CN112788945A - Mounting condition estimation device, learning device, and mounting condition estimation method - Google Patents
Mounting condition estimation device, learning device, and mounting condition estimation method Download PDFInfo
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- 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
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- 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
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Abstract
The invention provides a mounting condition estimation device, a learning device, and a mounting condition estimation method. The mounting condition can be estimated with high accuracy even with a small amount of information. A mounting condition estimation system (100) estimates a mounting condition of a mounting device (200) for mounting a component (P) on a substrate (B), and is provided with: an information acquisition unit (108) that acquires first component information that is the value of at least one component parameter of component parameters that are parameters relating to a component (P); and an estimation unit (105) that estimates the mounting conditions based on the first component information acquired by the information acquisition unit (108).
Description
Technical Field
The present disclosure relates to an apparatus, a method, a program, and a learning apparatus for estimating mounting conditions for mounting a component on a substrate by a mounting apparatus.
Background
The mounting apparatus for mounting a component on a substrate selects a suction nozzle for sucking and holding the component based on mounting conditions corresponding to the size and weight of the component, and determines the speed for mounting the component on the substrate. Generally, the mounting conditions correspond to identification information of each member mounted on the substrate.
For example, in the technique described in patent document 1, an operation acceleration, which is one of mounting conditions, is calculated based on information on a component and a type of a suction nozzle that sucks and holds the component.
Documents of the prior art
Patent document
Patent document 1: JP 2012-156200A
However, since only CAD data of the mounting substrate exists, only a part of the component information necessary for calculating the mounting condition may be acquired, or only a part of the component information may be acquired at different timings.
Disclosure of Invention
To this end, the present disclosure provides a mounting condition estimation device, a learning device, a mounting condition estimation system, a mounting condition estimation method, and a program that can estimate mounting conditions using only a part of component information.
A mounting condition estimation device according to an aspect of the present disclosure estimates a mounting condition of a mounting device for mounting a component on a substrate, the mounting condition estimation device including: a component information acquisition unit that acquires first component information that is a value of at least one component parameter among component parameters that are parameters related to the component; and an estimation unit that estimates a mounting condition based on the first component information acquired by the component information acquisition unit.
A learning device according to another aspect of the present disclosure learns a model for estimating a mounting condition of a mounting device for mounting a component on a board, the learning device including: a learning component information acquisition unit that acquires component information that is a value of a parameter relating to the component; a learned mounting condition acquisition unit that acquires mounting conditions corresponding to the component information acquired by the learned component information acquisition unit; and a learning unit that learns a model based on the component information acquired by the learning component information acquisition unit and the mounting condition acquired by the learning mounting condition acquisition unit, wherein the learning component information acquisition unit acquires first component information that is a value of at least one component parameter among the component parameters and second component information that is a value of another component parameter, the learning unit learns the first model based on the first component information acquired by the learning component information acquisition unit and the mounting condition corresponding to the first component information, and the learning unit learns the second model based on the first component information acquired by the learning component information acquisition unit, the second component information, and the mounting condition corresponding to the first component information and the second component information.
These general or specific aspects may be implemented by a system, a method, an integrated circuit, a computer program, or a computer-readable recording medium such as a CD-ROM, or any combination of a system, a method, an integrated circuit, a computer program, and a recording medium. In addition, the recording medium may be a non-transitory recording medium.
ADVANTAGEOUS EFFECTS OF INVENTION
According to the mounting condition estimation device of the present disclosure, even when all pieces of component information that can be obtained are not available, the mounting condition can be estimated and the mounting device can be set.
In addition, further advantages and effects in an aspect of the present disclosure will be apparent from the description and the accompanying drawings. The advantages and/or effects are provided by the features described in the description and the drawings of several embodiments, respectively, but it is not necessary to provide all of the advantages and/or effects in order to obtain 1 or more of the same features.
Drawings
Fig. 1 is a diagram showing an example of a structure of a mounting device in the embodiment.
Fig. 2 is a view partially showing a section a-a in fig. 1.
Fig. 3 is a block diagram showing a functional configuration of the mounting condition estimation system according to the embodiment.
Fig. 4 is a diagram showing an example of the mounting condition estimation screen.
Fig. 5 is a flowchart showing a flow of the mounting condition estimation system according to the present embodiment when estimating the mounting conditions.
Fig. 6 is a diagram showing an example of a mounting condition estimation screen on which a size value is displayed.
Fig. 7 is a diagram showing an example of a mounting condition estimation screen on which mounting conditions estimated according to the value of the size are displayed.
Fig. 8 is a diagram showing an example of a mounting condition estimation screen on which values of the size and the weight are displayed.
Fig. 9 is a diagram showing an example of a mounting condition estimation screen on which mounting conditions estimated based on the values of the size and the weight are displayed.
Fig. 10 is a diagram showing an example of a mounting condition estimation screen on which a size value and a top view image are displayed.
Fig. 11 is a flowchart showing a flow of processing of the mounting apparatus and the mounting condition estimation system.
Fig. 12 is a block diagram showing a functional configuration of the mounting condition estimating apparatus.
Fig. 13 is a block diagram showing a functional configuration of the learning apparatus.
Fig. 14 is a diagram showing an example of a database used for estimation by the estimation unit.
Description of reference numerals
4 base station
5 substrate conveying mechanism
6 parts supply part
7 feeder
8Y axle beam
9X axle beam
9a plate
10 mounting head
10a adsorption component
10b suction nozzle
11 parts recognizing camera
12 substrate recognizing camera
13 trolley
13a feeder base
14-part carrier tape
15 box rack
100 installation condition estimation system
101 control unit
102 data generating part
103 model selection unit
104 learning unit
105 estimation unit
106 display part
107 input/output unit
108 information acquisition unit
110 installation condition estimating device
120 learning device
200 mounting device
210 installation condition estimation screen
211 Member information Screen
212 installation condition screen
220 database
Detailed Description
In order to solve the above-described problem, a mounting condition estimation device according to an aspect of the present disclosure estimates a mounting condition of a mounting device for mounting a component on a substrate, and includes: a component information acquisition unit that acquires first component information that is a value of at least one component parameter among component parameters that are parameters related to the component; and an estimating unit that estimates a mounting condition based on the first component information acquired by the component information acquiring unit. For example, the parameter related to the component may include at least one of a size, a shape, a weight, an appearance, a category, a surface condition of the component, and a provision form for providing the component. The mounting condition may include at least one of information on a type of a suction nozzle that sucks the component in the mounting device, transfer, recognition, suction, and mounting of the component, and the component information acquisition unit may acquire measurement data obtained by measuring the component by the mounting device as at least one of the first component information and the second component information.
Thus, even when all the component information to be input for estimating the mounting condition is not prepared, the mounting condition can be estimated. Therefore, the mounting conditions can be set for the mounting apparatus at a stage when the amount of information of the component information is small, and productivity can be improved. In addition, production simulation can be performed even at a stage where the amount of information of the component information is small.
Further, the component information acquisition unit may acquire second component information that is a value of another component parameter related to the component, and the estimation unit may include: a first model learned based on the first component information and the mounting condition; and a second model learned based on the first component information, the second component information, and the mounting condition, wherein the mounting condition is estimated based on at least one of the first component information and the second component information acquired by the component information acquisition unit.
Accordingly, by estimating the mounting conditions using the model corresponding to the type of the acquired component information, it is possible to estimate the optimum mounting conditions corresponding to the amount of information of the acquired component information.
Further, the learning device learns a model for estimating a mounting condition of a mounting device for mounting a component on a board, and includes: a learning component information acquisition unit that acquires component information that is a value of a parameter relating to the component; a learned mounting condition acquisition unit that acquires mounting conditions corresponding to the component information acquired by the learned component information acquisition unit; and a learning unit that learns a model based on the component information acquired by the learning component information acquisition unit and the mounting condition acquired by the learning mounting condition acquisition unit, wherein the learning component information acquisition unit acquires first component information that is a value of at least one component parameter among the component parameters and second component information that is a value of another component parameter, the learning unit learns the first model based on the first component information acquired by the learning component information acquisition unit and the mounting condition corresponding to the first component information, and the learning unit learns the second model based on the first component information acquired by the learning component information acquisition unit, the second component information, and the mounting condition corresponding to the first component information and the second component information. The learning component information acquiring unit may acquire measurement data obtained by the mounting device measuring the component as at least one of the first component information and the second component information. The measurement data may include a defective rate at the time of mounting the component by the mounting device.
Accordingly, models corresponding to the types of the component information can be prepared. Therefore, the optimum mounting condition according to the information amount of the acquired component information can be estimated.
The embodiments are described below with reference to the drawings. The embodiments described below are all general or specific examples. The numerical values, shapes, materials, components, arrangement positions and connection forms of the components, steps, order of the steps, and the like shown in the following embodiments are examples, and do not limit the present disclosure. In the following description, among the components in the embodiments, components not described in the independent claims indicating the highest concept are described as arbitrary components.
The drawings are schematic and not necessarily strict. In the drawings, the same constituent elements are sometimes denoted by the same reference numerals.
Fig. 1 is a diagram showing an example of the structure of a mounting apparatus 200. In the present embodiment, the conveying direction of the substrate B is referred to as an X-axis direction, and a direction perpendicular to the X-axis direction is referred to as a Y-axis direction. The X-axis direction and the Y-axis direction are directions along a horizontal plane. Further, a direction perpendicular to the X-axis direction and the Y-axis direction is referred to as a Z-axis direction. The X-axis direction positive side and the negative side are the downstream side and the upstream side in the transport direction of the substrate B, respectively, and the Y-axis direction positive side and the negative side are the rear side (or the back side) and the front side (or the near side) in the front-back direction, respectively. The positive side and the negative side in the Z-axis direction are the upper side and the lower side in the up-down direction, respectively. The upper surface of the mounting device 200 is shown in fig. 1.
The mounting device 200 includes a base 4, a substrate conveyance mechanism 5, 2 component supply units 6, 2X-axis beams 9, a Y-axis beam 8, 2 mounting heads 10, 2 component recognition cameras 11, and 2 substrate recognition cameras 12.
The substrate transport mechanism 5 includes 2 slide rails along the X-axis direction, and is disposed at the center of the base 4. The substrate transport mechanism 5 transports the substrate B carried in from the upstream side, and positions and holds the substrate B at a position for performing component mounting work.
The 2 component supply portions 6 are arranged to sandwich the substrate transport mechanism 5 in the Y-axis direction. A plurality of feeders 7 are arranged in parallel along the X-axis direction in each component supply section 6. The feeder 7 pitch-feeds the component carrier tape containing the components in the carrier tape feeding direction to supply the components to a position where the mounting head 10 takes out the components (hereinafter referred to as a component taking-out position).
Further, a tray feeder, a rod feeder, a bulk feeder, or the like may be disposed in the component supply unit 6. The tray feeder supplies the components from a tray in which the components are stored. The rod feeder supplies the components from a rod container in which the components are stored. The bulk feeder supplies the components from a bulk container in which the components are stored.
The Y-axis beam 8 is disposed along the Y-axis direction at one end (right side in fig. 1) in the X-axis direction on the upper surface of the base 4. The 2X-axis beams 9 are coupled to the Y-axis beam 8 so as to be movable in the Y-axis direction in a state along the X-axis direction.
Mounting heads 10 are provided on the 2X-axis beams 9 so as to be movable in the X-axis direction, respectively. The mounting head 10 includes a plurality of suction modules 10a that can be raised and lowered while holding components by suction. Suction nozzles 10b (see fig. 2) are provided at the respective front ends of the suction modules 10 a.
The 2 mounting heads 10 are moved in the X-axis direction and the Y-axis direction by driving the Y-axis beam 8 and the X-axis beam 9, respectively. Thus, the 2 mounting heads 10 respectively pick up and take out the components from the component pickup positions of the feeders 7 arranged in the component supply units 6 corresponding to the mounting heads 10 by the suction nozzles 10B, and mount the components on the mounting points (or mounting positions) of the substrates B positioned in the substrate transport mechanism 5.
The 2 component recognition cameras 11 are respectively disposed between one of the 2 component supply units 6 and the substrate transport mechanism 5. The component recognition camera 11 picks up an image of a component when the mounting head 10 that has taken out the component from the component supply unit 6 moves above the component recognition camera 11. That is, the component recognition camera 11 recognizes the component held by the mounting head 10 and the holding posture of the component by imaging the component.
The board recognition camera 12 is mounted on the sheet 9a on which the mounting head 10 is mounted. Therefore, the substrate recognition camera 12 moves integrally with the mounting head 10. The substrate recognition camera 12 moves above the substrate B positioned on the substrate transport mechanism 5 in accordance with the movement of the mounting head 10, and recognizes the position of the substrate B by imaging a substrate mark (not shown) provided on the substrate B. In mounting of the component on the substrate B by the mounting head 10, the mounting position is corrected based on the recognition result of the component by the component recognition camera 11 and the recognition result of the position of the substrate B by the substrate recognition camera 12.
Fig. 2 is a view partially showing a section a-a in fig. 1. The mounting apparatus 200 has a function of mounting the component P on the substrate B.
As shown in fig. 2, component supply unit 6 includes a feeder base 13a, a plurality of feeders 7 mounted on feeder base 13a, and a carriage 13 supporting feeder base 13 a.
The carriage 13 is configured to be detachable from the base 4, and further includes a cassette holder 15. The magazine 15 is configured to hold a plurality of component reels C. The component reel C receives the component carrier tape 14 in a wound state. The component reels C are held at the upper holding position Hu or the lower holding position Hd of the cassette holder 15. The feeder 7 is equipped with a component carrier tape 14 pulled out from a component reel C held by a magazine 15. Feeder 7 may be disposed on a feeder base 13a provided on base 4 without using carriage 13.
Fig. 3 is a block diagram showing a functional configuration of the mounting condition estimation system 100. The mounting condition estimation system 100 is a system having both a function as a mounting condition estimation device and a function as a learning device, and includes a control unit 101, a data generation unit 102, a model selection unit 103, a learning unit 104, an estimation unit 105, a display unit 106, an input/output unit 107, an information acquisition unit 108, a mounting condition holding unit DB1, and a model holding unit DB 2.
The model selecting unit 103 selects an appropriate model corresponding to the type (component parameter) of the acquired component information from the plurality of learned models including the first model and the second model held in the model holding unit DB 2. In the present embodiment, it is described that 4 parameters including the size, the weight, the friction coefficient, and the fraction defective obtained from the top view image are set as the component parameters, and the mounting condition estimation system 100 includes the first to eighth models corresponding to the combination of these parameters.
The model holding portion DB2 holds at least a first model and a second model. In the case of the present embodiment, the model holding unit DB2 holds eight models, i.e., the first to eighth models. These plural learned models may be different models or the same model. Examples of the model (algorithm) include a regression model such as linear regression, logistic regression, or support vector machine, a tree model such as decision tree or random forest, and a neural network. For example, a model that can estimate an appropriate mounting condition even when the number of input component parameters is small may be used as the first model, and a model that is suitable for a case where there are more types of input component parameters than the first model may be used as the second model.
The information acquisition unit 108 is a processing unit that functions as a component information acquisition unit, a learning component information acquisition unit, and a learning mounting condition acquisition unit. When the information acquisition unit 108 functions as a component information acquisition unit, the information acquisition unit 108 acquires first component information, which is a value of at least one component parameter among component parameters that are parameters related to the component P, from CAD data, measurement values measured in the mounting device 200, and the like. Further, second part information, which is a value of another part parameter related to the part P, may be acquired. The information acquisition unit 108 may acquire the first component information and the second component information at the same time, or may acquire the second component information at a timing later than the first component information.
When the information acquisition unit 108 functions as a learning component information acquisition unit, the information acquisition unit 108 acquires first component information and second component information relating to the component P from the mounting data holding unit DB1 and the like. The information acquisition unit 108 outputs the acquired component information to the learning unit 104.
When the information acquisition unit 108 functions as a learning mounting condition acquisition unit, the information acquisition unit 108 acquires mounting conditions corresponding to component information from the mounting data holding unit DB1 or the like. The information acquisition unit 108 associates the acquired mounting conditions with the component information and outputs the same to the learning unit 104.
The input/output unit 107 receives input data based on an operation of an operator, for example, and outputs the input data to the control unit 101. Such an input/output unit 107 may include, for example, a keyboard, a touch sensor, a touch panel, a mouse, and the like.
The input/output unit 107 also includes an interface for outputting data to the mounting device 200 and inputting data from the mounting device 200. The mounting data generated by the data generation unit 102 may be output to the mounting device 200 via the input/output unit 107, or the results of the mounting conditions may be input from the mounting device 200 or the mounting simulator.
The estimation unit 105 estimates the mounting conditions of the mounting device 200. In the case of the present embodiment, the estimation unit 105 estimates the mounting conditions for mounting the component P on the board B, using the component information on the component P mounted on the board B as an input, based on the model selected by the model selection unit 103. The specific estimation method by the estimation unit 105 will be described later.
The data generation unit 102 generates mounting data for mounting the component P on the substrate B using the mounting conditions estimated by the estimation unit 105, the mounting conditions adjusted by an operator or the like, actual result mounting conditions, and the like. The mounting data includes, for example, the type and mounting order of the components P mounted on the substrate B, and the mounting positions of the components P on the substrate B.
The installation data may contain component information corresponding to the component P. In the case of the present embodiment, the mounting data is held in the mounting data holding portion DB 1. The mounting data is held in a state in which the respective component information of the plurality of kinds of components P and the mounting conditions are associated. Therefore, when the mounting data relating to the component P of the same type as the component P whose mounting condition is estimated by the estimation unit 105 is stored, the data generation unit 102 updates the mounting data. On the other hand, if there is no installation data corresponding to the same type of component P, new data is added to the installation data.
The mounting conditions included in the mounting data generated by the data generation unit 102 may be corrected or adjusted based on the results of the mounting conditions acquired from the mounting device 200. That is, the mounting apparatus 200 mounts the component P on the substrate B based on the mounting conditions estimated by the estimating section 105, but in some cases, a defective mounting substrate is produced due to the mounting. In such a case, the mounting apparatus 200 corrects or adjusts the component data included in the mounting conditions so as to reduce the frequency of defective products. There are cases where the installation data is updated by such correction or adjustment.
The learning unit 104 learns a model including a first model and a second model. In the present embodiment, the learning unit 104 performs model learning by supervised learning. The learning unit 104 learns the first model using, as input information, first component information acquired from the mounting data and the like by an information acquisition unit functioning as a component information acquisition unit, and using mounting conditions corresponding to the first component information as supervision information. The learning unit 104 learns the second model using the first component information and the second component information as input information and using the mounting conditions corresponding to the first component information and the second component information as supervision information.
When another model is held in the model holding unit DB2, the learning unit 104 may perform learning using component information and mounting conditions corresponding to the model.
The control unit 101 controls each component other than the control unit 101 included in the mounting condition estimation system 100. For example, the control unit 101 controls each component based on input data of the operator received by the input/output unit 107, and the like.
The mounting data holding portion DB1 and the model holding portion DB2 are recording media for holding mounting conditions and models, respectively. Examples of such a recording medium include a hard disk, a RAM (Read Only Memory), a ROM (Random Access Memory), and a semiconductor Memory. Such a recording medium may be volatile or nonvolatile.
The display unit 106 displays the component information acquired by the information acquisition unit 108 and the mounting conditions estimated by the estimation unit 105. The type of the display unit 106 is not particularly limited, and a liquid crystal display can be exemplified.
Fig. 4 is a diagram showing an example of the mounting condition estimation screen 210. The mounting condition estimation screen 210 displayed on the display unit 106 includes a component information screen 211 for presenting component information and a mounting condition screen 212 for presenting estimated mounting conditions.
The parameters related to the component P include a size, a shape, a weight, an appearance, a type, a surface state, a provision form, and the like, but in the present embodiment, all the component parameters related to the component P are a length L, a width W, a height T, a weight, a friction coefficient as a surface state, and a top view image as an appearance. In addition, the top view image is used in a case where the kind or the type of the component is estimated by matching of the image or the like.
As the mounting parameters of the mounted component P, there are the type of the suction nozzle performing suction, transfer, recognition, suction, and equipment, but in the case of the present embodiment, all the mounting parameters related to the component P are the type of the suction nozzle, and the equipment conditions including transfer and equipment of the component. The equipment condition is a parameter indicating what% of components are transferred at a predetermined speed and loaded.
Next, a method of estimating the mounting condition will be described. Fig. 5 is a flowchart showing a flow of the mounting condition estimation system 100 according to the present embodiment when estimating the mounting conditions. The information acquisition unit 108 functions as a component information acquisition unit, and acquires component information on the component P from the CAD data, the input/output unit 107, and the like (S101). When the operator presses the estimation button in the mounting condition estimation screen 210 displayed on the display unit 106 (yes in S102), it is determined whether or not a value of one of the component parameters (first component information in the present embodiment) is present (S103). If there is no value of the size (no in S103), an error message is displayed (S104), and the process ends. On the other hand, when there is a value of the size (yes in S103), it is determined whether only the value of the size exists or another value exists in the part information (S105). If the acquired component information is only the size as shown in fig. 6 (yes in S105), estimation is performed by the first model learned by the value of the size and the mounting condition (S106), and the mounting condition as the estimation result is displayed on the display unit 106 as shown in fig. 7 (S107).
Next, when the acquired component information includes information other than the size (no in S105) and a value of the weight other than the value of the size (second component information in the present embodiment) (yes in S108) and only the values of the size and the weight exist as shown in fig. 8 (yes in S109), estimation is performed by using the values of the size and the weight and the second model learned by the mounting conditions (S110), and the mounting conditions as the estimation results are displayed on the display unit 106 as shown in fig. 9 (S107). Here, the weight of the part P may use a result actually measured by the mounting device 200. Further, the weight of the part P measured by the operator input via the input/output unit 107 may be used. The kind of the suction nozzle as the estimated mounting condition is different from the result estimated with the first model. That is, a more suitable mounting condition is estimated by the second model.
Next, when there is no value of the weight other than the value of the size (no in S108) and no value of the friction coefficient (third component information in the present embodiment) (no in S111), the defect rate is derived based on the top view image shown in fig. 9, and estimation is performed by the third model learned by the values of the size and the defect rate (fourth component information in the present embodiment) and the mounting conditions (S112), and the mounting conditions as the estimation results are displayed on the display unit 106 as shown in fig. 10 (S107). Here, the top view image of the component P can be acquired by, for example, the substrate recognition camera 12 of the mounting apparatus 200. The equipment condition is reduced to 80% as the mounting condition which is the estimation result based on the combination of the component parameters of this time. This is considered to be because the component P is reflected in the estimated result, and the component P is transferred more slowly due to the high defective rate, and the component P held by the suction nozzle is mounted.
Next, when there is no weight value other than the size value (no in S108), there is a friction coefficient value (yes in S111), and there is no component information other than the size and friction coefficient values (yes in S113), estimation is performed by the fourth model learned by the size, friction coefficient values, and mounting conditions (S114), and the mounting conditions as the estimation results are displayed on the display unit 106 (S107).
Next, when there is no weight value other than the size value (no in S108), there is a friction coefficient value (yes in S111), and there is component information other than the size and friction coefficient values (no in S113), estimation is performed by using the fifth model learned by the mounting conditions and the values of the size, friction coefficient, and failure rate (S115), and the mounting conditions, which are the estimation results, are displayed on the display unit 106 (S107).
Next, when there is a value of weight other than the value of the size (yes in S108), and there is a value other than the value of the size and the weight (no in S109), and there is no value of the friction coefficient (no in S116), estimation is performed by the sixth model learned by the values of the size, the weight, and the defective fraction and the mounting conditions (S118), and the mounting conditions as the estimation results are displayed on the display unit 106 (S107).
Next, when there is a value of weight other than the value of the size (yes in S108), there is a value other than the size and the weight (no in S109), there is a value of the friction coefficient (yes in S116), and only the values of the size, the weight, and the friction coefficient exist (yes in S117), estimation is performed by the seventh model learned by the values of the size, the weight, and the friction coefficient and the mounting conditions (S119), and the mounting conditions as the estimation results are displayed on the display unit 106 (S107).
Next, when there is a value of the weight other than the value of the size (yes in S108), there is a value other than the size and the weight (no in S109), there is a value of the friction coefficient (yes in S116), and there is a value other than the values of the size, the weight, and the friction coefficient (no in S117), the eighth model learned by the values of the size, the weight, the friction coefficient, and the failure rate and the mounting conditions is estimated (S120), and the mounting conditions as the estimation results are displayed on the display unit 106 (S107).
Next, the flow of processing of the mounting apparatus 200 and the mounting condition estimation system 100 in the production of the mounting substrate will be described. Fig. 11 is a flowchart showing a flow of processing of the mounting apparatus and the mounting condition estimation system.
In the mounting apparatus 200, production of a mounting substrate is started (S201). The mounting data generated from the result estimated by the mounting condition estimation system 100 previously is used in the production of the mounting substrate. When a timing at which component parameters can be measured occurs in the production of sequentially mounting a plurality of components P on the substrate B (yes at S202), the mounting apparatus 200 performs measurement of the components P (S203). For example, when the weight of the component P is measured, the identification mark of the component P (for example, the component name AX shown in fig. 6 or the like) is output in association with the value of the weight, and the information acquisition unit 108 of the mounting condition estimation system 100 functions as a component information acquisition unit to acquire the value of the weight (S204).
The mounting condition estimation system 100 that has acquired the weight value as the component information estimates the weight-containing value for the component name AX, and resets the mounting condition of the estimation result as new mounting data (S205). Thereafter, the component name AX is mounted under the new mounting conditions. The above flow is repeated until the production is ended (no at S206).
When the production of the mounting substrate is completed (yes in S206), the mounting results are summed up (S207). The total of the mounting results includes mounting conditions adjusted by an operator or the like during production, collection of defective rates of the respective parts P, and the like.
The component information including the measured value and the defective rate is output in association with the actual results of the mounting conditions, and the information acquisition unit 108 of the mounting condition estimation system 100 functions as a learning component information acquisition unit and a learning mounting condition acquisition unit to acquire actual results mounting information (S208).
The mounting condition estimation system 100 updates the mounting data held in the mounting data holding part DB1 based on the new actual result mounting information (S209). In addition, the installation condition estimation system 100 performs relearning on each model based on the new actual performance installation information (S210).
The present invention is not limited to the above embodiments. For example, any combination of the constituent elements described in the present specification may be adopted, and another embodiment in which some of the constituent elements are removed may be adopted as an embodiment of the present invention. In addition, the present invention includes modifications of the above-described embodiment, which are made by various modifications that a person skilled in the art may take without departing from the gist of the present invention, that is, within the meaning of the terms described in the scope of the claims.
For example, although the mounting condition estimation system 100 that performs machine learning of a model and estimates mounting conditions has been described as an example, the mounting condition estimation device 110 that performs estimation of mounting conditions as shown in fig. 12 and the learning device 120 that performs machine learning of a model as shown in fig. 13 may be separated. In this case, the information acquisition unit 108 of the mounting condition estimation device 110 functions as a component information acquisition unit. The information acquisition unit 108 of the learning device 120 functions as a learning component information acquisition unit and a learning mounting condition acquisition unit.
The mounting condition estimation system 100 and the mounting condition estimation device 110 are described as including the data generation unit 102 and the mounting data holding unit DB1, but at least one of the mounting condition estimation system 100 and the mounting condition estimation device 110 may be included in the mounting device 200 or another higher-level computer.
In addition, although the case where the mounting conditions are estimated based on the model obtained by machine learning has been described in the above embodiment, the estimation unit 105 may estimate the mounting conditions based on the database 220 in which the component information and the mounting conditions are associated for each component name, as shown in fig. 14. Specifically, for example, when the information acquisition unit 108 acquires only the value of the size for the part name AX, the estimation unit 105 may specify the value of the size with the highest similarity from the database 220 and estimate the mounting condition associated with the specified value of the size as the mounting condition of the part name AX. In addition, when the value of the weight of the part name AX is obtained by measurement or the like, from the mounting conditions associated with the values of the size having the similarity of the values of the size of the first threshold or more, the mounting condition associated with the value of the weight having the highest similarity with respect to the value of the weight may be estimated as the mounting condition of the part name AX. Further, the mounting condition of the component name AX may be estimated based on the friction coefficient and the similarity of the top view image.
Further, the component recognition camera 11, the substrate recognition camera 12, and the weight measuring device are exemplified as the measuring device provided in the mounting device 200, but other devices such as a height sensor for measuring the height of the component P, and a three-dimensional measuring device for measuring the three-dimensional shape of the component P may be exemplified. In addition, these measured values can be adopted as one of the component information.
Further, although the mounting apparatuses 200 and the mounting condition estimation system 100 are described in a one-to-one state, a plurality of mounting apparatuses 200 may be communicably connected to 1 mounting condition estimation system 100. The communication-capable connection includes a connection via a public line such as the internet. By aggregating actual-result mounting conditions from a plurality of mounting apparatuses 200, it is possible to construct a database 220 with a large amount of information, or to perform model learning of machine learning based on a large amount of information, thereby improving the accuracy of estimation of mounting conditions.
Further, a plurality of mounting condition estimation devices 110 may be communicatively connected to one learning device 120, and the plurality of mounting condition estimation devices 110 may estimate the mounting conditions using the same learned model or database 220.
The following cases are also included in the present disclosure.
(1) The devices are specifically computer systems including microprocessors, ROMs, RAMs, hard disk components, display components, keyboards, mice, and the like. And storing the computer program in the RAM or the hard disk component. Each device achieves its function by the microprocessor acting in accordance with the computer program. Here, the computer program is configured by combining a plurality of command codes indicating instructions to the computer in order to achieve a predetermined function.
(2) A part or all of the components constituting each of the above-described apparatuses may include 1 system LSI (Large Scale Integration). The system LSI is an ultra-multifunctional LSI manufactured by integrating a plurality of components on 1 chip, and specifically is a computer system including a microprocessor, a ROM, a RAM, and the like. A computer program is stored in the RAM. The system LSI achieves its functions by the microprocessor operating in accordance with the computer program.
(3) Some or all of the components constituting each of the above-described devices may include an IC card or a single module that can be attached to and detached from each device. The IC card or the module is a computer system including a microprocessor, a ROM, a RAM, and the like. The IC card or the module may contain the above-described ultra-multifunctional LSI. The IC card or the module achieves its functions by the microprocessor acting following the computer program. The IC card or the module may have tamper resistance.
(4) The present disclosure may be configured as the method shown above. The present invention may be a computer program for realizing these methods by a computer, or may be a digital signal including the computer program.
The present disclosure can be configured such that the computer program or the digital signal is recorded on a computer-readable recording medium, such as a flexible disk, a hard disk, a CD-ROM, an MO, a DVD-ROM, a DVD-RAM, a BD (Blu-ray (registered trademark)) Disc, a semiconductor memory, or the like. The digital signal may be recorded in such a recording medium.
In addition, the present disclosure may be configured such that the computer program or the digital signal is transmitted via an electric communication line, a wireless or wired communication line, a network typified by the internet, data broadcasting, or the like.
The present disclosure may be a computer system including a microprocessor and a memory, the memory storing the computer program, and the microprocessor operating according to the computer program.
The program or the digital signal may be recorded in the recording medium and transferred, or may be transferred via the network or the like and implemented by another independent computer system.
(5) The above embodiment and the above modification may be combined.
Industrial applicability
The present disclosure can be used in a system for producing a mounting substrate by mounting a component on a substrate, and the like.
Claims (10)
1. A mounting condition estimation device that estimates a mounting condition of a mounting device for mounting a component on a substrate, the mounting condition estimation device comprising:
a component information acquisition unit that acquires first component information that is a value of at least one component parameter among component parameters that are parameters related to the component; and
and an estimation unit that estimates a mounting condition based on the first component information acquired by the component information acquisition unit.
2. The mounting condition estimating device according to claim 1,
the component information acquisition unit acquires second component information that is a value of another component parameter related to the component,
the estimation unit includes: a first model learned based on the first component information and the mounting condition; and a second model learned based on the first component information, the second component information, and the mounting condition, wherein the mounting condition is estimated based on the first component information and the second component information acquired by the component information acquisition unit.
3. The mounting condition estimation device according to claim 1 or 2,
the parameter related to the component includes at least one of a size, a shape, a weight, an appearance, a category, a surface condition of the component, and a provided form for providing the component.
4. The mounting condition estimation device according to claim 1 or 2,
the mounting condition includes at least one of information related to a type of a suction nozzle that sucks the component in the mounting device, transfer, recognition, suction, and equipment of the component.
5. The mounting condition estimation device according to claim 1 or 2,
the component information acquisition unit acquires measurement data obtained by the mounting device measuring the component as at least one of first component information and second component information.
6. A learning device for learning a model for estimating a mounting condition of a mounting device for mounting a component on a substrate, the learning device comprising:
a learning component information acquisition unit that acquires component information that is a value of a parameter relating to the component;
a learning component information acquisition unit configured to acquire component information corresponding to the component information acquired by the learning component information acquisition unit; and
a learning unit configured to learn a model based on the component information acquired by the learning component information acquisition unit and the mounting condition acquired by the learning mounting condition acquisition unit,
the learning component information acquisition unit acquires first component information that is a value of at least one component parameter among the component parameters and second component information that is a value of another component parameter,
the learning unit learns the first model based on the first component information acquired by the learning component information acquisition unit and the mounting condition corresponding to the first component information, and learns the second model based on the first component information, the second component information acquired by the learning component information acquisition unit and the mounting condition corresponding to the first component information and the second component information.
7. The learning apparatus according to claim 6, wherein,
the learning component information acquiring unit acquires measurement data obtained by the mounting device measuring the component as at least one of first component information and second component information.
8. The learning apparatus according to claim 7, wherein,
the measurement data includes a defective rate when the component is mounted by the mounting device.
9. A mounting condition estimation system is provided with:
the mounting condition estimation device of claim 1 or 2; and
the learning device according to any one of claims 6 to 8.
10. A mounting condition estimating method estimates a mounting condition of a mounting apparatus for mounting a component on a substrate,
the component information acquisition unit acquires first component information that is a value of at least one component parameter among component parameters that are parameters related to the component,
the estimation unit estimates a mounting condition based on the first component information acquired by the component information acquisition unit,
the component information acquisition unit acquires second component information that is a value of another component parameter related to the component,
the estimation unit estimates the mounting condition based on the first component information and the second component information acquired by the component information acquisition unit.
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| JP2019200840A JP7382575B2 (en) | 2019-11-05 | 2019-11-05 | Mounting condition estimation device, learning device, mounting condition estimation method, and program |
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