Production plant management system, operation countermeasure decision method, and recording medium

Abstract

A production plant management system (1) is a system that manages a state of a production plant that has a production device that produces a production object, and includes a state monitoring unit (20) that monitors the state, detects a given state based on a first condition for detecting the given state among the state, a countermeasure decision unit (30) that decides a countermeasure to be executed based on a second condition for deciding the countermeasure corresponding to the given state, an effect determination unit (60) that determines an effect of the countermeasure to be executed based on the state before and after the countermeasure decided is executed, and an update unit (70) that updates the first condition and the second condition based on the effect determined.

Description

Technical Field

[0001] This disclosure relates to a production workshop management system for managing the status of a production workshop equipped with production facilities for producing products, a method for determining work countermeasures within the system, and a recording medium. Background Technology

[0002] Previously, technologies have been disclosed that update the response method for a problem when a problem occurs in a production unit and output work instructions corresponding to the response method (e.g., Patent Document 1).

[0003] Prior art literature

[0004] Patent documents

[0005] Patent Document 1: International Publication No. 2018 / 142604 Summary of the Invention

[0006] -The problem the invention aims to solve-

[0007] However, sometimes the production equipment itself changes due to the conditions of the production workshop, etc., making it difficult to output the best operating instructions in such cases under the technology disclosed in the aforementioned Patent Document 1.

[0008] Therefore, this disclosure provides a production workshop management system, etc., that can output optimal work instructions in response to changes in the problem itself.

[0009] -Methods for solving problems-

[0010] One aspect of this disclosure relates to a production workshop management system that manages the state of a production workshop, the production workshop having production equipment for producing products, and comprising: a state monitoring unit that monitors the state and detects the given state based on a first condition for detecting a given state among the states; a countermeasure decision unit that determines the countermeasure to be executed based on a second condition for determining a countermeasure corresponding to the given state; an effect determination unit that determines the effect of the executed countermeasure based on the state before and after executing the determined countermeasure; and an update unit that updates the first condition and the second condition based on the determined effect.

[0011] Furthermore, these general or specific aspects can be realized either by a system, apparatus, method, recording medium or computer program, or by any combination of such systems, apparatus, method, recording medium and computer program.

[0012] -Invention Effects-

[0013] Based on the production workshop management system and other systems disclosed herein, optimal work instructions can be output in response to changes in the problem itself. Attached Figure Description

[0014] Figure 1 This is a diagram illustrating the installation production line of the production workshop management system involved in the application implementation method.

[0015] Figure 2 This is a structural diagram illustrating an example of a production workshop management system according to an implementation method.

[0016] Figure 3 This diagram illustrates an example of a monitoring object of the status monitoring unit involved in the implementation embodiment.

[0017] Figure 4 This is a schematic diagram illustrating the flow of operations of the production workshop management system involved in the implementation method.

[0018] Figure 5 This is a flowchart illustrating an example of the operation of the status monitoring unit involved in the implementation.

[0019] Figure 6 This is a flowchart illustrating an example of the operation of the countermeasure decision unit involved in the implementation method.

[0020] Figure 7 This is a table showing an example of a list of candidate countermeasures related to the implementation method.

[0021] Figure 8 This is a table showing an example of a list of priority countermeasures involved in the implementation.

[0022] Figure 9 This is a flowchart illustrating an example of the operation of the countermeasure mediation unit involved in the implementation.

[0023] Figure 10 This is an example of a resource management table involved in an implementation method.

[0024] Figure 11 This is a flowchart illustrating an example of the operation of the instruction output unit, effect determination unit, and update unit involved in the implementation method.

[0025] Figure 12 This is a table showing an example of an updated list of countermeasure candidates related to the implementation method.

[0026] Figure 13 This is a flowchart illustrating an example of a work countermeasure decision method according to another embodiment. Detailed Implementation

[0027] The production workshop management system disclosed herein is a production workshop management system for managing the state of a production workshop, wherein the production workshop has production equipment for producing products, and the production workshop management system comprises: a state monitoring unit that monitors the state and detects the given state based on a first condition for detecting a given state among the states; a countermeasure decision unit that determines the countermeasure to be executed based on a second condition for determining a countermeasure corresponding to the given state; an effect determination unit that determines the effect of the executed countermeasure based on the state before and after executing the determined countermeasure; and an update unit that updates the first condition and the second condition based on the determined effect.

[0028] Therefore, the effectiveness of countermeasures can be determined by assessing whether the state of the production workshop has changed before and after implementing them, and if so, how. Since the effectiveness of countermeasures changes when the problem itself in the production workshop changes, the first and second conditions can be updated to optimal conditions based on the determined effectiveness. Thus, optimal work instructions can be output in accordance with changes in the problem itself. For example, conditions can be intentionally changed in response to changes in production equipment or production conditions.

[0029] Alternatively, there may be multiple countermeasures, and the second condition may include a priority set according to each of the multiple countermeasures. The countermeasure decision unit determines the countermeasure to be output from the multiple countermeasures based on the respective priorities of the multiple countermeasures extracted in correspondence with the given state.

[0030] Accordingly, it is possible to execute a high-priority countermeasure based on the priority set for each of a plurality of countermeasures extracted according to a given detected state. In this disclosure, the priority set for each of the plurality of countermeasures can be updated based on the effect of the executed countermeasure.

[0031] Furthermore, the first condition may be a first learning model associated with a detection threshold corresponding to the given state, and the second condition may be a second learning model associated with multiple strategies corresponding to the given state and the priority.

[0032] Therefore, the first and second conditions can be effectively updated by using a learning model.

[0033] Furthermore, the detection threshold corresponding to the given state may include any one of the following: the detection threshold corresponding to the flow rate of the suction nozzle of the production device, the detection threshold corresponding to the deviation of the conveyor belt positioning position of the feeder of the production device, the detection threshold corresponding to the deviation of the adsorption position of the component adsorbed by the suction nozzle, or the detection threshold corresponding to the deviation of the conveying position of the substrate.

[0034] Furthermore, the countermeasure decision unit may also analyze the operation information of the production equipment obtained in the production workshop, the operator information of the workers performing operations in the production workshop, and the material information for the produced product to determine the countermeasure corresponding to the given state.

[0035] In this way, by analyzing the operating information of the production equipment, the information of the operators working in the production workshop, and the material information used for production, the optimal operating instructions can be effectively output.

[0036] Furthermore, the work countermeasure decision method disclosed herein is a work countermeasure decision method in a production workshop management system for managing the state of a production workshop, wherein the production workshop has production equipment for producing products, and the work countermeasure decision method includes: monitoring the state, and detecting the given state based on a first condition for detecting a given state in the state; determining the countermeasure to be executed based on a second condition for determining a countermeasure corresponding to the given state; determining the effect of the executed countermeasure based on the state before and after executing the determined countermeasure; and updating the first condition and the second condition based on the determined effect.

[0037] Furthermore, the recording medium disclosed herein is a computer-readable recording medium that records a work countermeasure decision program that enables a computer to execute the above-described work countermeasure decision method.

[0038] Furthermore, the embodiments described below are all general or specific examples. The values, shapes, materials, constituent elements, the arrangement and location of constituent elements, the connection methods, steps, and the order of steps shown in the following embodiments are examples and are not intended to limit this disclosure.

[0039] (Implementation Method)

[0040] The following uses Figures 1 to 12 The implementation method will be described below.

[0041] Figure 1 This is a diagram showing the installation production line 4 of the production workshop management system 1 involved in the application implementation method.

[0042] like Figure 1 As shown, production line 4 has multiple production devices for producing products.

[0043] The installation production line 4 has the function of producing products (e.g., mounting substrates) by mounting components (electronic components) on substrates, and has the function of supplying, transferring and recycling substrates for mounting objects respectively.

[0044] Specifically, in the assembly line 4, the substrate supply device M1, substrate transfer device M2, printing device M3, mounting devices M4 and M5, reflow soldering device M6, and substrate recycling device M7 are connected in series in this order. Each device from the substrate supply device M1 to the substrate recycling device M7 is connected to the management device 5 via the communication network 2.

[0045] For example, the printing apparatus M3, mounting apparatuses M4 and M5, and reflow soldering apparatus M6 perform component mounting operations on substrates conveyed along the mounting production line 4 for mounting components. That is, the substrates supplied by the substrate supply apparatus M1 are transferred into the printing apparatus M3 via the substrate receiving apparatus M2. The printing apparatus M3 performs a solder printing operation on the transferred substrates, screen printing solder for component bonding.

[0046] The solder-printed substrates are sequentially transferred to mounting devices M4 and M5. Mounting devices M4 and M5 perform component mounting operations on the solder-printed substrates.

[0047] Component mounting devices M4 and M5 include a base, a substrate conveying section, a component supply device, and a mounting head. A substrate is placed on the base. The substrate conveying section transports substrates transferred from an upstream device to a downstream device. The component supply device supplies components to the mounting head. The component supply device is equipped with multiple conveyor belt feeders for supplying components to the mounting head. The mounting head picks up components from the conveyor belt feeders, moves them above the substrate, and mounts the components at the substrate's mounting position. The mounting head is equipped with a suction nozzle that holds the components and can be independently raised and lowered. Component mounting operations are performed using these component mounting devices M4 and M5.

[0048] Furthermore, the substrate after component mounting is moved into the reflow soldering unit M6 and heated according to a given heating profile. Thereby, the solder used for component bonding printed on the heated substrate melts and solidifies. Thus, the component and substrate are soldered together, and the mounting substrate with the component mounted on it is completed. The completed mounting substrate is then recycled by the substrate recycling unit M7.

[0049] Next, use Figure 2 The structure of production workshop system 1 is described.

[0050] Figure 2 This is a structural diagram illustrating an example of a production workshop management system 1 according to an embodiment.

[0051] The production workshop management system 1 is a system that manages the status of a production workshop equipped with production facilities for producing products. The production workshop includes, for example, an assembly line 4, a storage warehouse, a preparation area, and a maintenance area. As described above, the assembly line 4 is equipped with production devices such as installation devices M4 and M5, and printing devices such as printing device M3, as well as inspection devices. The storage warehouse stores components, solder, screen printing masks, and other materials. The preparation area prepares equipment elements such as trolleys, feeders, nozzles, and heads. The maintenance area maintains the aforementioned equipment elements and fixtures. The fixtures mentioned here refer to those used for adjusting feeders, nozzles, heads, etc., and may also include those used for adjusting the head movement mechanism and conveying mechanism of the equipment. Operators perform production, preparation, and maintenance operations in each area of ​​the production workshop, and transfer components and equipment elements between areas. For example, the production workshop management system 1 is a computer installed in the production workshop. For example, the functions of the production workshop management system 1 may also be provided in a management device 5. Furthermore, the production workshop management system 1 can be a computer housed in a single enclosure, or it can be distributed across two or more enclosures and operated by two or more computers. Additionally, the production workshop management system 1 can be located outside the production workshop, such as as a server or other computer. Moreover, the operators are not limited to humans, but include robots, operating mechanisms, and automated guided vehicles (AGVs) performing the aforementioned tasks.

[0052] The production workshop management system 1 is a system that outputs instructions to operators or production equipment in the production workshop in response to the status of the production workshop. The production workshop management system 1 includes an acquisition unit 10, a status monitoring unit 20, a countermeasure decision unit 30, a countermeasure adjustment unit 40, an instruction output unit 50, an effect judgment unit 60, an update unit 70, learning models 23, 24, 33, and 34, and a resource database 41. The production workshop management system 1 is implemented by a computer including a processor and memory. The acquisition unit 10, status monitoring unit 20, countermeasure decision unit 30, countermeasure adjustment unit 40, instruction output unit 50, effect judgment unit 60, and update unit 70 are implemented by the processor according to a program stored in memory. Furthermore, the status monitoring unit 20 can be set up independently as a computer or equipped on a production equipment. Additionally, the production workshop management system 1 may have multiple status monitoring units 20. The learning models 23, 24, 33, and 34 and the resource database 41 are stored in memory. The storage of the stored program, learning models 23, 24, 33 and 34 and resource database 41 can be either the same storage or different storage.

[0053] The acquisition unit 10 acquires information used to monitor the status of the production workshop. For example, the acquisition unit 10 acquires information indicating the production status of the production workshop. Specifically, the acquisition unit 10 acquires the results of the production process of the production equipment (specifically, the presence or absence of productivity, quality, or defects) as information indicating the production status of the production workshop. The results of the production process can be either sensor history records obtained by sensors or data input by humans. In addition, for example, the acquisition unit 10 acquires information managed by the production workshop indicating the status of production resources used for production. Production resources include, for example, production equipment, equipment elements, operators, materials, or fixtures. For example, the information indicating the status of production resources can be sensor data such as that from cameras or sensors, or data input by humans. In addition, for example, the acquisition unit 10 acquires information about events that have changed in the production workshop. Specifically, the acquisition unit 10 acquires information indicating that the production equipment has stopped, that the feeders, nozzles, components, or substrates installed on the production equipment have been replaced, that the operators performing the work have changed, and that the operation data of the production equipment has changed.

[0054] The status monitoring unit 20 monitors the status of the production workshop using information acquired by the acquisition unit 10. For example, the status monitoring unit 20 detects a given state based on a first condition used to detect a given state (e.g., the first state or the second state described later) among the states of the production workshop. For example, the first condition is a first learning model associated with a detection threshold corresponding to the given state. Alternatively, the first condition may be a set detection threshold rather than a learning model.

[0055] The status monitoring unit 20 includes a first status monitoring unit 21 and a second status monitoring unit 22. The first status monitoring unit 21 and the second status monitoring unit 22 respectively perform the operations of the status monitoring unit 20 described above.

[0056] The first state monitoring unit 21 monitors a first state in the production workshop. For example, the first state is the production state of the production unit, and the first state monitoring unit 21 monitors the production process as a result of the production state of the production unit. For example, the first state monitoring unit 21 detects a first given state based on a learning model 23. The learning model 23 is a learning model for detecting a first given state that occurs in the production workshop corresponding to the production state of the production unit. Furthermore, the learning model 23 is also a first learning model (i.e., a first condition) that is associated with a detection threshold corresponding to the production state of the production unit. For example, within a given period, the first state monitoring unit 21 detects a first given state corresponding to a production indicator related to at least one of the following: production loss information occurring in the production unit, production quantity information of the products produced in the production unit, and quality information of the products produced in the production unit.

[0057] The second state monitoring unit 22 monitors a second state in the production workshop that differs from the first state. For example, the second state is the state of production resources, and the second state monitoring unit 22 monitors the state of these production resources. For example, the second state monitoring unit 22 detects a second given state based on a learning model 24. The learning model 24 is a learning model used to detect a second given state generated in the production workshop corresponding to the state of the production resources. Furthermore, the learning model 24 is also a first learning model (i.e., a first condition) associated with a detection threshold corresponding to the state of the production resources. For example, the second state monitoring unit 22 detects a second given state corresponding to an operating index related to the operating state of the production equipment included in the production resources. Furthermore, for example, the second state monitoring unit 22 detects a second given state corresponding to an operating index related to the work performed by the operators included in the production resources.

[0058] Here, use Figure 3 An example of the object monitored by the status monitoring unit 20 will be explained.

[0059] Figure 3 This is a diagram illustrating an example of a monitored object of the status monitoring unit 20 according to an embodiment. Additionally, in Figure 3 In this paper, the production equipment is described as the installation equipment and the production process is described as the installation process.

[0060] like Figure 3 As shown, the status monitoring unit 20 (specifically, the first status monitoring unit 21) monitors the results of the installation process, which consists of processes such as adsorption, identification, and installation, as a production status. For example, the first status monitoring unit 21 detects a first given state (specifically, the presence or absence of installation loss (defect loss), the installation quantity (productivity), and the installation quality, etc.) within a given period. This first given state corresponds to a production indicator related to at least one of the following: installation loss information occurring in the installation device, installation quantity information of the installation components installed in the installation device, and quality information of the installation components installed in the installation device.

[0061] Furthermore, the status monitoring unit 20 (specifically, the second status monitoring unit 22) monitors the status of elements (production resources) related to the installation process, such as the substrate, components, operators, heads, nozzles, and feeders, as production resources. For example, the second status monitoring unit 22 detects a second given state corresponding to an operating indicator related to the operating status of the installation equipment included in the production resources (e.g., deterioration of the installation equipment, nozzles, and feeders). Additionally, for example, the second status monitoring unit 22 detects a second given state corresponding to an operating indicator related to the operation performed by the operator on the installation equipment included in the production resources (e.g., operator errors). Furthermore, in addition to operating indicators, it can also detect the following second given states: measurement indicators related to the difference between the values ​​(vertical, horizontal, thickness, coordinate positions of various marks, viscosity) in the design data of the substrate, solder, or component and the values ​​actually measured by cameras and sensors; and time indicators related to the service life date and time of the solder or component and the actual date and time measured.

[0062] Back Figure 2As explained, the countermeasure decision unit 30 determines the countermeasure to be executed from a plurality of countermeasures extracted corresponding to the state of the production workshop monitored by the state monitoring unit 20. The countermeasure to be executed from the plurality of countermeasures corresponds to the first priority instruction, second priority instruction, etc., described later. For example, the countermeasure decision unit 30 determines the countermeasure to be executed based on a second condition used to determine the countermeasure corresponding to a given state (e.g., the first or second countermeasure described later). For example, the second condition includes a second learning model that establishes a correlation between the priority set according to each of the extracted countermeasures and the plurality of countermeasures corresponding to the given state and the priority. For example, the countermeasure decision unit 30 determines the first priority instruction to be executed from the plurality of countermeasures based on the priority order of each of the plurality of countermeasures extracted corresponding to the state of the production workshop monitored by the state monitoring unit 20. In other words, the countermeasure decision unit 30 determines the countermeasure to be executed (i.e., the first priority instruction) from the plurality of countermeasures based on the priority of each of the plurality of countermeasures extracted corresponding to the given state. For example, the countermeasure decision unit 30 analyzes the operation information of the production equipment acquired in the production workshop, the operator information performing operations in the production workshop, and the material information used for the produced goods to determine the countermeasures corresponding to a given state. Furthermore, for the analysis, there are cases where a countermeasure can be determined solely based on the tendency of a given state, and cases where a countermeasure cannot be determined solely based on the tendency of a given state. In the case where a countermeasure cannot be determined solely based on the tendency of a given state, the countermeasure decision unit 30 can determine the countermeasures corresponding to a given state by analyzing the operation information of the production equipment acquired in the production workshop for each production resource, the operator information performing operations in the production workshop, and the material information used for the produced goods, based on event information, and further analyzing the tendency before and after implementing the given countermeasure. Alternatively, an analysis unit independent of the countermeasure decision unit 30 can be used for analysis. Furthermore, for example, the countermeasure decision unit 30 updates the priority used to determine the priority order for the first priority instruction (countermeasure) based on the changes in the state of the production workshop relative to the state before the execution of the first priority instruction, and the state of the production workshop after the execution of the first priority instruction. Furthermore, for example, the strategy decision unit 30 updates the priority based on a learning model used to update the priority. Alternatively, the second condition may not be a learning model, but rather a data table including the priority set for each of the multiple strategies.

[0063] The countermeasure decision unit 30 includes a first countermeasure decision unit 31 and a second countermeasure decision unit 32. The first countermeasure decision unit 31 and the second countermeasure decision unit 32 respectively perform the operations of the countermeasure decision unit 30 described above.

[0064] The first countermeasure decision unit 31 determines the first countermeasure corresponding to the first state monitored by the first state monitoring unit 21. For example, the first countermeasure decision unit 31 determines the first countermeasure to be executed (i.e., the first priority instruction) from among multiple countermeasures extracted corresponding to the first state based on their respective priority order. For example, the first countermeasure decision unit 31 determines a first countermeasure that includes countermeasures to improve the aforementioned production indicators. Specifically, the first countermeasure decision unit 31 determines a first countermeasure for improving MTTR (Mean Time To Recovery). MTTR is an indicator of the maintenance efficiency of a system or equipment; a shorter MTTR means higher maintenance efficiency. For example, the first countermeasure decision unit 31 determines the first countermeasure based on a learning model 33. The learning model 33 is a learning model used to determine the first countermeasure corresponding to the first state; specifically, it is a learning model used to update priorities. Furthermore, the learning model 33 is also a second learning model (i.e., a second condition) that is associated with multiple countermeasures corresponding to a given state and their priorities.

[0065] The second countermeasure decision unit 32 determines the second countermeasure corresponding to the second state monitored by the second state monitoring unit 22. For example, the second countermeasure decision unit 32 determines the second countermeasure (i.e., the first priority instruction) to be executed from among multiple countermeasures extracted corresponding to the second state, based on their respective priority order. For example, the second countermeasure decision unit 32 determines a second countermeasure including production equipment corresponding to the above-mentioned operating indicators, countermeasures (maintenance / replacement) for equipment elements, or whether the operator corresponding to the above-mentioned operating indicators is capable of operating, and job training. Specifically, the second countermeasure decision unit 32 determines a second countermeasure to improve MTBF (Mean Time Between Failures). MTBF is an indicator of the reliability of a system or equipment; a longer MTBF means higher reliability. For example, the second countermeasure decision unit 32 determines the second countermeasure based on a learning model 34. The learning model 34 is a learning model used to determine the second countermeasure corresponding to the second state; specifically, it is a learning model used to update priorities. Furthermore, learning model 34 is also a second learning model (i.e., a second condition) that establishes associations with multiple countermeasures corresponding to a given state and their priorities. In addition, the second countermeasure determined here can also be accomplished by notifying the second countermeasure to a maintenance plan creation device or operator management device that is set up separately from the production workshop management system 1, or by accepting the execution result of the second countermeasure.

[0066] The countermeasures mediation unit 40 mediates between countermeasure 1 and countermeasure 2. Here, using... Figure 3 The reasons for needing the mediation of countermeasures 1 and 2 should be explained in detail.

[0067] For example, such as Figure 3As shown, the results of the adsorption installation process are related to the substrate, components, operator, head, nozzle, and feeder; the results of the identification installation process are related to the components, head, and nozzle; and the results of the installation process are related to the substrate, components, and nozzle. For example, the first countermeasure corresponds to the results of the production process and includes countermeasures for the substrate, components, operator, head, nozzle, or feeder. On the other hand, the second countermeasure also corresponds to the state of the production resources and includes countermeasures for the substrate, components, operator, head, nozzle, or feeder. That is, sometimes the production resources that are the object of the first countermeasure overlap with the production resources that are the object of the second countermeasure. When the production resources that are the object of the first countermeasure overlap with the production resources that are the object of the second countermeasure, it is difficult to execute both the first and second countermeasures simultaneously, and therefore it is necessary to coordinate the first and second countermeasures.

[0068] For example, the countermeasure mediation unit 40 mediates between the first and second countermeasures based on the problem degree set for the first state corresponding to the first countermeasure and the problem degree set for the second state corresponding to the second countermeasure. Furthermore, for example, the countermeasure mediation unit 40 mediates between the first and second countermeasures based on the availability of production resources required for either the first or second countermeasure. The availability of production resources is managed by the resource database 41.

[0069] The instruction output unit 50 outputs a first priority instruction. Specifically, the instruction output unit 50 outputs a first or second countermeasure as the first priority instruction based on the mediation achieved by the countermeasure mediation unit 40. For example, until the effect determination unit 60 (described later) determines the effect of the executed first priority instruction, the instruction output unit 50 does not output a second priority instruction, which is determined from multiple countermeasures and has a priority ranking after the first priority instruction. Furthermore, for example, if the effect determination unit 60 determines, by executing the first priority instruction, that the state of the production workshop after executing the first priority instruction has a given or greater tendency to improve compared to the state of the production workshop before executing the first priority instruction, the instruction output unit 50 does not output a second priority instruction extracted in association with the state of the production workshop corresponding to the first priority instruction, prior to execution. Furthermore, for example, if the effect determination unit 60 determines, by executing the first priority instruction, that the state of the production workshop after executing the first priority instruction does not show any improvement tendency compared to the state before executing the first priority instruction, the countermeasure decision unit 30 determines the second priority instruction to be executed based on the priority order of multiple countermeasures excluding the first priority instruction, and the instruction output unit 50 outputs the second priority instruction. Furthermore, for example, if the effect determination unit 60 cannot determine the effect within a given period, the countermeasure decision unit 30 determines the second priority instruction to be executed based on the priority order of multiple countermeasures excluding the first priority instruction, and the instruction output unit 50 outputs the second priority instruction. The instruction output unit 50 may also output instructions to the control unit of the production equipment, portable terminals held by operators, or production management devices that manage the production equipment, or operator management devices that manage operators.

[0070] The effect determination unit 60 determines the effect of the executed countermeasure (instruction) based on the state of the production workshop before and after executing the determined countermeasure (in other words, the output first priority instruction). Specifically, the effect determination unit 60 determines the effect of the executed first countermeasure or second countermeasure based on at least one of the first state and the second state before and after executing the first countermeasure or second countermeasure corresponding to the output instruction.

[0071] The update unit 70 updates the first and second conditions based on the determined effect, that is, updates the learning models 23, 24, 33 and 34.

[0072] Details of the status monitoring unit 20, countermeasure decision unit 30, countermeasure mediation unit 40, instruction output unit 50, effect judgment unit 60, and update unit 70 will be described later.

[0073] The monitoring of the first state by the first state monitoring unit 21 and the decision on the first countermeasure by the first countermeasure decision unit 31 are performed in parallel, as are the monitoring of the second state by the second state monitoring unit 22 and the decision on the second countermeasure by the second countermeasure decision unit 32. For this purpose, the following is used: Figure 4 Please provide an explanation.

[0074] Figure 4 This is a schematic diagram illustrating the operation flow of the production workshop management system 1 according to the embodiment.

[0075] The production workshop management system 1 performs problem detection by the status monitoring unit 20, decision-making on countermeasures by the countermeasure decision-making unit 30, mediation by the countermeasure mediation unit 40, and countermeasure execution by the instruction output unit 50. These can be applied to the so-called OODA loop, where problem detection corresponds to "Observe", decision-making on countermeasures corresponds to "Orient", mediation corresponds to "Decide", and countermeasure execution corresponds to "Action".

[0076] As described above, the monitoring of the first state by the first state monitoring unit 21 and the determination of the first countermeasure by the first countermeasure decision unit 31 are used to improve MTTR. Figure 4 In this system, the cycle of problem discovery by the first state monitoring unit 21, the determination of countermeasure policy by the first countermeasure decision unit 31, the mediation by the countermeasure mediation unit 40, and the execution of countermeasures by the instruction output unit 50 is defined as the MTTR cycle. As described above, the monitoring of the second state by the second state monitoring unit 22 and the determination of the second countermeasure by the second countermeasure decision unit 32 are used to improve MTBF. Figure 4 In this system, the cycle of problem discovery by the second status monitoring unit 22, the decision of countermeasure policy by the second countermeasure decision unit 32, the mediation by the countermeasure mediation unit 4, and the countermeasure execution by the instruction output unit 50 is set as the MTBF cycle.

[0077] Thus, the monitoring of the first state by the first state monitoring unit 21 and the decision on the first countermeasure by the first countermeasure decision unit 31, and the monitoring of the second state by the second state monitoring unit 22 and the decision on the second countermeasure by the second countermeasure decision unit 32 are performed in parallel. For example, process assurance can be achieved based on the OODA loop from both MTBF and MTTR perspectives.

[0078] Furthermore, by maintaining the independence and parallel execution of problem discovery, countermeasure determination, mediation, and countermeasure implementation for each process within the OODA loop, the waiting time between processes can be minimized, enabling real-time control. Details will be described later; it is possible to adjust priorities and execute countermeasures while adapting to the ever-changing state of the production workshop over time.

[0079] Furthermore, although an example has been given where the first state is the production state of the production apparatus and the second state is the state of the production resource, this is not a limitation. For example, it is also possible that the first state is the production state of the production apparatus, and the second state is the production state of a production apparatus different from the first state. Additionally, for example, it is also possible that the first state is the state of the production resource, and the second state is the state of the production resource different from the first state. For example, in... Figure 4 The example shown illustrates the parallel execution of MTBF and MTTR cycles, but multiple MTBF cycles and multiple MTTR cycles can also be executed in parallel. Furthermore, when MTBF and MTTR cycles are executed in parallel and adjustments are made to the first and second countermeasures, the countermeasure adjustment unit 40 can prioritize the first countermeasure over the second countermeasure. Especially when there is no difference in the problem severity as described below, prioritizing the first countermeasure can maintain the operation of the production unit. "No difference in problem severity" as used herein includes the same problem severity or a difference in problem severity within a given range.

[0080] Next, use Figures 5 to 12 The details of the status monitoring unit 20, the countermeasure decision unit 30, the countermeasure mediation unit 40, the instruction output unit 50, the effect judgment unit 60, and the update unit 70 are explained.

[0081] First, use Figure 5 The details of the status monitoring unit 20 are explained.

[0082] Figure 5 This is a flowchart illustrating an example of the operation of the status monitoring unit 20 involved in the embodiment. Figure 5 This illustrates the handling of observations in the OODA loop.

[0083] First, the status monitoring unit 20 acquires monitoring data (step S1 1). Specifically, the first status monitoring unit 21 acquires monitoring data related to the production status of the production unit, and the second status monitoring unit 22 acquires monitoring data related to the status of production resources.

[0084] Next, the state monitoring unit 20 reads in the learning model (step S12). Specifically, the first state monitoring unit 21 reads in the learning model 23, and the second state monitoring unit 22 reads in the learning model 24.

[0085] Learning model 23 is a learning model used to detect a first given state that occurs in the production workshop corresponding to the production state of the production unit, and is associated with a detection threshold corresponding to the production state of the production unit. For example, learning model 23 is learned such that, through input monitoring data, the output is the first given state (e.g., productivity, quality, or defective loss) represented by the acquired monitoring data, whereby the first given state corresponds to a production indicator related to at least one of the following: information on production loss occurring in the production unit, information on the quantity of products produced in the production unit, and information on the quality of products produced in the production unit. Here, a specific example is given to illustrate the learning method (update method) of learning model 23.

[0086] For example, suppose a decrease in productivity is detected based on a detection threshold corresponding to the productivity associated with the learning model 23, and a strategy to improve productivity is output. Suppose that this increases productivity but decreases quality, i.e., it is effective for productivity but deteriorates for quality. For example, if the learning policy is set to prioritize quality, based on the above effects, the detection threshold corresponding to productivity is relaxed (making it difficult to detect a decrease in productivity). Thus, a detection threshold that achieves a balance between productivity and quality is learned.

[0087] Learning model 24 is a learning model used to detect a second given state that occurs in the production workshop corresponding to the state of production resources, and it is associated with a detection threshold corresponding to the state of the production resources. For example, learning model 24 is trained so that, through input monitoring data, the output is a second given state represented by the acquired monitoring data (e.g., deterioration of production equipment or facilities, or operator error), and the second given state corresponds to an operational indicator related to the operating state of the production equipment included in the production resources, or an operational indicator related to the work performed by the operators included in the production resources. Here, a specific example is given to illustrate the learning method (update method) of learning model 24.

[0088] For example, suppose that a decrease in nozzle flow is detected based on a detection threshold corresponding to the flow rate of the nozzle associated with the learning model 24, and a countermeasure such as maintaining the nozzle within one week is output. For example, suppose that the adsorption error rate deteriorates after the countermeasure is output but before maintenance (before the one-week period has elapsed), and the effect of the output countermeasure is not achieved. In this case, the detection of the decrease in nozzle flow may be too late, so learning is performed based on the above effect to make the detection threshold corresponding to the nozzle flow rate more stringent (i.e., it becomes easier to detect the decrease in nozzle flow rate earlier). Thus, the detection threshold can be learned to enable maintenance at the optimal time. In addition, the detection threshold corresponding to the nozzle flow rate is an example; besides, the above learning can also be applied to setting detection thresholds for deviations in the feeder conveyor belt stop position, deviations in the adsorption position of the part adsorbed by the nozzle, or deviations in the conveying position of the substrate.

[0089] Next, the status monitoring unit 20 determines whether a problem is detected in the first given state or the second given state (step S13). For example, the first status monitoring unit 21 determines whether a decrease in productivity, a decrease in quality, or an increase in defective losses is detected. For example, the second status monitoring unit 22 determines whether a deterioration in the production equipment, a deterioration in equipment components, or an error in the operator's work is detected.

[0090] If no problem is detected (Yes in step S13), the process from step S11 is repeated until a problem is detected.

[0091] If a problem is detected (Yes in step S13), a countermeasure policy for the detected problem is decided.

[0092] Next, use Figure 6 The details of the countermeasures decision-making department 30 will be explained.

[0093] Figure 6 This is a flowchart illustrating an example of the operation of the countermeasure decision unit 30 involved in the implementation. Figure 6 This illustrates the process of determining the orient in the OODA loop.

[0094] The countermeasure decision unit 30 analyzes related production resources (e.g., production resources that may be the cause) in response to the problem detected by the status monitoring unit 20 (step S21). For example, if the first status monitoring unit 21 detects a decrease in productivity during the installation process of the installation device, the production resources analyzed as potentially causing the problem are the substrate, components, operator, head, nozzle, and feeder (see reference). Figure 3Furthermore, for example, if a problem such as nozzle deterioration is detected by the second state monitoring unit 22, the production resource that may be the cause of the problem is the nozzle.

[0095] Next, the strategy decision unit 30 reads in the learning model (step S22). Specifically, the first strategy decision unit 31 reads in the learning model 33, and the second strategy decision unit 32 reads in the learning model 34.

[0096] Learning model 33 is a learning model used to determine the first countermeasure corresponding to the production state of the production unit. Specifically, it is a learning model used to update the priority of determining the priority order for the first countermeasure. For example, learning model 33 is learned such that, upon inputting a detected problem, countermeasures for the detected problem are output as candidates. When multiple candidates are output for a detected problem, multiple countermeasures are extracted corresponding to the multiple candidates. The learning method for learning model 33 will be described later.

[0097] Learning model 34 is a learning model for determining the second strategy corresponding to the state of production resources. Specifically, it is a learning model for updating the priority used to determine the priority order for the second strategy. For example, learning model 34 is learned such that, upon inputting a detected problem, it outputs strategies for the detected problem as candidates. If multiple candidates are output for a detected problem, multiple strategies are extracted corresponding to these candidates. The learning method for learning model 34 will be described later.

[0098] Next, the strategy decision unit 30 analyzes the priority of each of the multiple strategies to determine their respective priority order (step S23). For example, when the learning models 33 and 34 output strategies for the detected problems as candidates, they establish corresponding priorities for the strategies and output them. As a result, the strategy decision unit 30 is able to grasp the priority of each strategy.

[0099] Next, the countermeasures decision-making unit 30 creates a list of candidate countermeasures (step S24). Using... Figure 7 Let's explain the list of candidate countermeasures.

[0100] Figure 7 This is a table showing an example of a list of candidate countermeasures related to the implementation method.

[0101] For example, consider a problem where a deterioration in the suction error rate of the nozzle on the component is detected as a first given state (e.g., productivity, quality, or defective loss). In this case, candidate countermeasures such as suction position teaching, feeder replacement, and nozzle replacement are output from the learning model 33, and priority probabilities are output as the priority of each candidate countermeasure. Thus, the countermeasure decision unit 30 can generate... Figure 7The list of candidate countermeasures is shown below. Figure 7 In the list of candidate countermeasures shown, adsorption location teaching has a priority probability of 60%, making it the highest priority among candidate countermeasures aimed at addressing the problem of worsening adsorption error rates. Alternatively, when there are candidate countermeasures with equal priority probabilities, past performance (number of successful countermeasures, shifts in priority probability, etc.) can also be used to determine the priority.

[0102] Back Figure 6 As explained in the text, next, the countermeasure decision unit 30 registers the highest-priority countermeasure candidate from the created countermeasure candidate list as a countermeasure to the detected problem into the priority countermeasure list (step S25). For example, after creating... Figure 7 In the case of the proposed countermeasure list, to address the problem of worsening adsorption error rate, a countermeasure such as adsorption position teaching is registered in the priority countermeasure list. For example, multiple countermeasures extracted corresponding to the state of the production workshop when a problem of worsening adsorption error rate is detected include adsorption position teaching, feeder replacement, and nozzle replacement. The countermeasure decision unit 30 registers the adsorption position teaching countermeasure in the priority countermeasure list by determining, based on the priority order (priority) of each of the multiple countermeasures, that adsorption position teaching is the first priority instruction to be executed from among the multiple countermeasures.

[0103] Furthermore, repeatedly acquiring monitoring data at given time intervals may detect various problems. For example, sometimes another problem is detected before a solution to one problem is completed. For instance, there may be cases where multiple problems are detected for a first given state (e.g., productivity, quality, or defective losses), and multiple problems are detected for a second given state (e.g., deterioration of production equipment or facilities, or operator error). Thus, whenever a problem is detected, a candidate list of solutions is created, and the highest-priority solution from each candidate list is added to a priority solution list. Here, in Figure 8 The image shows an example of a list of priority countermeasures.

[0104] Figure 8 This is a table showing an example of a list of priority countermeasures involved in the implementation.

[0105] like Figure 8As shown, it is known that, for the problem of the first given state, the countermeasure of teaching the adsorption position is registered in the priority countermeasure list for the problem of the aforementioned deterioration of the adsorption error rate. Furthermore, it is known that, for the problem of the second given state, the countermeasure of cleaning is registered in the priority countermeasure list for the problem of poor feeder sliding. Furthermore, it is known that, for the problem of the second given state, the countermeasure of replacement is registered in the priority countermeasure list for the problem of conveyor belt wear. In addition, for the problems of the first and second given states, a problem level is preset as an indicator of the importance of the problem. For example, the problem of deterioration of the adsorption error rate can be considered a problem of the first state (the production state of the production unit) when the problem is detected, so the problem level set for the problem of deterioration of the adsorption error rate can be considered a problem level set for the first state when the problem is detected. Similarly, for example, the problem of poor feeder sliding can be considered a problem of the second state (the state of production resources) when the problem is detected, so the problem level set for the problem of poor feeder sliding can be considered a problem level set for the second state when the problem is detected.

[0106] Next, use Figure 9 The details of the Countermeasures Mediation Department 40 will be explained.

[0107] Figure 9 This is a flowchart illustrating an example of the operation of the countermeasure mediation unit 40 involved in the implementation. Figure 9 This illustrates the handling of Decide in the OODA loop.

[0108] First, the countermeasures mediation unit 40 reads in the priority countermeasures list (step S31) and selects the countermeasures with the highest priority (i.e., problem degree) (step S32). For example, the read-in priority countermeasures list is... Figure 8 In the case of the list shown, the countermeasure mediation unit 40 selects the adsorption position for teaching as the countermeasure with the highest priority.

[0109] Next, the countermeasures and mediation department 40 reads resource data (resource management table) from the resource database 41 (step S33). Figure 10 Let's explain the resource management forms.

[0110] Figure 10 This is an example of a resource management table involved in an implementation method.

[0111] For example, resource management forms manage the presence or absence of various production resources; specifically, they manage whether a certain countermeasure is currently being implemented for each production resource, or whether a certain countermeasure is currently being implemented against each production resource. Figure 10 The presence or absence of production resources is indicated by the opening and closing of the lock. Figure 10 The resource management table shown manages the presence or absence of the head, nozzle, feeder, and operators A and B as production resources. Regarding the head and feeder, if a certain countermeasure is currently in effect, the lock is set to "open." Regarding the nozzle, if no countermeasure is currently in effect, the lock is set to "closed." Regarding operators A and B, if no countermeasure is currently in effect, the lock is set to "closed." The term "lock" here can also refer to either or both of the physical and imaginary spaces. For example, prohibiting the removal of a feeder from the production unit until the lock is closed refers to a lock in the physical space. Furthermore, prohibiting the use of a feeder with a locked resource during production planning or updates refers to a lock in the imaginary space.

[0112] Back Figure 9 As explained in the description, next, the countermeasures adjustment unit 40 determines whether the production resources are locked for the selected countermeasure (step S34). For example, suppose the countermeasures adjustment unit 40 selects adsorption position teaching. Furthermore, for example, adsorption position teaching is set as a countermeasure performed by operator A. In this case, the countermeasures adjustment unit 40 checks the locked status of operator A in the read resource management table.

[0113] If the production resources for the selected countermeasure are locked (Yes in step S34), the countermeasure mediation unit 40 selects the countermeasure with the second highest priority (step S35) and performs the processing from step S33 onwards again.

[0114] If the production resources for the selected countermeasure are not locked (No in step S34), the countermeasure mediation unit 40 will lock the production resources for the selected countermeasure (step S36).

[0115] Then, it is determined whether the production resources for all countermeasures included in the priority countermeasure list are locked (step S37). If the production resources for all countermeasures are not locked (No in step S37), the selected countermeasure is excluded, and the process from step S32 is repeated. If the production resources for all countermeasures are locked (Yes in step S37), the countermeasure with the highest priority among the countermeasures in the priority countermeasure list whose production resources are not locked is executed.

[0116] Next, use Figure 11 The details of the instruction output unit 50, the effect judgment unit 60, and the update unit 70 are explained.

[0117] Figure 11 This is a flowchart illustrating an example of the operation of the instruction output unit 50, effect determination unit 60, and update unit 70 involved in the embodiment. Figure 11The execution of countermeasures in the OODA loop and the processing after the countermeasures are executed are shown. Furthermore, regarding the problem of worsening adsorption error rate, the case where the countermeasure selected by the countermeasure adjustment unit 40 is adsorption position teaching and the locked production resource is operator A is referred to as Case 1. Regarding the problem of feeder slippage, the case where the countermeasure selected by the countermeasure adjustment unit 40 is cleaning and the locked production resources are the feeder and operator B is referred to as Case 2.

[0118] First, the instruction output unit 50 executes countermeasures for the production resources locked by the countermeasure adjustment unit 40 (step S41). For example, in specific example 1, the instruction output unit 50 outputs a first countermeasure (e.g., a first priority instruction) that causes operator A to perform adsorption position teaching. For example, in specific example 2, the instruction output unit 50 outputs a second countermeasure (e.g., a first priority instruction) that causes operator B to perform feeder cleaning. Thus, instructions corresponding to the countermeasures are output and executed. In addition, the execution of the instructions can be performed manually by operators or automatically by production equipment.

[0119] Next, the effect determination unit 60 acquires monitoring data (step S42). Specifically, the effect determination unit 60 acquires monitoring data related to the production status of the production unit or the status of production resources. The effect determination unit 60 acquires monitoring data to confirm changes in the state of the production workshop caused by the execution of instructions corresponding to countermeasures, that is, to determine the effect of instructions corresponding to the executed countermeasures. For example, in specific example 1, the effect determination unit 60 acquires monitoring data on the results of the installation process related to adsorption. That is, the effect determination unit 60 uses the loss information associated with the nozzle of the monitored object as monitoring data and monitors its trend. For example, in specific example 2, the effect determination unit 60 acquires monitoring data on the status of the feeder. That is, the effect determination unit 60 uses the loss information associated with the feeder of the monitored object as monitoring data and monitors its trend. For example, the effect determination unit 60 uses the learning model 23 or 24 to detect the first given state or the second given state, similar to the status monitoring unit 20.

[0120] Next, the effect determination unit 60 determines whether a problem is detected in the first given state or the second given state (step S43). If a problem is detected, it can be determined that there is no effect corresponding to the instruction of the executed countermeasure, or that the effect corresponding to the instruction of the executed countermeasure is not manifested. If no problem is detected, it can be determined that there is an effect corresponding to the instruction of the executed countermeasure.

[0121] If no problem is detected (No in step S43), the update unit 70 updates the learning model 33 or 34 based on the determined effect (step S44). For example, in specific example 1, if no problem is detected, the update unit 70 determines that the adsorption position teaching is effective for the problem and updates the learning model 33 to increase the priority of the adsorption position teaching. For example, in specific example 2, if no problem is detected, the update unit 70 determines that cleaning is effective for the problem and updates the learning model 34 to increase the priority of cleaning.

[0122] Next, since the instruction has been completed, the effect determination unit 60 will release the locks on the production resources locked during the execution of this instruction (step S45). For example, in specific example 1, the lock on operator A will be released. For example, in specific example 2, the locks on operator B and the feeder will be released.

[0123] Next, the effect determination unit 60 removes the countermeasure to be executed by this instruction from the priority countermeasure list (step S46). For example, in specific example 1, the adsorption position teaching is removed from the priority countermeasure list. For example, in specific example 2, cleaning is removed from the priority countermeasure list.

[0124] Then, the effect determination unit 60 deletes the candidate list of countermeasures for problems not detected by the current indication (step S47). For example, in the case of specific example 1, a problem such as the deterioration of the adsorption error rate was not detected, and no countermeasure is needed for this problem, so it is deleted. Figure 7 The countermeasure candidate list is shown. Deleting a countermeasure candidate means that if the effect determination unit 60 determines that, due to the execution of the first priority instruction (adsorption position teaching instruction), the adsorption error rate after the execution of the adsorption position teaching instruction shows a given or greater tendency to improve compared to the state (adsorption error rate) before the execution of the adsorption position teaching instruction, the instruction output unit 50 does not output the second priority instruction (feeder change or nozzle change instruction) extracted in relation to the adsorption error rate corresponding to the adsorption position teaching instruction. Furthermore, in addition to issues for which countermeasures have been implemented, the effect determination unit 60 can also determine whether the problems indicated in the priority countermeasure list continue. In addition to issues for which countermeasures have been implemented, the effect determination unit 60 can also delete priority countermeasures for problems for which no problems have been detected. Based on the detected problems, there is a correlation, and efficient countermeasures can be executed for such problems.

[0125] On the other hand, if a problem is detected (as in step S43), the effect determination unit 60 determines whether a timeout has occurred (step S48). In other words, the effect determination unit 60 determines whether the effect cannot be determined within a given time. Sometimes, a certain amount of time is required from the execution of the instruction to the manifestation of the effect, and therefore the processing in step S48 is performed. Regarding the given period, for example, the time required to obtain the effect is set according to each instruction. Alternatively, as a countermeasure added to production plans and maintenance plans, for instructions that are not performed immediately, a plan for performing the instruction can be created, and the effect determination can be performed after the production resources are released and the plan is executed.

[0126] If no problem is detected before the timeout (No in step S48), or until the timeout occurs, repeat the processes in steps S42, S43, and S48.

[0127] In the event of a timeout (as in step S48), the update unit 70 updates the learning model 33 or 34 based on the determined effect (step S49). For example, in specific example 1, if a timeout occurs due to a problem being detected, the update unit 70 determines that adsorption position teaching is ineffective and updates the learning model 33 to lower the priority of adsorption position teaching. For example, in specific example 2, if a timeout occurs due to a problem being detected, the update unit 70 determines that cleaning is effective and updates the learning model 34 to lower the priority of cleaning. Furthermore, if a problem is detected but there is a tendency for improvement in the monitoring data (with the following improvement tendency given), the update unit 70 updates the learning model 34 to reduce the degree of priority reduction.

[0128] Next, since the instruction has been completed, the effect determination unit 60 will release the locks on the production resources that were locked when the instruction was executed (step S50). For example, in specific example 1, the lock on operator A will be released. For example, in specific example 2, the locks on operator B and the feeder will be released.

[0129] Next, the effect determination unit 60 removes the countermeasure to be executed by this instruction from the priority countermeasure list (step S51). For example, in specific example 1, the adsorption position teaching is removed from the priority countermeasure list. For example, in specific example 2, cleaning is removed from the priority countermeasure list.

[0130] Next, the effect determination unit 60 updates the list of candidate countermeasures for problems that would be detected even if the current instruction were executed (step S52). Here, using Figure 12 The updating of the candidate countermeasure list in the case of Specific Example 1 will be explained.

[0131] Figure 12 This is a table showing an example of an updated list of countermeasure candidates related to the implementation method.

[0132] For example, in cases where a deterioration in the adsorption error rate can be detected even when the instruction to teach the adsorption position is executed, such as... Figure 12 As shown, the adsorption location is removed from the countermeasure candidate list as a countermeasure candidate. Furthermore, from the creation... Figure 7 The countermeasure candidate list shown has been in place for some time, during which production has continued in the production workshop. Therefore, the status of the feeder and nozzle changes, and consequently, the priority of feeder and nozzle replacements may also change. Therefore, the effect determination unit 60 can also perform priority analysis and update the priority in the countermeasure candidate list. For example, if it is known that... Figure 7 In the candidate countermeasure list shown, the priority ratio (priority probability) of feeder replacement versus nozzle replacement is 3:1, but... Figure 12 The ratio of candidate countermeasures shown is 2:3.

[0133] Back Figure 11 As explained in the description, the effect determination unit 60 registers the highest-priority countermeasure candidate from the created countermeasure candidate list as a countermeasure to the detected problem in the priority countermeasure list (step S53). For example, in the creation of... Figure 12 In the case of the proposed countermeasure list shown, to address the problem of worsening adsorption error rate, a countermeasure such as nozzle replacement is registered in the priority countermeasure list. That is, to address the problem of continued worsening of the adsorption error rate after adsorption position teaching, an instruction to replace the nozzle can be output.

[0134] This means that since the effect determination unit 60 determines the effect of the executed first priority instruction (adsorption position teaching), the actions after step S50 are not executed. Therefore, the instruction output unit 50 does not output the second priority instruction (feeder replacement or nozzle replacement) which is determined from the multiple countermeasures (adsorption position teaching, feeder replacement, and nozzle replacement) and has a priority after the adsorption position teaching instruction. This is so that the nozzle replacement instruction can be output after it is determined that the adsorption position teaching has no effect.

[0135] Furthermore, this means that if the effect determination unit 60 determines that by executing the first priority instruction (adsorption position teaching), there is no improvement tendency in the adsorption error rate after executing the adsorption position teaching relative to the state before executing the adsorption position teaching, the countermeasure determination unit 30 determines the second priority instruction (adsorption position teaching) to be executed based on the priority order of each of the multiple countermeasures (feeder replacement and nozzle replacement) excluding adsorption position teaching, and the instruction output unit 50 outputs an instruction for nozzle replacement. This is to output an instruction for nozzle replacement that has the highest priority after adsorption position teaching.

[0136] Furthermore, this means that if the effect determination unit 60 cannot determine the effect within a given period, the countermeasure decision unit 30 determines the second priority instruction (nozzle replacement) to be executed based on the priority order of each of the multiple countermeasures (feeder replacement instruction and nozzle replacement) excluding the first priority instruction (adsorption position teaching), and the instruction output unit 50 outputs the nozzle replacement instruction. This is so that after the timeout, the nozzle replacement instruction with the highest priority among the multiple countermeasures excluding adsorption position teaching is output.

[0137] Additionally, sometimes in step S13, the status monitoring unit 20 detects a problem where, after a high-priority countermeasure from the countermeasure candidate list for that problem has been registered in the priority countermeasure list, the registered countermeasure has a low priority, and production resources for the registered countermeasure have been locked, thus preventing the registered countermeasure from being executed smoothly. In such cases, sometimes the problem corresponding to the unexecuted countermeasure is resolved by using countermeasures for other problems that were executed first. In this case, the registered countermeasure can also be removed from the priority countermeasure list before execution, and the countermeasure candidate list is also deleted.

[0138] As explained above, the effectiveness of countermeasures can be determined by observing whether the state of the production workshop changed before and after implementing them, and how it changed if it did. When the problem itself in the production workshop changes, the effectiveness of the countermeasures also changes. Therefore, based on the determined effectiveness, conditions 1 and 2 can be updated to optimal conditions. Thus, optimal work instructions can be output corresponding to changes in the problem itself.

[0139] (Other implementation methods)

[0140] The production workshop management system 1 of this disclosure has been described above based on the embodiments, but this disclosure is not limited to the above embodiments. As long as it does not depart from the spirit of this disclosure, various modifications that can be conceived by those skilled in the art to implement the embodiments, as well as ways of constructing by combining the constituent elements of different embodiments, are also included within the scope of this disclosure.

[0141] For example, in the above embodiment, an example of the production workshop management system 1 having learning models 23, 34, 33 and 34 has been described, but it is also possible not to have learning models 23, 34, 33 and 34.

[0142] For example, in the above embodiment, an example was described where the first state is the production state of the production device and the second state is the state of the production resources, but this is not a limitation. For example, it is not particularly limited as long as the first state and the second state are different states in the production workshop.

[0143] For example, in the above embodiment, the production workshop management system 1 is described as having an acquisition unit 10, a status monitoring unit 20, a countermeasure decision unit 30, a countermeasure adjustment unit 40, an instruction output unit 50, an effect judgment unit 60, and an update unit 70. However, the production device may also have some of these components. For example, the production device may also have an acquisition unit 10, a status monitoring unit 20, and a countermeasure decision unit 30.

[0144] For example, the instructions corresponding to the countermeasures can consist of multiple instructions. Furthermore, the instructions corresponding to the countermeasures can also be output to multiple production units or portable terminals held by multiple operators.

[0145] For example, this disclosure can be implemented not only as a production workshop management system 1, but also as a work countermeasure decision method that includes the steps (processes) performed by each constituent element constituting the production workshop management system 1.

[0146] Figure 13 This is a flowchart illustrating an example of a work countermeasure determination method involved in other embodiments.

[0147] Work strategy decision-making methods are work strategy decision-making methods in production workshop management systems that manage the status of production workshops equipped with production facilities for producing products, such as... Figure 13 As shown, the process includes: monitoring the aforementioned state, detecting a given state based on a first condition for detecting a given state among the aforementioned states (step S1), determining a countermeasure to be executed based on a second condition for determining a countermeasure corresponding to the given state (step S2), judging the effect of the executed countermeasure based on the aforementioned state before and after executing the determined countermeasure (step S3), and updating the first condition and the second condition based on the judged effect (step S4).

[0148] For example, the steps in the job strategy decision-making method can also be executed by a computer (computer system). Furthermore, this disclosure can be implemented as a program for causing a computer to perform the steps included in the job strategy decision-making method. Further, this disclosure can be implemented as a non-transitory, computer-readable recording medium such as a CD-ROM containing the program.

[0149] For example, in the case where this disclosure is implemented by a program (software), the program is executed using the computer's hardware resources such as the CPU, memory, and input / output circuits, thereby executing each step. That is, the CPU retrieves data from the memory or input / output circuits, performs calculations, and outputs the calculation results to the memory or input / output circuits, thereby executing each step.

[0150] Furthermore, the components of the production workshop management system 1 described in the above embodiment can also be implemented as dedicated or general-purpose circuits.

[0151] Furthermore, each component of the production workshop management system 1 described in the above embodiment can also be implemented as an LSI (Large Scale Integration) of an integrated circuit (IC).

[0152] Furthermore, integrated circuits are not limited to LSIs; they can also be implemented using dedicated circuits or general-purpose processors. Programmable FPGAs (Field Programmable Gate Arrays) or the interconnection of circuit cells within LSIs can also be utilized, along with the configuration of reconfigurable processors.

[0153] Furthermore, if the technology of replacing LSI with integrated circuit technology through advancements in semiconductor technology or other derived technologies emerges, then of course this technology can also be used to integrate the various components included in the production workshop management system 1.

[0154] In addition, this disclosure also includes various modifications that can be conceived by those skilled in the art to implement the embodiments, and methods that are implemented by arbitrarily combining the constituent elements and functions of each embodiment without departing from the spirit of this disclosure.

[0155] Industrial availability

[0156] This disclosure can be used, for example, for the management of production workshops.

[0157] -Symbol Explanation-

[0158] 1. Production Workshop Management System

[0159] 2. Communication Network

[0160] 4. Install the production line

[0161] 5. Management Device

[0162] 10 Acquisition Department

[0163] 20 Status Monitoring Department

[0164] 21. First Status Monitoring Unit

[0165] 22. Second Status Monitoring Unit

[0166] Learning models 23, 24, 33, and 34

[0167] 30 Countermeasures Decision-Making Department

[0168] 31 First Countermeasures Decision-Making Department

[0169] 32 Second Countermeasures Decision-Making Department

[0170] 40. Mediation Department

[0171] 41 Resource Database

[0172] 50 Indicator Output Section

[0173] 60 Effect Judgment Department

[0174] 70 Update Department

[0175] M1 substrate supply device

[0176] M2 substrate receiving device

[0177] M3 Printing Unit

[0178] M4 and M5 mounting devices

[0179] M6 Reflow Soldering Unit

[0180] M7 substrate recycling device.

Claims

1. A production workshop management system, which manages the status of a production workshop, wherein the production workshop is equipped with production equipment for producing goods. The production workshop management system has the following features: A state monitoring unit monitors the state and detects the given state based on a first condition for detecting a given state among the states; The countermeasure decision unit determines the countermeasure to be executed based on a second condition used to determine the countermeasure corresponding to the given state; The effect determination unit determines the effect of the executed countermeasure based on the state before and after the countermeasure is executed. and The updating unit updates the first condition and the second condition based on the determined effect. There are multiple countermeasures. The second condition includes a priority set according to each of the plurality of said countermeasures. The strategy decision-making unit determines the strategy to be output from among the multiple strategies extracted corresponding to the given state, based on the respective priorities of each of the multiple strategies. The first condition is a first learning model that is associated with a detection threshold corresponding to the given state. Based on the determined effect, the updating unit updates the detection threshold in the first learning model. The second condition is a second learning model that establishes an association with multiple strategies corresponding to the given state and the priority. The updating unit updates the priority of each of the multiple strategies in the second learning model based on the determined effect.

2. The production workshop management system according to claim 1, wherein, The detection threshold corresponding to the given state includes any one of the following: the detection threshold corresponding to the flow rate of the suction nozzle of the production device, the detection threshold corresponding to the deviation of the stop position of the conveyor belt of the feeder of the production device, the detection threshold corresponding to the deviation of the adsorption position of the component adsorbed by the suction nozzle, or the detection threshold corresponding to the deviation of the conveying position of the substrate.

3. The production workshop management system according to claim 1 or 2, wherein, The countermeasure decision unit analyzes the operation information of the production equipment obtained in the production workshop, the operator information of the operation in the production workshop, and the material information of the product to determine the countermeasure corresponding to the given state.

4. A method for determining work strategies, which is a method for determining work strategies in a production workshop management system for managing the status of a production workshop, wherein the production workshop has production equipment for producing products. The method for determining operational countermeasures includes: Monitor the state, and detect the given state based on a first condition for detecting a given state among the states; The strategy to be executed is determined based on the second condition used to determine the strategy corresponding to the given state; Based on the states before and after the countermeasures are implemented, the effect of the implemented countermeasures is determined. and The first condition and the second condition are updated based on the determined effect. The proposed countermeasures are multiple. The second condition includes a priority set according to each of the plurality of said countermeasures. Based on the priority of each of the multiple strategies extracted corresponding to the given state, the strategy to be output is determined from among the multiple strategies. The first condition is a first learning model that is associated with a detection threshold corresponding to the given state. Based on the determined effect, the detection threshold in the first learning model is updated. The second condition is a second learning model that establishes an association with multiple strategies corresponding to the given state and the priority. Based on the determined effect, the priority of each of the multiple strategies in the second learning model is updated.

5. A computer-readable recording medium containing a job strategy decision program that causes a computer to execute the job strategy decision method of claim 4.

Images