Production data creation device and production data creation method

Abstract

To provide a production data creation device capable of easily setting optimal operating parameters for each substrate application, and a production data creation method.SOLUTION: The production data creation device includes: an input unit that receives inputs of input parameters based on at least the quality and the productivity; and a setting unit that sets operating parameters for component mounting equipment that mounts a component onto a substrate based on the input parameters. The input unit further receives an input of shape information of the component. The setting unit sets operating parameters corresponding to the input shape information of the component and the input parameters, from at least the shape information of the component, the input parameters, and a rules table associated with the operating parameters.SELECTED DRAWING: Figure 9

Description

[Technical field]

[0001] The present disclosure relates to a production data creation device and a production data creation method that create production data for a component mounting device to mount components on a board. [Background technology]

[0002] In a component mounting device that mounts components on a board, component mounting operations are controlled based on operation parameters including many parameters such as parameters related to component suction by a nozzle, parameters related to component shape recognition, and parameters related to component mounting on a board. Appropriate values ​​for these operation parameters must be set for each component. Patent Document 1 describes that parameters such as appropriate operating acceleration of a head are calculated based on the ratio between an inputted mass of a component and an area of ​​a suction hole of a nozzle that picks up the component. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2012-156200 A Summary of the Invention [Problem to be solved by the invention]

[0004] The production data creation device of the present disclosure includes an input unit and a setting unit.

[0005] The input unit further receives input of shape information of the part.

[0006] The setting unit sets the operation parameters corresponding to the inputted shape information of the part and the inputted input parameters from a rule table that associates at least the shape information of the part, the input parameters, and the operation parameters.

[0007] The production data creation method disclosed herein includes accepting input of input parameters based on at least quality and productivity, and setting operating parameters for a component mounting device to mount components on a board based on the input parameters, and further accepting input of component shape information, and setting operating parameters corresponding to the input component shape information and the input input parameters based on a rule table that associates at least the component shape information, the input parameters, and the operating parameters.

[0008] A production data creation device according to another aspect of the present disclosure includes an input unit and a setting unit.

[0009] The input unit further receives input of shape information of the part.

[0010] The setting unit sets the operation parameters corresponding to the inputted shape information of the part and the inputted input parameters from a learning model in which at least the shape information of the part, the input parameters, and the operation parameters are associated with each other.

[0011] A production data creation method of another aspect of the present disclosure includes accepting input of input parameters based on at least quality and productivity, and setting operating parameters for a component mounting device to mount components on a board based on the input parameters, and further accepting input of component shape information, and setting operating parameters corresponding to the input component shape information and the input input parameters from a learning model that associates at least the component shape information, the input parameters, and the operating parameters. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram illustrating the configuration of a component mounting system according to an embodiment. [Diagram 2] FIG. 2 is a block diagram showing the configuration of a processing system of a management computer (production data generating device) according to an embodiment. [Diagram 3] FIG. 3 is a diagram illustrating the configuration of production data used in the component mounting system according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating the configuration of component data used in the component mounting system according to the embodiment. [Diagram 5] FIG. 5 is a diagram showing an example of a use selection screen in the management computer (production data creation device) according to the embodiment. [Figure 6] FIG. 6 is a diagram showing an example of a part shape input screen in the management computer (production data creation device) according to the embodiment. [Figure 7] FIG. 7 is a flow diagram of the first production data creating method according to the embodiment. [Figure 8] FIG. 8 is a diagram showing an example of an input parameter input screen in the management computer (production data generating device) according to the embodiment. [Figure 9] FIG. 9 is a flow diagram of the second production data creating method according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Even when mounting the same parts, the optimal part mounting operation differs depending on whether the production model is an in-vehicle device board that prioritizes quality or a communication device board that prioritizes productivity. Therefore, it is desired to prepare optimal operation parameters according to the use of the board. However, in the conventional techniques including Patent Document 1, it is not possible to automatically generate operation parameters that take into account the use of the board, and workers change the operation parameters based on a set of operation parameters calculated for each part, based on their experience, and the quality of the operation parameters varies depending on the worker who creates them.

[0014] An embodiment of the present disclosure will be described with reference to the drawings. First, the configuration of a component mounting system 1 will be described with reference to FIG. 1. The component mounting system 1 has a function of mounting components on a board to produce a mounted board. In this embodiment, a configuration is adopted in which a plurality of (here, three) component mounting lines 4 are connected to a management computer 3 via a communication network 2. Work on the component mounting lines 4 is managed by the management computer 3. Note that the number of component mounting lines 4 is not limited to three, and may be one, two, or five or more.

[0015] The management computer 3 has a function of transmitting data necessary for the operation of the production equipment (component mounting devices M4, M5) equipped on the component mounting line 4 to the production equipment. In addition, data such as the operation status and work history of the production equipment is transmitted from the production equipment to the management computer 3. Note that the component mounting system 1 may include a line management computer for each component mounting line 4, and the management computer 3 and the production equipment may transmit and receive data via the line management computers. In addition, the management computer 3 has a function of creating operation parameters, component data, production data, etc. used in the production equipment of the component mounting line 4.

[0016] 1, component mounting line 4 is configured by connecting board supply device M1, board transfer device M2, solder printing device M3, component mounting devices M4 and M5, reflow device M6, and board removal device M7. Boards supplied by board supply device M1 are carried into solder printing device M3 via board transfer device M2. Solder printing device M3 performs a solder printing operation in which solder for joining components is screen-printed on the board.

[0017] The boards after solder printing are sequentially handed over to component mounting devices M4 and M5. The component mounting devices M4 and M5 perform a component mounting operation to mount components on the boards after solder printing. The component mounting devices M4 and M5 use a nozzle on the mounting head to pick up the components supplied by the feeder by vacuum suction, capture an image of the state of the components held by the nozzle with a component recognition camera, and mount the components at a specified mounting angle on the mounting position on the board. The component mounting devices M4 and M5 are equipped with multiple sensors to monitor operational mistakes and operational errors during component mounting operations, such as the suction operation in which the nozzle picks up the components and the component recognition operation in which the component recognition camera captures and recognizes the picked-up components.

[0018] After mounting the components, the board is carried into the reflow device M6. In the reflow device M6, the board is heated according to a specified heating profile, causing the solder used to join the components to melt and solidify. This results in the components being solder-joined to the board, completing the mounting board with the components mounted on the board, which is then collected by the board collection device M7.

[0019] Next, the configuration of the processing system of the management computer 3 will be described with reference to Fig. 2. Here, the configuration related to the function of creating operation parameters, component data, and production data used in component mounting work by the component mounting devices M4 and M5 will be described, among the multiple functions provided in the management computer 3. The management computer 3 includes a processing unit 10, a production information storage unit 15 which is a storage device, a production history storage unit 21, an input unit 23, a display unit 24, and a communication unit 25.

[0020] The processing unit 10 is a data processing device such as a CPU (Central Processing Unit), and includes an input processing unit 11, a first setting unit 12, a second setting unit 13, and a performance acquisition unit 14 as internal processing units. The management computer 3 does not need to be configured as a single computer, but may be configured as multiple devices. For example, all or part of the storage device and processing unit may be provided in a cloud via a server. Moreover, the processing unit 10 does not need to include both the first setting unit 12 and the second setting unit 13, but may include only one of them.

[0021] The input unit 23 is an input device such as a keyboard, a touch panel, a mouse, etc., and is used when inputting operation commands and data. The display unit 24 is a display device such as a liquid crystal panel, and in addition to displaying various data stored in the memory unit, displays various information such as an operation screen and an input screen for operation by the input unit 23. The communication unit 25 is a communication interface, and transmits and receives data to and from the production equipment (component mounting devices M4, M5) that constitute the component mounting line 4 via the communication network 2.

[0022] 2, production information storage unit 15 stores a production data library 16, a component library 17, an operation parameter library 18, a rule table 19, a learning model 20, etc. In production data library 16, production data used in the production of mounted boards by component mounting devices M4 and M5 is stored for each production model name of the mounted board.

[0023] 3, an example of production data 30 included in the production data library 16 will be described. Each of the multiple production data 30 included in the production data library 16 specifies data required to produce a mounting board for one production model name. That is, the production data 30 specifies, for each component to be mounted, a "component name" 31 of the component to be mounted on the mounting board for the production model name, a component code 32 for relating the component to component data in the component library 17, and a "mounting coordinate" 33 and a "mounting angle" 34 indicating the mounting position and mounting angle of the component on the mounting board, respectively.

[0024] Furthermore, the production data 30 specifies, for each component name, equipment condition data 35 indicating the conditions of the equipment used in the production of the mounted board, i.e., the setting state of the component mounting devices M4, M5. In the example shown here, the equipment condition data 35 is included in the production data 30 provided via the communication network 2. However, it is also possible to provide only the equipment condition data 35 in the form of a separate file.

[0025] The following data on component mounting devices M4 and M5 is specified as equipment condition data 35. Specifically, a "supply position" 36 indicating the position where components are supplied, a "feeder" 37 indicating the feeder used to supply components, a "mounting head" 38 indicating the mounting head that performs the component mounting work to mount components, a "nozzle" 39 indicating the nozzle used to hold components, etc. are specified.

[0026] 2, component library 17 stores a plurality of component data items that associate the type of component with operation parameters for precisely controlling various operations for mounting the components in component mounting devices M4 and M5. The component data items are associated with production data 30 by component codes 32. That is, even for components with the same component name, component library 17 stores different component data items that correspond to the mounting positions of the production model names of the mounted boards to be produced. Note that, even if the production model names and mounting positions are different, common component data items are used if the operation parameters are the same.

[0027] 4, an example of part data 40 contained in the part library 17 will be described. The part data 40 is associated with the production data 30 by the part code 32.

[0028] The part data 40 is composed of a shape diagram 42, size data 43, part parameters 44, and operation parameters 47. Images, values, terms, etc. are entered in the blank spaces for each item. Note that the "values" used here are not limited to numerical data, but also include the selection results of options expressed quantitatively and qualitatively, such as yes / no, cheap / expensive, high / medium / low speed, etc. The shape diagram 42 illustrates the external shape of the target part. The size data 43 indicates the size information of the part, i.e., the external dimensions, number of leads, lead pitch, lead length, lead width, part height, etc., as numerical data.

[0029] The part parameters 44 are attribute information about the parts, and include part information 45, which is information about the parts themselves, and tape information 46, which is information about the carrier tape for feeding the parts by a feeder. The part information 45 indicates the polarity, polarity mark, mark position, part type, shape type, and price information of the part. The tape information 46 includes the tape material of the carrier tape, the tape width indicating the width dimension of the carrier tape, the feed interval indicating the tape feed pitch, and color and material information, which is information related to the characteristics when the carrier tape is the subject of image recognition.

[0030] The operation parameters 47 are machine parameters that define the operation mode when a component is to be mounted by the component mounting devices M4 and M5. In the example shown here, the operation parameters 47 include a model 47a indicating the type of the component mounting devices M4 and M5, and a nozzle setting 47b indicating the type of nozzle to be used. Furthermore, the operation parameters 47 include a speed parameter 47c, a recognition parameter 47d, a gap 47e, a pickup parameter 47f, and a placement parameter 47g.

[0031] The speed parameters 47c include the pickup speed when the nozzle picks up the components, the mounting speed when the mounting head transfers the components, and the tape feed speed when the feeder feeds the carrier tape. In this embodiment, the pickup speed, mounting speed, and tape feed speed can be set as a percentage of the maximum speed between 100% and 20%. The recognition 47d is a parameter that specifies the mode of component recognition, and includes a camera type that indicates the type of component recognition camera used, an illumination mode that indicates the illumination form at the time of image capture, and a recognition speed that is the movement speed of the nozzle at the time of image capture. The recognition speed can be set to high speed, medium speed, or low speed. Note that the speed-related parameters may be numerical values ​​(1 to 100%) or options (high speed, medium speed, low speed, etc.).

[0032] Gap 47e includes the suction gap when the nozzle picks up a component and the mounting gap when the held component is mounted on the board. Suction 47f specifies the pickup position offset, which indicates the offset amount when the nozzle picks up a component, and the pickup angle. Placement 47g specifies the pressure load when the nozzle places the held component on the board.

[0033] In this way, the operation parameters 47 include nozzle parameters (nozzle settings 47b) related to the nozzle that picks up the component, pickup parameters related to pickup when the nozzle picks up the component (pickup speed, pickup gap, pickup 47f), recognition parameters (recognition 47d) for recognizing the shape of the component, mounting parameters for mounting the component (mounting speed, mounting gap, placement 47g), etc. Note that the component parameters 44 and operation parameters 47 shown in the component data 40 in Fig. 4 are examples of the relevant items, and various parameters other than the items shown here are set as necessary.

[0034] For example, parameters include the pickup hold time, which is the time the nozzle is in contact with the component when picking up a component; the mounting hold time, which is the time the component is in contact with the board when mounting it on the board; the component recognition count, which is the number of times a component is recognized by the recognition camera; pickup check ON / OFF, which determines whether a check is made to see if a component has been picked up; thickness variation tolerance, which sets the tolerance when measuring component thickness; component pickup status detection ON / OFF, which determines whether the component pickup status is detected; simultaneous component pickup and mounting ON / OFF, which determines whether components are picked up or mounted simultaneously; component pickup position automatic learning ON / OFF, which determines whether the component pickup position is automatically set; the component pickup retries, which determines the number of times pickup is attempted again when pickup has failed; and the number of recognition retries, which determines the number of times recognition is attempted again when recognition of a component cannot be performed.

[0035] 2, the operation parameter library 18 stores a plurality of operation parameter sets, which are a set of a plurality of parameters set as operation parameters 47 of the component data 40. The operation parameter sets include a recommended parameter set that can be used universally regardless of the type of component or the production model of the mounted board, and a plurality of operation parameter sets corresponding to the application of the mounted board, etc. The applications of the mounted board include an in-vehicle device board that emphasizes quality, a home appliance device board that balances quality and productivity, a communication device board that emphasizes productivity, an electronic device board that emphasizes cost, and a prototype board for the purpose of checking operation.

[0036] The production history storage unit 21 stores production history information 22 and the like. The production history information 22 stores performance values, such as the work history of the component mounting devices M4, M5 (production equipment) acquired by the performance acquisition unit 14, a pickup rate indicating the success rate of a pickup operation in which a nozzle picks up a component from a feeder, a recognition rate indicating the success rate of component recognition in which an image of the picked component is captured and recognized by a component recognition camera, and a missing rate indicating the proportion of components discarded due to work mistakes or operation errors among the supplied components.

[0037] In FIG. 2, the input processing unit 11 causes the display unit 24 to display various input screens for inputting various information for setting the operation parameters 47 from the input unit 23. Here, with reference to FIG. 5, an application selection screen 50 that the input processing unit 11 causes the display unit 24 to display will be described. A "part name" input box 51, a "application" selection box 52, and a "decide" button 53 are displayed on the application selection screen 50. A part name ("M8064") is inputted into the "part name" input box 51 by the input unit 23. In the "application" selection box 52, "automotive device board", "home appliance board", "communication device board", "electronic device board", and "prototype board" are displayed as options for the application of the mounting board to be produced, and an application is selected by selecting a displayed radio button 52a by the input unit 23.

[0038] Here, "home appliance board" is selected. When the "OK" button 53 is operated, the production model name and the selected application are input to the application selection screen 50. In this way, the input unit 23 accepts the input of one application from among the multiple applications displayed on the screen as options. The multiple applications include an in-vehicle device board, a home appliance board, a communication device board, an electronic device board, and a prototype board. Note that the terms that identify the multiple applications are not limited to the terms in-vehicle device board, home appliance board, communication device board, electronic device board, and prototype board, and may be other terms, symbols, illustrations, etc.

[0039] Next, a component shape input screen 54 that the input processing unit 11 causes to be displayed on the display unit 24 will be described with reference to Fig. 6. The component shape input screen 54 is a screen display for inputting size data 43 of the component data 40. A "component name" input box 55, a "component shape" input box 56, and a "OK" button 57 are displayed on the component shape input screen 54. The name of the component to be mounted on the mounting board ("M8064") is input by the input unit 23 into the "component name" input box 55.

[0040] In the "Part Shape" input frame 56, the size data 43, such as the external dimensions, number of leads, lead pitch, lead length, lead width, part height, part type, shape type, etc., are input by the input unit 23. The "Part Shape" input frame 56 is scrolled up and down using a scroll bar 56a. When the "OK" button 57 is operated, the part name and part shape information (size data 43) input in the part shape input screen 54 are input. In this way, the input unit 23 accepts the input of part shape information.

[0041] 2, the first setting unit 12 sets operation parameters 47 corresponding to the component shape information and the application of the mounting board input by the input unit 23, based on the rule table 19 or learning model 20 stored in the production information storage unit 15. The rule table 19 associates the component shape information (size data 43), the application of the mounting board, operation parameters 47, etc., and sets the operation parameters 47 corresponding to the component shape information and the application of the mounting board from the operation parameter set in the operation parameter library 18.

[0042] When creating component data 40 for a component whose use is a home appliance board input on use selection screen 50 in Fig. 5 and whose component name is "M8064" input on component shape input screen 54 in Fig. 6, first setting unit 12 sets operation parameter 47 from the operation parameter set for home appliance boards stored in operation parameter library 18 in accordance with rule table 19. For example, in the case of suction gap, which is operation parameter 47, first setting unit 12 sets a parameter calculated in accordance with the rules specified in rule table 19 for the suction gap in the operation parameter set for home appliance boards, using the component height, which is the input component shape, as a variable.

[0043] 2, the learning model 20 is a trained model that has been trained by associating component shape information (size data 43), the use of the mounting board, and operation parameters 47. The learning model 20 estimates the operation parameters 47 from an operation parameter set in an operation parameter library 18 that corresponds to the use of the mounting board, component shape information, production history information 22, and the like.

[0044] For example, when creating component data 40 for a component with a component name of "M8064", first setting unit 12 sets operation parameters 47 that make the pickup rate higher than a predetermined value and the pickup speed higher than a predetermined value, using an operation parameter set for a home appliance board, component shape information, and production history information 22 as variables, in accordance with learning model 20. That is, first setting unit 12 sets operation parameters 47 that correspond to the component shape information input from learning model 20 and the application of the mounting board. Component data 40 created by first setting unit 12 is stored in component library 17.

[0045] More specifically, some of the values ​​set in the rule table 19 or learning model 20 for each application of the component data 40 "M8064" will be explained. As the speed parameter 47c of the recommended parameter set, the pickup speed, mounting speed, and tape feed speed are set to 100%, which is the maximum speed. Also, as the recognition 47d, the recognition speed is set to high speed. Next, the operation parameters 47 set in the operation parameter set for in-vehicle equipment boards will be explained. For in-vehicle equipment boards, production with higher accuracy (emphasis on quality) than the recommended parameter set is required. Therefore, the pickup speed, mounting speed, and tape feed speed are set to 60%. Also, as the recognition 47d, the recognition speed is set to medium speed.

[0046] Next, the operation parameters 47 set in the operation parameter set for home appliance boards will be explained. For home appliance boards, production that emphasizes a good balance between quality and productivity is required. Therefore, the pickup speed, mounting speed, and tape feed speed are set to 80%. Furthermore, for recognition 47d, the recognition speed is set to medium speed. Next, for communication device boards, production that is more productive (emphasis on productivity) than the recommended parameter set is required. Therefore, the pickup speed, mounting speed, and tape feed speed are set to 90%. Furthermore, for recognition 47d, the recognition speed is set to high speed.

[0047] Next, for electronic device boards, even higher productivity (higher emphasis on productivity) is required than the operation parameters 47 set in the operation parameter set for communication device boards. Therefore, the pickup speed, mounting speed, and tape feed speed are set to 100%. Also, for recognition 47d, the recognition speed is set to high speed. Next, for prototype boards, since the creation of the board is prioritized, more emphasis on quality (higher emphasis on quality) is required than for in-vehicle device boards. Therefore, the pickup speed, mounting speed, and tape feed speed are set to 40%. Also, for recognition 47d, the recognition speed is set to low speed. Note that the above-mentioned operation parameters are an example in "M8064", and the values ​​set by the operation parameter set, rule table 19, or learning model 20 differ depending on the part.

[0048] Note that the rule table 19 and the learning model 20 may include weighting information to be applied to each parameter of the recommended parameter set included in the operation parameter library 18 for each application of the mounting board, instead of information associating the input application of the mounting board with the operation parameter set corresponding to the application of the mounting board included in the operation parameter library 18. In this case, the first setting unit 12 sets the operation parameters 47 by executing the above-mentioned process using the operation parameter set corresponding to the application of the mounting board, based on the weighting information corresponding to the input application of the mounting board and the recommended parameter set.

[0049] In this way, the management computer 3 is a production data creation device that includes an input unit 23 that receives input of one of a plurality of uses displayed on the screen as options (use selection screen 50), and a first setting unit 12 that sets operation parameters 47 for the component mounting devices M4 and M5 to mount components on the board based on the input use. This makes it possible to easily set the optimum operation parameters 47 according to the use of the board.

[0050] Next, the first production data creation method in the management computer 3 (production data creation device) will be described with reference to the flow of Fig. 7. First, the input of one of a plurality of uses displayed on the screen as options (use selection screen 50) is accepted using the input unit 23 (ST1: use selection step). Next, the input of part shape information is accepted from the screen display (part shape input screen 54) using the input unit 23 (ST2: part shape input step).

[0051] Next, the first setting unit 12 sets the operation parameters 47 corresponding to the inputted shape information of the component and the inputted use from the rule table 19 that associates the shape information of the component, the use of the mounting board, and the operation parameters 47 (ST3: first operation parameter setting step). Alternatively, the first setting unit 12 sets the operation parameters 47 corresponding to the inputted shape information of the component and the inputted use from the learning model 20 that associates the shape information of the component, the use of the mounting board, and the operation parameters 47.

[0052] Next, a second example of the present embodiment will be described. The second example is different from the above-mentioned example in that the operating parameters 47 are set based on the input target characteristics (input parameters), in that the operating parameters 47 are set based on the application of the selected mounting board. Hereinafter, the same components as those in the above-mentioned example are given the same reference numerals, and detailed description will be omitted. First, with reference to FIG. 8, an input parameter input screen 58 displayed on the display unit 24 by the input processing unit 11 will be described. On the input parameter input screen 58, a "production model name" input frame 59, an "input parameter" input frame 60, and a "decide" button 61 are displayed. In the "part name" input frame 59, the part name ("M8064") is input by the input unit 23.

[0053] The "Input Parameter" input frame 60 displays a slider 60a for inputting the ratio of the input parameters "quality" and "productivity", and the input parameters are input by operating the slider 60a via the input unit 23. Here, the positions of 75% for "quality" and 25% for "productivity" are specified by the slider 60a. When the "Enter" button 61 is operated, the production model name and the values ​​of the input parameters inputted into the input parameter input screen 58 are inputted. In this way, the input unit 23 accepts the input of input parameters based on at least quality and productivity.

[0054] The input parameters are not limited to quality and productivity, and may be, for example, mounting accuracy and cost. The number of input parameters is not limited to two, and may be one or three or more. The values ​​of the input parameters are not limited to the ratio of two parameters, and may be the absolute values ​​of each parameter.

[0055] 2, the second setting unit 13 sets operation parameters 47 based on the input parameters input by the input unit 23, based on the rule table 19 or the learning model 20 stored in the production information storage unit 15. The rule table 19 associates part shape information (size data 43), the input parameters, the operation parameters 47, and the like, and specifies rules for estimating the operation parameters 47 corresponding to the part shape information and the input parameters from the recommended parameter set in the operation parameter library 18.

[0056] When creating part data 40 for a part with a part name "M8064" and input parameters (quality 75%, productivity 25%) entered on input parameter input screen 58 in FIG. 8, second setting unit 13 identifies operation parameters 47 from the recommended parameter set stored in operation parameter library 18 in accordance with quality-based rule table 19 and productivity-based rule table 19, and sets operation parameters 47 weighted (weighted average) according to the input parameters.

[0057] For example, in the case of the mounting speed, which is an operational parameter 47, the second setting unit 13 sets a parameter calculated for the mounting speed of the recommended parameter set according to the weighting rules specified in the rule table 19, using the input parameters as variables. In this case, since the production model places more importance on quality than on productivity, the mounting speed is set to a value slower than that of the recommended parameter set.

[0058] The learning model 20 corresponds component shape information (size data 43), input parameters, and operational parameters 47, and is a model that estimates the operational parameters 47 from the recommended parameter set in the operational parameter library 18 corresponding to the application of the mounting board, the component shape information, the input parameters, and the production history information 22.

[0059] For example, when creating component data 40 for a component with a component name of "M8064", second setting unit 12 sets operation parameters 47 in accordance with learning model 20 such that the mounting load is smaller than a predetermined value and the defect rate is smaller than a predetermined value, using the recommended parameter set, component shape information, input parameters, and production history information 22 as variables. That is, second setting unit 13 sets operation parameters 47 corresponding to the component shape information and input parameters input from learning model 20. Component data 40 created by second setting unit 13 is stored in component library 17.

[0060] In this way, the management computer 3 of the second embodiment is a production data creation device that includes an input unit 23 that accepts input of input parameters based on at least quality and productivity from a screen display (input parameter input screen 58), and a second setting unit 13 that sets operation parameters 47 for component mounting devices M4 and M5 to mount components on a board based on the input parameters. This makes it possible to easily set optimal operation parameters 47 according to the target characteristics of the board.

[0061] Next, the second production data creation method in the management computer 3 (production data creation device) of the second embodiment will be described along the flow of Fig. 9. Hereinafter, the same steps as those in the first production data creation method are given the same reference numerals and detailed description will be omitted. First, using the input unit 23, input of input parameters based on at least quality and productivity is accepted from the screen display (input parameter input screen 58) (ST11: input parameter input step). Next, the part shape input step (ST2) is executed.

[0062] Next, the second setting unit 13 sets the operation parameters 47 corresponding to the input shape information of the part and the input parameters from the rule table 19 that associates the shape information of the part with the input parameters and the operation parameters 47 (ST12: second operation parameter setting step). Alternatively, the second setting unit 12 sets the operation parameters 47 corresponding to the input shape information of the part and the input parameters from the learning model 20 that associates the shape information of the part with the input parameters and the operation parameters 47.

[0063] The present invention has been described above based on the present embodiment. Those skilled in the art will understand that modified examples of these embodiments and examples are also within the scope of the present invention. Machine learning includes, for example, "supervised learning" that learns the relationship between input and output using teaching data to which labels (output information) are assigned to input information, "unsupervised learning" that builds a data structure only from unlabeled input, "semi-supervised learning" that handles both labeled and unlabeled data, and "reinforcement learning" that learns the action that can obtain the most feedback by obtaining feedback for the selected action from the observation result of the state.

[0064] Specific examples of machine learning techniques include neural networks (including deep learning using a multi-layer neural network), genetic programming, decision trees, Bayesian networks, and support vector machines (SVMs). The learning unit applies more optimal feature information generated by machine learning to various setting values ​​of the operation parameters 47 stored in the learning model 20. That is, the feature information indicates various setting values ​​of the operation parameters 47. In the above-described embodiment, the various setting values ​​of the operation parameters 47 used in production are used as labels.

[0065] In the above embodiment, the operation parameters 47 are set from one selected use, but the operation parameters 47 may be set from multiple uses. When setting the operation parameters 47 from multiple uses, the operation parameters 47 are calculated for each use, and the weighting is changed between the selected use and the non-selected use among the calculated multiple operation parameters 47 to calculate an average (weighted average). By calculating in this manner, it is possible to easily set the optimum operation parameters 47 for substrate uses that are difficult to classify other than the above-mentioned substrate uses.

[0066] In addition, the various set values ​​of the operation parameters 47 may be options other than numerical values. In the case of options, a reward is given to the operation parameters 47 of the options that are set without modification, and no reward is given to the operation parameters of the options that are modified. Then, the learning model is updated by updating the value (estimation rate) of the option according to the reward. For example, the options include a 2D mode and a 3D mode for the camera type of the operation parameters 47.

[0067] According to the present disclosure, optimal operating parameters can be easily set depending on the application of the substrate. [Industrial Applicability]

[0068] The production data creation device and production data creation method disclosed herein have the effect of making it possible to easily set optimal operating parameters depending on the application of a board, and are useful in the field of mounting components on boards. [Explanation of symbols]

[0069] 1 Component mounting system 2. Communication Network 3 Management Computer 4. Component mounting line 10 Processing section 11 Input Processing Section 12 First Setting Section 13 Second Setting Section 14. Performance Acquisition Department 15 Production information storage unit 16 Production Data Library 17 Parts Library 18 Operation Parameter Library 19 Rules Table 20 Learning Model 21 Production history memory section 22 Production History Information 23 Input section 24 Display section 25 Communications Department 30 Production Data 35 Equipment condition data 40 Parts Data 42 Shape diagram 43 Size Data 44 Part parameters 45 Parts Information 46 Tape Information 47 Operating parameters 47a Model 47b Nozzle Settings 47c Speed ​​parameters 47d recognition 47e Gap 47f Adsorption 50 Use selection screen 51 Input box 52 Selection Frame 52a Radio Button 53 Button 54 Part shape input screen 55 Input box 56 Input box 56a Scrollbar 57 Button 58 Input parameter input screen 59 Input box 60 input boxes 60a slider 61 Buttons 75 Quality M1 board supply device M2 Substrate transfer device M3 solder printing device M4, M5 component mounting equipment M6 Reflow Machine M7 Board recovery device

Claims

1. an input unit for receiving input parameters based on at least quality and productivity; a setting unit that sets operation parameters for the component mounting device to mount components on a board based on the input parameters that have been input; The input unit further receives input of shape information of the part, The setting unit sets operation parameters corresponding to the inputted shape information of the part and the inputted input parameters from a rule table that associates at least the shape information of the part, the input parameters, and the operation parameters.

2. an input unit for receiving input parameters based on at least quality and productivity; a setting unit that sets operation parameters for the component mounting device to mount components on a board based on the input parameters that have been input; The input unit further receives input of shape information of the part, The setting unit sets operation parameters corresponding to the input shape information of the part and the input input parameters from a learning model that associates at least the shape information of the part, the input parameters, and the operation parameters.

3. 3. The production data creation device according to claim 1, wherein the operational parameters include at least one of a nozzle parameter related to a nozzle that picks up the component, a pickup parameter related to pickup when picking up the component with the nozzle, a recognition parameter for recognizing a shape of the component, and a mounting parameter for mounting the component.

4. Accept input parameters based on at least quality and productivity, setting operation parameters for the component mounting apparatus to mount components on a board based on the input parameters that have been input; further receiving input of shape information of the part; A production data creation method, comprising: setting operation parameters corresponding to the input shape information of the part and the input input parameters from a rule table that associates at least the shape information of the part, the input parameters, and the operation parameters.

5. Accept input parameters based on at least quality and productivity, setting operation parameters for the component mounting apparatus to mount components on a board based on the input parameters that have been input; further receiving input of shape information of the part; A production data creation method, comprising: setting operation parameters corresponding to the input shape information of the part and the input input parameters from a learning model that associates at least the shape information of the part, the input parameters, and the operation parameters.

6. 6. The production data creation method according to claim 4, wherein the operational parameters include at least one of a nozzle parameter related to a nozzle that picks up the component, a pickup parameter related to pickup when picked up by the nozzle, a recognition parameter for recognizing a shape of the component, and a mounting parameter for mounting the component.

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