assembly 204. Devices 203 are, in particular, electronic devices. The protective strip 206 may, for example, have protective properties such as moisture resistance, dust resistance, chemical resistance, and electrical insulation. By covering the devices 203 on the circuit board 202 with the protective strip 206, these devices 203 can be protected from external environmental factors. This improves the robustness and service life of the devices 203 and the circuit board assembly 204. For simplicity, the coating head 205 can apply the protective strip 206 in a two-dimensional coating path parallel to the circuit board 202.

[0019] In order to apply the protective strips 206, it is necessary to first know which protective strips 206 to apply on the circuit board 202, that is, to first determine the layout of the protective strips. Then, it is necessary to know the application route for these protective strips 206, that is, the order of the multiple protective strips 206 and which of the two endpoints each protective strip 206 starts from and the other endpoint accordingly.

[0020] Figure 2 An example of a protective strip layout generated based on the layout of device 203 on circuit board 202 is illustrated schematically. Device 203 is exemplarily represented by dashed squares and dashed circles, and only one of device 203 is labeled with reference numerals. It is conceivable that the route generation device 201 automatically determines the layout of device 203 on circuit board 202 based on a top view image of circuit board assembly 204 and automatically generates the corresponding protective strip layout accordingly. Protective strip 206 is represented by a solid square and should be understood that, for example, protective strip 206, as indicated by reference numerals, is generated when the applicator head 205 moves straight, for example, from endpoint 1 to endpoint 2 of protective strip 206. Protective strip 206 may, for example, have a constant width and may only have horizontal (e.g., endpoints 1, 2) and vertical (e.g., endpoints 5, 6) protective strips 206, thereby simplifying the generation of the protective strip layout.

[0021] With the protective strip layout already determined, it is especially important to quickly find a coating route that best meets the requirements.

[0022] In this application, a genetic algorithm is used to generate coating routes. For genetic algorithms, defining the individuals and genes is crucial. For the specific scenario of coating protective strips 206, in this application, the individuals and genes of the genetic algorithm are defined as follows: the two endpoints of each of the plurality of protective strips 206 are marked differently (all endpoints are marked differently), each individual in the population contains the marks of all endpoints of all protective strips and represents a potential coating route for the plurality of protective strips in the order of the marks. A pair of marks from the two endpoints of each protective strip forms a gene for each individual. Here, because each protective strip is coated only once in the potential coating route, each individual in the population contains all endpoints of all protective strips exactly once. The potential coating route represented by the individual is specifically a coating route generated by connecting the corresponding endpoints of the protective strips to each other with line segments according to the order of the individual's marks.

[0023] exist Figure 2 For example, each pair of endpoints of the protection strip 206 is identified by a numerical designation, specifically a series of consecutive numbers starting from 1. If there are n protection strips, one endpoint of the first protection strip 206 is identified as 1 and the other endpoint as 2, and so on, with one endpoint of the nth protection strip 206 being identified as 2n-1 and the other endpoint as 2n. Corresponding to... Figure 2 There are a total of five protective strips 206, and the endpoints of the protective strips 206 are identified by numbers 1 to 10. In the initial identification, the order of the protective strips 206 and their corresponding endpoints can be arbitrary.

[0024] But the signage is clearly not limited to Figure 2 It can be any identifier that starts with 1, but can also be any other number, letter, or binary code, and its main function is to mark and distinguish all endpoints.

[0025] Figure 3 An example is shown based on Figure 2 The four individuals were generated based on the identifier. Corresponding to... Figure 2 The five protective bars 206 in each individual include five genes. Each gene includes a pair of identifiers at the two ends of a protective bar 206 and is enclosed in parentheses. Taking the second individual as an example, the potential smearing routes represented by the second individual (3,4), (1,2), (5,6), (7,8), (9,10) are from 3 to 4, from 4 to 1, from 1 to 2, from 2 to 5, from 5 to 6, from 6 to 7, from 7 to 8, from 8 to 9, and from 9 to 10.

[0026] Figure 4An exemplary flow diagram of the method for generating coating paths according to this application is illustrated. Multiple protective strips 206 are applied to devices 203 on a circuit board 202 by a coating apparatus 200 according to the coating paths. Here, the coating paths are specifically two-dimensional coating paths parallel to the circuit board 202.

[0027] like Figure 4 As shown, the method includes the following steps:

[0028] In the initial population generation step 100, the two endpoints of each of the plurality of protective strips 206 are marked differently, and multiple different individuals are generated by changing the order of the markings.

[0029] Fitness assessment step 102, in which the fitness of each individual is assessed based on the potential application route characterized by each individual;

[0030] In step 104, individuals for reproduction are selected from the current population based on their fitness using a selection operator.

[0031] Crossover step 106 (see also the section on...) Figure 6 (Description of the process) In the crossover step 106, the individuals selected in the selection step 104 are paired for crossover. In the crossover, at least one gene in the same position of a pair of individuals is exchanged. If one or more new genes introduced into the individual after the exchange represent the same protection bar 206 as one or more old genes that have not been changed, then the one or more old genes are replaced with the corresponding gene in the gene that was introduced out of the individual, so that the individual generated after the replacement covers all protection bars 206.

[0032] Mutation step 108 (see also the section on...) Figure 7 (Description of the process), in the mutation step 108, the individuals newly generated in the crossover step 106 are mutated, the mutations include intergenetic mutations and / or intragenetic mutations, in which genes within an individual are swapped in position, and in which two of a pair of identifiers of genes within an individual are swapped in position.

[0033] Update step 110, in which the current population is updated based on individuals with high fitness among the individuals newly generated in mutation step 108;

[0034] In iteration step 112, the selected steps 104, 106, 108, and 110 will be iterated until the preset stopping condition is reached and the iteration is completed.

[0035] In route generation step 114, the individual with the highest fitness is selected from the individuals in the population generated when the iteration is completed, and a coating route is generated based on that individual.

[0036] Genetic algorithms can find a globally better solution or a globally better coating route within a limited time.

[0037] exist Figure 3 For example, the generated individuals do not include the preset identifiers of the starting point and the ending point.

[0038] However, in some cases, see Figure 2 The coating device 200 may always start from a preset total starting point (identifier 0) and / or end at a preset total ending point (identifier 11). In such cases, each individual may additionally include an identifier for the preset total starting point and / or an identifier for the preset total ending point, so that the represented potential coating route covers the preset total starting point and / or the preset total ending point.

[0039] Clearly, given the existence of a total starting point and / or a total ending point, each individual always begins with the identifier of the total starting point and / or ends with the identifier of the total ending point. Correspondingly, potential application routes also always begin with the total starting point and / or end with the total ending point. In fitness assessment step 102, fitness is assessed based on potential application routes that begin with the total starting point and / or end with the total ending point.

[0040] See Figure 2 In the case of identification by numerical code, for example, the preset total starting point is identified as 0, and the preset total ending point is identified as 2n+1 (n is the number of protection strips).

[0041] Figure 5 An example of multiple individuals generated in the initial population generation step 100 is illustrated. Here, each individual includes an identifier 0 for the overall starting point and an identifier 11 for the overall ending point.

[0042] According to an exemplary embodiment of this application, in the initial population generation step 100, individuals generated based on the nearest neighbor heuristic algorithm and combined with a random scattering suboptimal solution strategy are combined with randomly generated individuals to form an initial population.

[0043] See Figure 2 and Figure 5 For example, the nearest neighbor heuristic algorithm can be used to obtain... Figure 5 The first individual in the sequence is 0, (1,2), (3,4), (5,6), (7,8), (9,10), 11. For details, see [link to documentation]. Figure 2For the remaining protection bars 206, starting from the initial point 0, point 1 is closest to point 0, point 3 is closest to point 2, point 5 is closest to point 4, point 7 is closest to point 6, and point 9 is closest to point 8, thus obtaining the first individual. Based on the first individual, combining the random distribution suboptimal solution strategy can yield more suboptimal solutions (or locally optimal individuals). Here, it is assumed that the second individual 0, (3,4), (1,2), (5,6), (7,8), (9,10), 11 are obtained through the random distribution suboptimal solution strategy. In addition, several individuals are randomly generated, for example, here... Figure 5 The remaining four individuals are then combined to form the initial population. In the initial population, suboptimal solutions (in this case, the first and second individuals) constitute only a small portion, i.e., at least less than 50%, while random individuals (the remaining four individuals), or random solutions, constitute the majority. Introducing suboptimal solutions accelerates convergence, while the majority of random solutions provides sufficient diversity to prevent direct and rapid convergence to local suboptimal solutions.

[0044] According to an exemplary embodiment of this application, in the generated coating path, it is permissible for the distance between the end point of a protective strip 206 and the start point of the next protective strip 206 in relation to that coating path to be greater than the distance between the end point of that protective strip 206 and the start point of the nearest other protective strip 206 among all other protective strips 206. That is, the coating path generated in this application is not necessarily a solution obtained by the nearest neighbor heuristic algorithm.

[0045] According to an exemplary embodiment of this application, in the fitness evaluation step 102, fitness is evaluated based on the time it takes for the coating device 200 to achieve the potential coating path represented by each individual; the shorter the time, the higher the fitness. Since the coating device 200 may not move at a constant speed, evaluating fitness based on time is more accurate. For example, it is conceivable, for instance, to use the reciprocal of time as fitness, so that the shorter the time, the higher the fitness.

[0046] Alternatively, in fitness assessment step 102, fitness can also be assessed based on the length of the potential application path represented by each individual; the shorter the length, the higher the fitness.

[0047] According to an exemplary embodiment of this application, in the fitness evaluation step 102, the potential coating routes characterized by each individual are first modified based on a preset rule for avoiding ultra-tall devices (devices 203 that would conflict with the coating head 205 based on their height) in the device 203, and then the fitness of each individual is evaluated based on the modified potential coating routes. The concept of avoiding ultra-tall devices is disclosed in the applicant's Chinese application No. 2024111190639, entitled "Method for Generating Coating Routes, Computer Program Product, Route Generation Apparatus, and Coating Equipment". The entire contents of that application are incorporated herein by reference.

[0048] Alternatively, it is conceivable to evaluate fitness directly based on the original potential coating path without considering modifications. Furthermore, alternative rules or additions to the rules for avoiding ultra-high-performance devices, in the presence of other modification rules, can be used to first modify the potential coating path characterized by the individual according to the corresponding rules, and then evaluate fitness based on the modified potential coating path.

[0049] According to an exemplary embodiment of this application, in the selection step 104, a tournament selection operator is employed. For simplicity, the tournament size of the tournament selection operator is two individuals. It is conceivable that each time two individuals are randomly selected from the current population, and the individual with higher fitness wins. The initial population size is m (in... Figure 5 In the case of m=6), m competitions can be held accordingly, and m individuals can be selected for crossover step 106. However, it is also conceivable that the scale of the competitions is more than two; and / or, fewer or more than m tournaments can be held, thereby selecting fewer or more than m individuals for crossover step 106.

[0050] Instead of tournament selection operators, alternatives could include roulette wheel selection operators, ranking selection operators, random selection operators, etc.

[0051] Figure 6 An example of crossover step 106 is illustrated schematically. Here, for ease of observation and understanding, it is compared with... Figure 3 and Figure 5 The different genes of an individual are displayed in separate rows. Genes that are about to change are highlighted with dashed boxes, while genes that have already changed are indicated in bold.

[0052] According to an exemplary embodiment of this application, such as Figure 6 As shown, in the crossover, a string of genes at the same position in the pair of individuals is randomly selected for exchange. Alternatively, or additionally, single-point or multi-point crossovers with fixed positions can also be conceived. A string of genes is specifically understood as at least two genes that are adjacent to each other.

[0053] by Figure 6 For example, the leftmost pair is used for crossing, which corresponds to Figure 5 The first and fourth individuals in the pair are shown. The individual on the left in a pair is called the father, and the individual on the right is called the mother. A randomly selected sequence of genes is outlined in the dashed box, namely the father's genes (5,6)(7,8) and the mother's genes (1,2)(5,6). The individuals generated after crossover are shown in the middle. For the father generated after crossover, the (1,2) in the newly introduced gene (1,2)(5,6), indicated in bold, conflicts with the unchanged old gene (1,2), representing the same protection bar 206. Here, the conflicting old gene (1,2) of the father can be replaced with (7,8) in the father's substituted genes (5,6)(7,8), while the newly introduced gene (5,6) of the father does not conflict and therefore does not require processing. For the parent generated after crossover, the newly introduced gene (7,8) represents the same protective strip as the old gene (8,7). Therefore, the old gene (8,7) of the parent is replaced with (1,2) from the parent's replaced genes (1,2)(5,6). Through the above replacement, the two rightmost individuals obtained can both cover all protective strips 206.

[0054] Figure 7 An example of mutation step 108 is illustrated schematically. Figure 6 Similarly, dashed boxes are used to outline genes that are about to change, and bold text is used to indicate genes that have already changed.

[0055] According to an exemplary embodiment of this application, see Figure 7 In this variation, two genes within an individual are randomly swapped and / or the identifiers of a string of genes within an individual are randomly reversed. Alternatively, it is conceivable to randomly swap the positions of more than one or more pairs of genes within an individual.

[0056] by Figure 7 For example, the leftmost figure shows the newly generated individual in crossover step 106. First, the positions of two genes (7,8) and (9,10) within the individual are randomly swapped to obtain the middle individual; this can also be considered as inter-gene variation. Then, the identifiers of a string of genes within the individual are randomly reversed; in this case, the identifiers of three genes (3,4)(1,2)(5,6) are completely reversed to (6,5)(2,1)(4,3). Reversal can also be considered as a combination of inter-gene variation and intra-gene variation.

[0057] According to an exemplary embodiment of this application, the update step 110 includes a replacement step, in which a new population is generated by replacing individuals with low fitness in the current population with individuals with high fitness from the newly generated individuals in the mutation step 108. This can improve the speed of the algorithm. However, depending on the need, the update step 110 may also be replaced by or supplemented by other forms of updates. For example, individuals with high fitness from the newly generated individuals may be used to expand the current population, or similar methods may be used.

[0058] According to an exemplary embodiment of this application, the stopping condition in the iterative step 112 is preset based on the time limit for generating the coating route.

[0059] According to an exemplary embodiment of this application, in the route generation step 114, a coating route is first generated based on the identifier of the selected individual, and then the coating route is modified based on a preset rule for avoiding ultra-high devices in the device 203 to generate the final coating route.

[0060] In the context, "multiple" is especially understood as at least two.

[0061] Where technically feasible, the proposed features can be viewed individually and combined with each other in any way without exceeding the scope of this application.

[0062] The various concepts in this application can be understood, in particular, within the scope of genetic algorithms, and at least some of the steps can be implemented using neural networks.

[0063] In the accompanying drawings, for the sake of brevity, for multiple elements of the same kind or function, sometimes only one of them is marked with the figure reference numeral.

[0064] The elements in the accompanying drawings, especially the number, position, and interrelationship of the protective strips, are merely examples and do not constitute any limitation on this application.

[0065] Although specific embodiments of this application are described in detail herein, they are given for illustrative purposes only and should not be construed as limiting the scope of this application. Various substitutions, modifications, and alterations can be conceived without departing from the spirit and scope of this application.

[0066] List of reference numerals

[0067] 100 Initial Population Generation Steps

[0068] 102 Fitness Assessment Steps

[0069] 104 Selection Steps

[0070] 106 Cross Steps

[0071] 108 Mutation Steps

[0072] 110 Update Steps

[0073] 112 Iteration Steps

[0074] 114 Route Generation Steps

[0075] 200 Coating Device

[0076] 201 Route Generation Device

[0077] 202 Circuit Board

[0078] 203 Devices

[0079] 204 Circuit Board Assembly

[0080] 205 Application Head

[0081] 206 Protective strip.

Claims

1. A method for generating coating paths, wherein a coating apparatus (200) applies a plurality of protective strips (206) to devices (203) on a circuit board (202) according to the coating paths, characterized in that, The coating route is generated based on a genetic algorithm. In the genetic algorithm, the two endpoints of each of the multiple protective strips (206) are marked with different identifiers. Each individual in the population contains the identifiers of all endpoints of all protective strips (206) and represents a potential coating route of the multiple protective strips (206) in the order of the identifiers. A pair of identifiers of the two endpoints of each protective strip (206) forms a gene of the individual.

2. The method for generating coating routes according to claim 1, characterized in that, The method includes the following steps: In the initial population generation step (100), the two ends of each of the plurality of protective strips (206) are marked differently, and multiple different individuals are generated by changing the order of the markings. Fitness assessment step (102), in which the fitness of each individual is assessed based on the potential application route characterized by each individual; In the selection step (104), individuals for reproduction are selected from the current population based on their fitness using a selection operator. In the crossover step (106), individuals selected in the selection step (104) are paired and crossovered. In the crossover, at least one gene in the same position of a pair of individuals is exchanged. If one or more new genes introduced into the individual after the exchange represent the same protection strip (206) as one or more old genes that have not been changed, then the one or more old genes are replaced with the corresponding genes in the genes that were introduced out of the individual, so that the individual generated after the replacement covers all protection strips (206). The mutation step (108) involves mutating the individuals newly generated in the crossover step (106). The mutation includes intergenetic mutation and / or intragenetic mutation. In the intergenetic mutation, the genes within an individual are swapped. In the intragenetic mutation, two of a pair of identifiers of a gene within an individual are swapped. Update step (110), in which the current population is updated based on individuals with high fitness among the individuals newly generated in mutation step (108); In the iteration step (112), the selection step (104), the crossover step (106), the mutation step (108) and the update step (110) are iterated until the preset stopping condition is reached and the iteration is completed. In the route generation step (114), the individual with the highest fitness is selected from the individuals of the population generated when the iteration is completed, and a coating route is generated based on that individual.

3. The method for generating coating routes according to claim 1 or 2, characterized in that, In the generated coating path, it is permissible for the end point of a protective strip (206) to be at a distance greater than the starting point of the next protective strip (206) in relation to the coating path. The end point of the protective strip (206) is also permissible as to the starting point of the nearest protective strip (206) among all other protective strips (206).

4. The method for generating coating routes according to claim 1 or 2, characterized in that, The method includes at least one of the following features: The identifier is a number, and each of the two endpoints of the plurality of protective strips (206) is identified by consecutive numbers starting from 1. When there are n protective strips (206), the identifier of one endpoint of the first protective strip (206) is 1 and the identifier of the other endpoint is 2, and so on, the identifier of one endpoint of the nth protective strip (206) is 2n-1 and the identifier of the other endpoint is 2n. Each individual additionally includes a preset total starting point identifier and / or a preset total ending point identifier, such that the represented potential coating route covers the preset total starting point and / or the preset total ending point identifier, wherein the total starting point identifier is in particular 0, and the preset total ending point identifier is in particular 2n+1 when the plurality of protection strips (206) are n protection strips (206).

5. The method for generating coating routes according to claim 2, characterized in that, In the initial population generation step (100), individuals generated based on the nearest neighbor heuristic algorithm and combined with the random scattering suboptimal solution strategy are combined with randomly generated individuals to form the initial population.

6. The method for generating coating routes according to claim 2, characterized in that, In the fitness assessment step (102), fitness is assessed based on the time it takes for the coating device (200) to achieve the potential coating route represented by each individual; the shorter the time, the higher the fitness. or In the fitness assessment step (102), fitness is assessed based on the length of the potential coating path represented by each individual; the shorter the length, the higher the fitness.

7. The method for generating coating routes according to claim 2, characterized in that, In the fitness evaluation step (102), the potential coating path represented by each individual is first modified based on the preset rules for avoiding ultra-high devices in the device (203), and then the fitness of each individual is evaluated based on the modified potential coating path.

8. The method for generating coating routes according to claim 2, characterized in that, In the selection step (104), a tournament selection operator is employed; the tournament size of the tournament selection operator is specifically two individuals.

9. The method for generating coating routes according to claim 2, characterized in that, The method includes at least one of the following features: In the crossover, a string of genes at the same position in the pair of individuals is randomly selected and interchanged; In the aforementioned mutations, the positions of two genes within an individual are randomly swapped and / or the identifiers of a string of genes within an individual are randomly reversed.

10. The method for generating coating routes according to claim 2, characterized in that, The update step (110) includes a replacement step in which a new population is generated by replacing individuals with low fitness in the current population with individuals with high fitness from the newly generated individuals in the mutation step (108).

11. The method for generating coating routes according to claim 2, characterized in that, The stopping condition in the iterative step (112) is preset based on the time limit for generating the coating route.

12. The method for generating coating paths according to claim 1 or 2, characterized in that, The method includes at least one of the following features: The coating path is a two-dimensional coating path parallel to the circuit board (202); The potential coating path represented by an individual is a coating path generated by connecting the corresponding endpoints of the protective strip (206) to each other with line segments in the order of the individual's identification. The method includes a protective strip layout generation step, in which the layout of a plurality of protective strips (206) to be applied is automatically generated based on the layout of the device (203) on the circuit board (202), and in particular, the layout of the device (203) on the circuit board (202) is determined based on a top view image of the circuit board (202) and the device (203) thereon.

13. A computer program product, characterized in that, It includes computer program instructions, which, when executed by one or more processors, enable the processors to perform the method for generating coating routes according to any one of claims 1 to 12.

14. A route generation device, characterized in that, The route generation apparatus (201) includes a processor and a memory, the memory storing computer program instructions, which, when executed by the processor, enable the processor to perform a method for generating a coating route according to any one of claims 1 to 12.

15. A coating apparatus, characterized in that, The coating equipment includes a coating device (200) for coating the protective strip (206) and a route generation device (201) according to claim 14.

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