Management device, management method, and program

Abstract

To provide a management device and the like capable of detecting problems related to production costs on a production line.SOLUTION: A management device 100 includes a monitoring unit 110 that monitors the production status in a production line 200 that produces circuit boards by mounting a component on a board, a setting unit 120 that sets a first production cost required when producing the circuit board, and a problem detection unit 130 that detects a problem related to the production cost by comparing a second production cost based on the production status with the first production cost.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a management device, a management method, and a program. [Background technology]

[0002] Patent Document 1 discloses a production line consisting of multiple production devices. An integrated control device capable of communicating with the production line is connected to the production line. When the integrated control device acquires information indicating the production status of the multiple production devices, including multiple different abnormalities, it displays information indicating the production device that should perform processing to deal with the abnormality on each display device provided in each production device. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2012-145997 Summary of the Invention [Problem to be solved by the invention]

[0004] The integrated control device in Patent Document 1 detects abnormalities in production equipment based on, for example, a decrease in productivity. However, the integrated control device detects abnormalities without considering production costs. Therefore, the integrated control device cannot determine the magnitude of the problem related to production costs, for example, when an error occurs in an expensive part versus an inexpensive part. Therefore, if an abnormality is detected uniformly based solely on productivity, there is a risk that production costs will increase due to measures to address the abnormality. Therefore, it is desirable to be able to detect problems related to production costs in order to improve the production status of the production line.

[0005] The present invention provides a management device and the like that can detect problems related to production costs on a production line. [Means for solving the problem]

[0006] A management device according to one embodiment of the present invention includes a monitoring unit that monitors the production status of a production line that produces circuit boards by mounting components on boards, a setting unit that sets a first production cost required when producing the circuit boards, and a problem detection unit that detects problems related to production costs by comparing a second production cost based on the production status with the first production cost.

[0007] A management method according to one embodiment of the present invention detects problems related to production costs by monitoring the production status of a production line that produces circuit boards by mounting components on boards, setting a first production cost required when producing the circuit boards, and comparing a second production cost based on the production status with the first production cost.

[0008] A program according to one aspect of the present invention is a program for causing a computer to execute the above-described management method. [Effects of the Invention]

[0009] According to the present invention, it is possible to provide a management device or the like that can detect problems related to production costs on a production line. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing a schematic configuration of a mounting system according to an embodiment. [Figure 2] FIG. 2 is a block diagram showing a mounting system according to an embodiment. [Figure 3] FIG. 3 is a diagram for explaining productivity and production costs according to the embodiment. [Figure 4] FIG. 4 is a diagram for explaining productivity and production costs according to the embodiment. [Figure 5] FIG. 5 is a diagram for explaining productivity and production costs according to the embodiment. [Figure 6] FIG. 6 is a diagram for explaining productivity according to the embodiment. [Figure 7] FIG. 7 is a sequence diagram showing a processing procedure of the mounting system according to the embodiment. [Figure 8] FIG. 8 is a flowchart illustrating a specific example of the problem detection process executed by the management device according to the embodiment. [Figure 9] FIG. 9 is a flowchart showing a management method according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Note that each of the embodiments described below represents a specific example of the present invention. Therefore, the numerical values, shapes, materials, components, component arrangements and connection forms, steps, and step sequences shown in the following embodiments are merely examples and are not intended to limit the present invention. Therefore, among the components in the following embodiments, components that are not recited in the independent claims of the present invention will be described as optional components.

[0012] Furthermore, each drawing is a schematic diagram and is not necessarily drawn to precise scale, dimensions, etc. Furthermore, in each drawing, the same components are denoted by the same reference numerals.

[0013] Furthermore, in this specification, terms indicating relationships between elements, such as parallel and the same, as well as numerical values ​​and numerical ranges, are not expressions that express only the strict meaning, but are expressions that also include a substantially equivalent range, for example, a difference of about several percent (or about 10%).

[0014] Furthermore, in this specification, ordinal numbers such as "first" and "second" do not refer to the number or order of components unless otherwise specified, but are used to avoid confusion and distinguish between components of the same type.

[0015] Furthermore, in this specification, when a comparison is made, for example, with "above a threshold" or "below a threshold," it means that the distinction is made at the threshold, and may mean "greater than the threshold" or "below the threshold," respectively.

[0016] (Embodiment) [composition] First, the configuration of a mounting system according to an embodiment will be described.

[0017] Fig. 1 is a diagram showing a schematic configuration of a mounting system 10 according to an embodiment. Fig. 2 is a block diagram showing the mounting system 10 according to an embodiment.

[0018] The mounting system 10 is a system for producing circuit boards for electronic devices such as smartphones or personal computers, and produces circuit boards by mounting components such as integrated circuits (ICs), semiconductors, capacitors, and resistors on the boards.

[0019] The mounting system 10 includes a production line 200, a display unit 210, and a management device 100.

[0020] The production line 200 is a production facility that produces circuit boards by mounting components on boards. As shown in Figure 1, the production line 200 includes, for example, a board stocker M1, an adhesive application device M2, a solder paste printing device M3, component mounting devices M4 and M5, a reflow device M6, and an appearance inspection device M7.

[0021] Production line 200 is configured, for example, by connecting multiple production devices in series. In production line 200, boards are transported sequentially from board stocker M1 located upstream to downstream production devices, where components are mounted on the boards. For example, component mounting device M4 is equipped with a mounting head that picks up components and mounts them on the boards. Component mounting device M4 mounts components on boards transported from upstream production devices, and then transports the boards with the mounted components to downstream devices.

[0022] Each production device, including the board stocker M1, adhesive application device M2, solder paste printing device M3, component mounting devices M4 and M5, reflow device M6, and visual inspection device M7, is communicably connected via a communication network to a management device 100 that manages each production device. Each production device transmits information (hereinafter simply referred to as the production status) indicating the production status (also referred to as the production situation) that indicates, for example, the progress of processing in that device and any abnormalities that have occurred in that device to the management device 100. In this way, the management device 100 monitors the production status of the production line 200.

[0023] The above-described plurality of production devices provided in the production line 200 are merely examples. The production devices provided in the production line 200 may be any known production devices used in known production lines (mounting lines).

[0024] The display unit 210 is a display for displaying various types of information. For example, the display unit 210 displays an image of information indicating a production cost (specifically, a second production cost) described below. For example, when the display unit 210 acquires information from the management device 100 and each production device of the production line 200, it displays the acquired information.

[0025] The mounting system 10 may be equipped with one or more display units 210. For example, the mounting system 10 may be equipped with a display unit 210 for each production device included in the production line 200. For example, the display unit 210 may be disposed near each production device. This makes it easier to notify information from the management device 100 to each operator who operates each production device.

[0026] Management device 100 is a device that manages the production devices provided in production line 200. For example, management device 100 monitors the production status, such as errors that occur in production line 200. Management device 100 also transmits data to the production devices to control their operation and processing. Storage unit 150 stores data indicating production conditions for each type of board, such as information indicating a component ID, which is the type of component to be mounted on the board, and information indicating an arrangement number, which is the position where a feeder that supplies the components is attached. Furthermore, storage unit 150 stores component library data, which is composed of items that indicate characteristics such as the shape of the component, for each component ID.

[0027] The management device 100 is realized by a computer that includes, for example, a communication interface for communicating with the production line 200, a non-volatile memory that stores programs executed by each processing unit, a volatile memory that is a temporary storage area for executing the programs, an input / output port for sending and receiving signals, and a processor that executes the programs. The communication interface may be realized by a connector to which a communication line is connected for wired communication, or by a wireless communication circuit for wireless communication.

[0028] The management device 100 includes a monitoring unit 110 , a setting unit 120 , a problem detection unit 130 , an output unit 140 , and a storage unit 150 .

[0029] The monitoring unit 110 is a processing unit that monitors the production line 200. Specifically, the monitoring unit 110 monitors the production status of the production line 200, which produces circuit boards by mounting components on boards. More specifically, the monitoring unit 110 monitors the production status of the production line 200 by acquiring performance information from each production device included in the production line 200. For example, the monitoring unit 110 monitors the production status by counting the number of errors that indicate the occurrence of errors for each type of component. Note that the monitoring unit 110 may reset the count of the number of errors to 0 when the placement number of a feeder corresponding to a component ID is changed. This is because, when the feeder attachment location is changed in this way, errors caused by the difference between the center position of the outer shape of a component actually supplied by the feeder and the ideal design value are eliminated, making it unnecessary for an operator to take action. Here, the number of errors is not limited to the number of times an error occurred, but may also be the probability of an error occurring per unit time calculated from the number of times an error occurred, or a value obtained by dividing the number of times an error occurred by the number of times components were fed by the feeder.

[0030] The setting unit 120 is a processing unit that sets a first production cost required when producing a circuit board.

[0031] The first production cost is, for example, the amount of loss allowed in the production of circuit boards by production line 200. More specifically, it is an expense calculated based on information indicating the number of errors that have occurred and the unit price of each component, which information is input by an operator before production of circuit boards begins on production line 200. Setting unit 120 sets the first production cost by storing the amount of loss calculated in this manner for each type of component in storage unit 150.

[0032] Furthermore, for example, the setting unit 120 sets a first productivity required when producing circuit boards. The setting unit 120 sets the first productivity by storing the productivity for each type of board in the storage unit 150.

[0033] In this embodiment, productivity refers to performance in terms of time involved in the production of circuit boards. Productivity (specifically, a productivity index) is, for example, the time at which production is completed. Productivity may be the cycle time of the production line 200 (more specifically, a production device on the production line 200 that is a bottleneck in the production of circuit boards), or the availability rate of the production line 200.

[0034] The first productivity is, for example, the ideal production completion time of the circuit boards by the production line 200. More specifically, it is the production completion time calculated based on data indicating the production conditions stored in the storage unit 150. Note that the first productivity may be the time from the start to the end of the production of the circuit boards.

[0035] The management device 100 may be connected to a user interface (not shown) such as a mouse and keyboard for setting the first productivity and the first production cost.

[0036] The storage unit 150 also stores a production plan. The production plan may include the total number of boards to be produced, the number of components used per board, and the cycle time of a production device that is a bottleneck in the production line 200 (i.e., the production device that takes the longest processing time among the production devices included in the production line 200). In these cases, for example, the setting unit 120 may calculate (set) the first productivity and the first production cost based on the production plan.

[0037] The problem detection unit 130 is a processing unit that detects problems related to production costs. Specifically, the problem detection unit 130 detects problems related to production costs by comparing a second production cost based on the production status with the first production cost.

[0038] The second production cost is, for example, the production cost incurred when the circuit board is actually produced. The problem detection unit 130 calculates the second production cost based on, for example, the production status. For example, the problem detection unit 130 calculates the second production cost based on information indicating an error related to component pickup monitored as the production status and information indicating the unit price of the component in which the error occurred, and detects a problem related to the production cost based on the calculated second production cost. For example, the information indicating an error related to component pickup monitored as the production status (hereinafter also referred to as error information) is the number of times an error has occurred, indicating the occurrence status of errors for each type of component.

[0039] More specifically, the problem detection unit 130 calculates the loss amount for each type of component as the second production cost based on the error information and information indicating the unit price (cost [yen / number of components]) of the component in which the error occurred. If information indicating the unit price of the component is not stored in the storage unit 150, the problem detection unit 130 may automatically rank the components and determine the unit price of the components based on a priority according to their conditions. The component conditions may be determined arbitrarily and are not particularly limited. For example, the component conditions may be the type of component included in the component library data, the outer shape of the component, or the weight of the component. Information indicating the component conditions may be stored in the storage unit 150 in advance. The priority according to the component conditions may be determined arbitrarily and are not particularly limited. For example, the component conditions may be set as "high priority: 3 / 100," "medium priority: 6 / 100," or "low priority: 9 / 100."

[0040] Additionally, information indicating the unit price of the part may be obtained from a learning model.

[0041] The learning model is, for example, a machine learning model generated by learning information indicating the unit price of a part and the type of the part as supervised data. The learning model, for example, receives the production conditions of the production line 200 as input and outputs information indicating the unit price of the part. In this way, for example, the information indicating the unit price of the part is obtained by inputting the production conditions of the production line 200 into the learning model generated by learning information indicating the unit price of the part and the type of the part as supervised data.

[0042] The production conditions are, for example, information indicating the types of components used in the mounting. The information indicating the production conditions may be stored in the storage unit 150, or may be acquired by the problem detection unit 130 by being input by an operator via a user interface or the like.

[0043] The learning model is, for example, a machine learning model that uses a neural network such as deep learning (for example, a convolutional neural network), but may be another machine learning model. The learning model may be stored in the storage unit 150. For example, the problem detection unit 130 inputs production conditions into the learning model to obtain information indicating the unit price of parts from the learning model.

[0044] The second production cost may be acquired from the production line 200 by, for example, the monitoring unit 110 as an example of the production state.

[0045] The second production cost may also be the production cost predicted to be incurred until production is finally completed on production line 200. For example, the second production cost may be calculated based on the production cost incurred when the circuit boards are actually produced and the number of components remaining that have not yet been mounted on the boards and / or the number of boards remaining for which production has not been completed. For example, problem detection unit 130 calculates the second production cost based on the number of components that will be mounted on the boards after the production status is acquired, in addition to the error information and information indicating the unit prices of the components.

[0046] The problem regarding the production cost is, for example, the difference between the target production cost and the current production cost. For example, the problem detection unit 130 detects a problem regarding the production cost when the second production cost, which is the loss amount based on the production status, is higher than the first production cost, which is the allowable loss amount.

[0047] For example, the problem detection unit 130 determines whether the second production cost is higher than the first production cost. For example, if the second production cost is higher than the first production cost, the problem detection unit 130 determines that there is a problem with the production cost. On the other hand, for example, if the second production cost is equal to or less than the first production cost, the problem detection unit 130 determines that there is no problem with the production cost.

[0048] The problem regarding production costs may be a cause that arises when there is a difference between the target production cost and the current production cost.

[0049] Furthermore, for example, the problem detection unit 130 detects a problem related to productivity by comparing a second productivity based on the production status with the first productivity.

[0050] A problem related to productivity is, for example, a difference between a productivity target and the current productivity. For example, the problem detection unit 130 detects a problem related to productivity by determining whether or not there is a problem with productivity based on the production status.

[0051] For example, the problem detection unit 130 determines whether the production time (second production time), which is an example of second productivity, is longer than the production time (first production time), which is an example of first productivity. That is, the problem detection unit 130 determines whether the time actually required for production is longer than the time predicted before production, for example. For example, if the second production time is longer than the first production time, the problem detection unit 130 determines that there is a problem with productivity. On the other hand, for example, if the second production time is equal to or shorter than the first production time, the problem detection unit 130 determines that there is no problem with production costs.

[0052] The problem regarding productivity may be a cause of a difference between the productivity target and the current productivity.

[0053] Furthermore, the problem detection unit 130 may repeatedly detect problems related to productivity and problems related to production costs at any timing while the production line 200 is producing circuit boards.

[0054] Furthermore, for example, if these problems are repeatedly detected by the problem detection unit 130, the setting unit 120 may repeatedly set the first production cost and the first productivity. For example, when setting the first production cost and the first productivity after the problem detection unit 130 detects a problem, the setting unit 120 may set the second production cost and the second productivity calculated by the problem detection unit 130 to detect the problem as the new first production cost and the first productivity. This allows, for example, when the problem detection unit 130 detects a problem again, the current productivity and production cost to be compared with the productivity and production cost when the previous problem was detected. Therefore, whether or not the productivity and production cost are deteriorating can be detected as a problem.

[0055] Of course, the problem detection unit 130 may detect a problem by comparing the productivity and production cost set before production with the productivity and production cost calculated based on the latest production state, and may also detect a problem by comparing the productivity and production cost when the previous problem was detected with the productivity and production cost calculated based on the latest production state. This makes it possible to detect problems regarding how the current situation is compared to the productivity and production cost predicted before production, and how the productivity and production cost are changing compared to the most recent production state.

[0056] As described above, the second productivity and the second production cost may be calculated based on a production state (second production state) that is later than the production state (first production state) that was used to calculate the first productivity and the first production cost. In other words, the second production state may be the production state of the production line 200 at a time later than the first production state.

[0057] The output unit 140 is a processing unit that outputs various information. For example, the output unit 140 outputs information indicating the second production cost to the display unit 210 via a communication interface provided in the management device 100. As a result, for example, the output unit 140 causes the display unit 210 to display the second production cost of the production line 200 in which a problem related to the production cost has been detected by the problem detection unit 130.

[0058] The output unit 140 may output information about the problem detected by the problem detection unit 130 to the display unit 210, a computer used by an operator, an external server, etc. The output unit 140 may output information indicating the first production cost, the first productivity, and the second productivity to these devices, etc.

[0059] Processing units such as the monitoring unit 110, the setting unit 120, the problem detection unit 130, and the output unit 140 are realized, for example, by a memory that stores the control programs executed by each processing unit, and a processor that executes the control programs.

[0060] The storage unit 150 is a storage device that stores various types of information. The storage unit 150 stores, for example, information indicating productivity, production costs, and unit prices of parts, as well as information indicating production conditions, etc. The storage unit 150 is realized by, for example, a flash memory or an HDD (Hard Disk Drive).

[0061] [Productivity and production costs] Next, productivity and production costs will be specifically described.

[0062] 3 to 5 are diagrams illustrating productivity and production costs according to an embodiment. Specifically, FIGS. 3 to 5 are graphs with production costs on the horizontal axis and productivity on the vertical axis. For example, the graphs shown in FIGS. 3 to 5 are set so that the productivity and production costs set before production line 200 starts producing circuit boards (hereinafter simply referred to as "pre-production") are set as the origin. Note that the higher the production cost relative to the origin of the graph, the higher the production cost is compared to the schedule (production plan) set before production, indicating a deterioration relative to the schedule. Also, the lower the productivity relative to the origin of the graph, the lower the productivity is compared to the schedule set before production, indicating a deterioration relative to the schedule.

[0063] For example, the problem detection unit 130 calculates an evaluation result indicating a second productivity and a second production cost based on the acquired production status, and calculates where the calculated evaluation result is located in Fig. 3. In other words, the problem detection unit 130 calculates the coordinates of the calculated evaluation result on the graph.

[0064] If the calculated evaluation result is located in the second quadrant, it can be said that the production state is good in both productivity and production costs compared to the production plan that was planned before production ("Productivity: Good and Production Cost: Good" in the second quadrant in Figure 3). If the calculated evaluation result is located in the first quadrant, it can be said that the production state is good in productivity but poor in production costs compared to the production plan that was planned before production ("Productivity: Good and Production Cost: Bad" in the first quadrant in Figure 3). If the calculated evaluation result is located in the third quadrant, it can be said that the production cost is good but poor in productivity compared to the production plan that was planned before production ("Productivity: Bad and Production Cost: Good" in the third quadrant in Figure 3). If the calculated evaluation result is located in the fourth quadrant, it can be said that the production state is bad in both productivity and production costs compared to the production plan that was planned before production ("Productivity: Bad and Production Cost: Bad" in the fourth quadrant in Figure 3).

[0065] For example, if the calculated evaluation result is not located in the second quadrant, in other words, if the calculated evaluation result is located in any of the first, third, or fourth quadrants, the problem detection unit 130 determines that there is a problem with at least one of productivity and production costs.

[0066] Furthermore, for example, the problem detection unit 130 detects that there is a problem with at least one of productivity and production cost when at least one of productivity and production cost deteriorates. For example, suppose that the problem detection unit 130 calculates an evaluation result a1 based on the production state at a first time. Next, suppose that the problem detection unit 130 calculates an evaluation result a2 based on the production state at a second time after the first time. For example, the problem detection unit 130 detects a problem related to the productivity and production cost of the production line 200 at the second time based on the evaluation results a1 and a2. In the example shown in FIG. 3, the evaluation result a2 shows a deterioration in both productivity and production cost compared to the evaluation result a1. Therefore, the problem detection unit 130 determines that there is a problem with productivity and production cost.

[0067] For example, when problem detection unit 130 determines that there is a problem with at least one of productivity and production cost, that is, when problem detection unit 130 detects at least one of a problem related to productivity and a problem related to production cost, problem detection unit 130 extracts errors in production line 200. Next, problem detection unit 130 determines, from among the detected errors, errors that are estimated to need to be addressed in order to improve the detected problem.

[0068] For example, suppose that (i) an error in the feeder, (ii) an error in the nozzle (suction nozzle), and (iii) an error in the head (suction head) have occurred in the production line 200. Furthermore, suppose that the calculated evaluation result is located in the first quadrant. In this case, for example, the problem detection unit 130 determines which of the three errors can be addressed to move the evaluation result from the first quadrant to the second quadrant. For example, the memory unit 150 pre-stores countermeasure information that associates the type of error that may occur with information indicating how productivity and production costs may be changed by taking countermeasures against the error. The problem detection unit 130 selects one or more errors from the three errors based on the evaluation result and the countermeasure information. For example, if the problem detection unit 130 selects (i) the feeder error, the output unit 140 transmits information to the display unit 210 prompting the user to take countermeasures against the feeder. As a result, the display unit 210 displays information prompting the user to take countermeasures against the feeder. Therefore, the operator can take measures for the feeder in accordance with such information displayed on the display unit 210. This makes it easier to resolve deterioration in productivity and production costs.

[0069] The countermeasure information may be generated by calculation by the problem detection unit 130 based on the error information. For example, the problem detection unit 130 calculates the productivity and production cost for when an error occurs and when no error occurs based on the error information. In this way, the problem detection unit 130 may generate countermeasure information that indicates how the productivity and production cost will change when a countermeasure is taken for the error.

[0070] Furthermore, the criteria by which the problem detection unit 130 selects an error, i.e., a countermeasure for the error, may be determined arbitrarily and are not particularly limited. Furthermore, the criteria by which the problem detection unit 130 selects an error, i.e., a countermeasure, may be determined arbitrarily so as to prioritize improvement of either productivity or production costs.

[0071] As shown in FIG. 4, for example, suppose the problem detection unit 130 calculates an evaluation result b. Ideally, measures should be taken to move the evaluation result in the direction of arrow A. However, depending on the type of error, there is a possibility that a trade-off occurs between productivity and production cost. Therefore, it may be determined arbitrarily whether the problem detection unit 130 selects a measure that prioritizes improving productivity or a measure that prioritizes improving production cost. For example, it may be determined arbitrarily whether the problem detection unit 130 selects a measure that prioritizes moving the evaluation result in the direction of arrow B or a measure that prioritizes moving the evaluation result in the direction of arrow C. Information indicating how to select (also referred to as selection information) may be stored in the storage unit 150 in advance, or may be acquired by the problem detection unit 130 by being input by an operator via a user interface or the like. For example, such information may be acquired by the problem detection unit 130 by being input by an operator via a user interface or the like before production, or may be acquired by the problem detection unit 130 by being input by an operator via a user interface or the like when a problem is detected.

[0072] As shown in FIG. 5, for example, the problem detection unit 130 calculates an evaluation result c1 based on the acquired production status. In this case, the problem detection unit 130 determines that a problem related to production costs has been detected because the coordinates of the evaluation result c1 are located in the first quadrant. Therefore, the problem detection unit 130 determines, for example, based on the error information, measures to be presented to the operator that will improve production costs. The output unit 140 causes the display unit 210 to display information indicating the measures determined by the problem detection unit 130. The operator takes measures based on the information displayed on the display unit 210.

[0073] Furthermore, the problem detection unit 130 calculates the evaluation result c2 based on a new production status acquired after a predetermined time has elapsed since the production status was acquired to calculate the evaluation result c1. The predetermined time may be determined arbitrarily and is not particularly limited. Information indicating the predetermined time is stored in advance in the storage unit 150, for example.

[0074] Here, evaluation result c2 shows an improvement in production costs compared to evaluation result c1, and although productivity has decreased, it remains high compared to the starting point. Therefore, for example, problem detection unit 130 determines new measures to be presented to the operator that will improve production costs based on the error information. Output unit 140 displays information indicating the new measures determined by problem detection unit 130 on display unit 210. The operator takes measures based on the new information displayed on display unit 210.

[0075] By repeating this process, for example, the problem detection unit 130 calculates an evaluation result c3 based on a new production state. In this case, the evaluation result c3 indicates a state in which both productivity and production costs are high compared to the origin, and therefore it is determined that there are no problems related to productivity or production costs.

[0076] As described above, for example, the management device 100 performs problem determination (i.e., problem detection) taking into consideration productivity, production costs, or both. Furthermore, the management device 100 manages the current position in the coordinates of the evaluation result while the operator is implementing countermeasures.

[0077] Specifically, the setting unit 120 sets (determines) coordinates with two axes, productivity and production cost. The intersection of the axes is set to the respective plans for productivity and production cost (specifically, the first productivity and the first production cost). Furthermore, the problem detection unit 130 periodically plots the current productivity and production cost (specifically, the second productivity and the second production cost) on the set coordinates during production (for example, each time one sheet is produced). The problem detection unit 130 determines whether there is a problem with productivity and production cost based on the position of the plot. Furthermore, the problem detection unit 130 determines whether there is a problem with productivity and production cost based on the amount of change in the plot.

[0078] The problem detection unit 130 predicts the number of defects that will occur in the future based on, for example, the current defect occurrence status (such as pickup errors, recognition errors, or mounting errors) included in the error information, and calculates the production cost based on the predicted number of defects. Furthermore, the problem detection unit 130 tracks the production status and determines whether there is a problem with the production cost based on the predicted number of defects (specifically, the loss amount) from, for example, the current defect rate monitored on a unit basis (feeder address / used components), the remaining number of boards to be produced, the number of components used per board (component count), the remaining number of components to be mounted, and the cost per component. At this time, for example, even if the production data is changed, the problem detection unit 130 continues to add the number of components as long as the feeder arrangement remains unchanged. For example, if the defect rate is 1500 ppm, the remaining number of circuit boards to be produced is 500, five components are used per board, and each component costs 50 yen, the problem detection unit 130 calculates that 3.75 components will be defective compared to if production had progressed ideally, resulting in an additional production cost (i.e., loss amount) of 187.5 yen.

[0079] If the production plan cannot be acquired, the problem detection unit 130 may predict the amount of waste when a predetermined number of circuit boards, such as 100, are produced in the future.

[0080] Furthermore, when the problem detection unit 130 cannot acquire information indicating the unit price of a component, the problem detection unit 130 may predict the amount of defective work using the number of components mounted.

[0081] Furthermore, production cost planning (calculation of allowable loss and / or planned loss) may be performed by any method. The problem detection unit 130 may calculate (predict) the loss amount (planned loss) for each type of part based on the set defect rate, production data, and production quantity. The defect rate may be input and changed (i.e., set) by the operator via a user interface or the like.

[0082] The problem detection unit 130 may also calculate a defect rate for each component and / or mounting condition based on past production results, and calculate a planned loss based on the calculated defect rate, production data, and the number of sheets produced. The problem detection unit 130 may also determine the amount of defect (planned defect) for the production plan from these two calculation results. Specifically, the problem detection unit 130 may determine the planned defect based on a production plan input by an operator or information indicating conditions for calculating the amount of defect, such as strictness or lenience. Information indicating such conditions and past production results may be stored in advance in the storage unit 150.

[0083] Furthermore, the criteria used by the problem detection unit 130 to determine whether a problem exists may be changed depending on the production status of the production line 200, operator settings, and the like. When determining whether a problem exists, the operator's priorities may change depending on various circumstances, such as whether they want to prioritize throughput or the defect rate. Therefore, for example, the operator may set the expected operating rate of the production line 200, and the problem detection unit 130 may use that operating rate to determine whether a problem exists in productivity or production costs. For example, the production line 200 may produce circuit boards based on a production plan in which the operating rate of the production line 200 is set to 80% of the progress rate of the production plan. For example, the problem detection unit 130 may detect a problem related to productivity and production costs if the set (acquired) operating rate is higher than the actual operating rate of the production line 200.

[0084] Furthermore, for example, the problem detection unit 130 calculates the loss occurrence time (i.e., the time required for the production of circuit boards by the production line 200 that was not included in the production plan) based on the increase in cycle time of a bottleneck production device among the multiple production devices included in the production line 200 and the remaining number of circuit boards that the production line 200 will produce in the future. The loss occurrence time can be caused, for example, by the stoppage of a production device due to an error, or by the occurrence of an abnormality (simultaneous suction failure) in which multiple suction heads are unable to simultaneously suction components even though the production device is operating. For example, if the calculated loss occurrence time is equal to or greater than a predetermined time, the problem detection unit 130 determines that there is a problem with productivity. On the other hand, for example, if the calculated loss occurrence time is less than the predetermined time, the problem detection unit 130 determines that there is no problem with productivity. The predetermined time may be determined arbitrarily in advance and is not particularly limited.

[0085] The lost time thus generated may be used to calculate productivity or production costs (for example, the amount of loss due to an extension of production time).

[0086] Furthermore, if improvements are seen in productivity and production costs after the measures are displayed, the measures do not need to be determined and displayed. In this case, for example, the output unit 140 may cause the display unit 210 to display a message such as, "Although problems are seen in production costs, improvements are being seen."

[0087] Furthermore, information indicating the calculated defective product amount may be output to the output unit 140 and displayed on the display unit 210. For example, the display unit 210 may display the total amount of the defective product amount if the production state remains as it is.

[0088] Fig. 6 is a diagram for explaining productivity according to the embodiment. Specifically, Fig. 6 is a graph showing the change over time in the number of circuit boards produced by production line 200. The horizontal axis of the graph shown in Fig. 6 indicates the production time, and the vertical axis of the graph indicates the number of circuit boards produced by production line 200. Time t0 indicates the time when production starts. The number of production XXX is the total number of circuit boards to be produced.

[0089] First, before production starts, for example, an operator creates a production plan including the number of pieces to be produced and the production time. In the example shown in FIG. 6, a plan (initial plan) is created so that production starts at time t0 and is completed at time t5, as indicated by the solid line. For example, the operator first creates an ideal production plan, as indicated by the dashed-dotted line, in which production progresses ideally without errors and is completed at time t2. Next, the operator creates a production plan, indicated by the solid line, that includes a time margin in the ideal production plan. For example, the operator inputs a production plan such as that indicated by the solid line using a user interface. The setting unit 120 acquires the input production plan and sets productivity and production costs (e.g., first productivity and first production cost) based on the acquired production plan.

[0090] The operator may input a production plan including the type of parts used in production, cost, and production quantity, etc. In this case, the setting unit 120 may set the productivity and production cost by calculating them based on the production plan.

[0091] Next, assume that production of circuit boards progresses on production line 200, and at time t1, monitoring unit 110 acquires a production status indicating that YYY circuit boards have been produced. Based on the acquired production status, setting unit 120 sets (calculates) productivity and production costs (e.g., second productivity and second production costs). For example, problem detection unit 130 detects productivity-related problems and production cost-related problems based on the first productivity and first cost, and the second productivity and second cost, set by setting unit 120. In this example, at time t1, production of circuit boards is progressing faster than the initial production plan, and in this case, problem detection unit 130 determines that there is no problem with productivity.

[0092] The management device 100 may create a future production plan based on the production status at time t1. For example, the setting unit 120 calculates the time (time t3 in this example) when production will ideally progress and be completed in order to produce the remaining number of circuit boards (XXX - YYY) to be produced from time t1. As a result, the setting unit 120 creates an ideal production plan, for example, as shown by the two-dot chain line in FIG. 6. Next, the setting unit 120 calculates the time (time t4 in this example) when production will be completed, including a time margin in the ideal production plan. As a result, the setting unit 120 creates a production plan, for example, as shown by the dotted line in FIG. 6.

[0093] Information indicating the production plan calculated in this way (for example, the remaining number of pieces to be produced and the estimated time of completion of production) may be output by the output unit 140 to the display unit 210, and may be displayed by the display unit 210.

[0094] [Processing Procedure] Next, the processing procedure of the mounting system 10 will be described.

[0095] 7 is a sequence diagram showing the processing procedure of the mounting system 10 according to the embodiment. Note that the sequence diagram shown in FIG. 7 will be described assuming that the display unit 210 and the user interface are arranged on the production line 200.

[0096] First, the production line 200 performs a turning operation to produce circuit boards (S110).

[0097] Furthermore, the production line 200 transmits mounting quality data of the circuit boards (i.e., information indicating the production status of the production line 200) to the management device 100 (S120). For example, the production line 200 transmits information indicating the number of circuit boards produced and errors that occurred during the production of the circuit boards to the management device 100 as mounting quality data. In this way, the management device 100 monitors the production line 200.

[0098] Furthermore, when the management device 100 acquires the mounting quality data, it detects problems related to productivity and problems related to production costs based on the acquired mounting quality data (S130).

[0099] In the mounting system 10, the operations of steps S110 to S130 are repeatedly executed.

[0100] Now, suppose that a problem is detected in step S130, in which case the management device 100 determines a countermeasure for the detected problem (S140).

[0101] Next, the management device 100 outputs information indicating the determined countermeasure content to the production line 200 (S150).

[0102] The display unit 210 arranged on the production line 200 displays information indicating the acquired countermeasure content (S160).

[0103] The operator checks the information displayed on the display unit 210 and takes measures (S170).

[0104] Next, the operator inputs information indicating the implemented measures using the user interface (S180). Of course, the operator may implement measures other than those displayed in step S160 and input information indicating the implemented measures.

[0105] The production line 200 transmits information indicating the measures taken by the operator to the management device 100 (S190).

[0106] Next, the management device 100 verifies the implemented countermeasures (S200). For example, the management device 100 verifies the effectiveness of the countermeasures by comparing the productivity and production cost calculated based on the production status acquired before the countermeasures were implemented (e.g., before acquiring information indicating the countermeasures implemented by the operator) with the productivity and production cost calculated based on the production status acquired after the countermeasures were implemented (e.g., after acquiring information indicating the countermeasures implemented by the operator). For example, if the productivity and production cost calculated based on the production status acquired after the countermeasures were implemented are better than the productivity and production cost calculated based on the production status acquired before the countermeasures were implemented, the management device 100 determines that the countermeasures were effective. On the other hand, if the productivity and production cost calculated based on the production status acquired after the countermeasures were implemented are not better than the productivity and production cost calculated based on the production status acquired before the countermeasures were implemented, the management device 100 determines that the countermeasures were ineffective.

[0107] For example, if the management device 100 determines that the countermeasures were ineffective, it returns to step S140 and determines a new countermeasure based on the detected problem, and the mounting system 10 repeats the processing from step S150 onwards. Also, for example, if the management device 100 determines that the countermeasures were effective, the mounting system 10 repeats the processing from steps S110 to S130. If the management device 100 determines that the countermeasures were effective, it may transmit information indicating that the countermeasures were effective to the production line 200, thereby displaying the information on the display unit 210.

[0108] 8 is a flowchart showing a specific example of the problem detection process executed by the management device 100 according to the embodiment. Specifically, FIG. 8 shows a specific example of the process executed by the problem detection unit 130.

[0109] First, the problem detection unit 130 evaluates the second productivity based on the production status (S310). Specifically, the problem detection unit 130 calculates the predicted production completion time based on the production status. For example, the problem detection unit 130 calculates the second productivity, that is, the current productivity, as the predicted production completion time based on the current production performance and the cycle time of the production device that is the bottleneck.

[0110] Next, the problem detection unit 130 evaluates the second production cost based on the production status (S320). Specifically, the problem detection unit 130 calculates the production cost expected to be required until production is completed based on the production status. For example, the problem detection unit 130 calculates the amount of defective work relative to the production plan (specifically, the first production cost) based on the defective work occurrence status as the current defective work amount, which is an example of the second production cost.

[0111] The problem detection unit 130 performs, for example, steps S310 and S320 to calculate where on the graph shown in FIG. 3 the evaluation results indicating the second productivity and the second production cost are located.

[0112] Next, the problem detection unit 130 determines whether the calculated evaluation result is located in the second quadrant of the graph shown in FIG. 3, for example (S330).

[0113] If the problem detection unit 130 determines that the calculated evaluation result is not located in the second quadrant of the graph shown in FIG. 3, for example (No in S330), it determines that there is a problem with at least one of productivity and production cost (S340).

[0114] On the other hand, if the problem detection unit 130 determines that the calculated evaluation result is located in the second quadrant of the graph shown in FIG. 3, for example (Yes in S330), it determines whether the evaluation result is tending to worsen (S350).

[0115] For example, the problem detection unit 130 determines whether at least one of the calculated second productivity and second production cost is worse than the first productivity or first production cost calculated using a production state acquired before (e.g., immediately before) the production state used for the calculation in step S310 and step S320.

[0116] When the problem detection unit 130 determines that the evaluation results tend to worsen (Yes in S350), it determines that there is a problem with at least one of productivity and production costs (S340).

[0117] On the other hand, if the problem detection unit 130 determines that the evaluation results are not tending to worsen (No in S350), it determines that there are no problems with productivity and production costs (S360).

[0118] FIG. 9 is a flowchart showing a management method according to an embodiment.

[0119] For example, the management device 100 performs the following process.

[0120] First, the monitoring unit 110 monitors the production status in the production line 200 that produces circuit boards by mounting components on boards (S10).

[0121] Next, the setting unit 120 sets a first production cost required when producing the circuit board (S20).

[0122] Next, the problem detection unit 130 detects a problem related to the production cost by comparing the second production cost based on the production status with the first production cost (S30).

[0123] When a problem is detected by the problem detection unit 130, for example, the output unit 140 outputs the second production cost of the production line 200 in which a problem related to the production cost has been detected to the display unit 210, thereby displaying the second production cost on the display unit 210.

[0124] Conventionally, problems have been detected uniformly based on the probability of occurrence of mounting errors, regardless of production cost, such as distinguishing between inexpensive and expensive components. As a result, conventionally, the cost-effectiveness of troubleshooting measures against mounting errors and other problems has been reduced. Furthermore, because problems are detected without considering the number of components to be used in the future, even if an operator takes measures to address the problem, the effectiveness of the measures may be reduced, for example, because the production line 200 immediately produces a different model (e.g., a circuit board of a different type from the circuit board currently being produced). Therefore, the management device 100 compares the first production cost with the second production cost to detect problems related to production costs. This allows problems such as mounting errors to be detected while taking production costs into consideration, so that, for example, errors that are cost-ineffective even when measures are taken can be prevented from being notified to the operator. Therefore, the management device 100 can reduce unnecessary processing from the perspective of production cost, such as unnecessary shutdowns of the production line 200 or unnecessary notification of errors to the operator when an error occurs on the production line 200.

[0125] [Effects, etc.] Below, examples of techniques that can be obtained from the disclosure of this specification will be given, and the effects and the like that can be obtained from the exemplified techniques will be described.

[0126] Technique 1 is a management device 100 that includes a monitoring unit 110 that monitors the production status in a production line 200 that produces circuit boards by mounting components on boards, a setting unit 120 that sets a first production cost required when producing the circuit boards, and a problem detection unit 130 that detects problems related to the production cost by comparing a second production cost based on the production status with the first production cost.

[0127] According to this, the management device 100 can detect a problem related to the production cost in the production line 200 by using the first production cost and the second production cost. For example, the detected problem is displayed on the display unit 210 and notified to the operator, so that the operator can take measures for the production line 200 taking into consideration the production cost. This can prevent an increase in production cost due to taking measures for the production line 200.

[0128] Technology 2 is the management device 100 described in Technology 1, in which the setting unit 120 sets a first productivity required when producing circuit boards, and the problem detection unit 130 detects a problem related to productivity by comparing a second productivity based on the production status with the first productivity.

[0129] According to this, the management device 100 can also detect problems related to productivity in the production line 200 by using the first productivity and the second productivity. For example, by notifying an operator of a detected problem, the operator can take measures for the production line 200 while taking into consideration both productivity and production costs.

[0130] Technique 3 is the management device 100 described in Technique 1 or 2, in which the problem detection unit 130 calculates a second production cost based on information indicating an error related to the adsorption of a part monitored as a production status and information indicating the unit price of the part in which the error occurred, and detects a problem related to the production cost based on the calculated second production cost.

[0131] This allows production costs to be calculated with high accuracy.

[0132] Technique 4 is the management device 100 according to Technique 3, in which the problem detection unit 130 further calculates the second production cost based on the number of components mounted on the board after the production status is acquired.

[0133] This allows production costs to be calculated with greater accuracy.

[0134] Technique 5 is the management device 100 described in Technique 3 or 4, in which the information indicating the unit price of the part is obtained by inputting the production conditions of the production line 200 into a learning model generated by learning information indicating the unit price of the part and the type of the part as supervised data.

[0135] This allows easy acquisition of information indicating the unit price of parts.

[0136] Technique 6 is the management device 100 according to any one of techniques 1 to 5, which includes an output unit 140 that causes the display unit 210 to display the second production cost of the production line 200 in which a problem related to the production cost has been detected by the problem detection unit 130.

[0137] This allows the operator to be notified of the second production cost of the production line 200 in which a problem regarding the production cost has been detected.

[0138] Technique 7 is a management method that monitors the production status in production line 200 that produces circuit boards by mounting components on boards (S10), sets a first production cost required when producing the circuit boards (S20), and detects problems related to the production cost by comparing a second production cost based on the production status with the first production cost (S30).

[0139] This provides the same effects as the management device 100 according to the first technique.

[0140] Technique 8 is a management method according to Technique 7, in which the second production cost of the production line 200 in which a problem related to the production cost is detected is displayed on the display unit 210.

[0141] This allows the operator to be notified of the second production cost of the production line 200 in which a problem regarding the production cost has been detected.

[0142] Technique 9 is a program for causing a computer to execute the management method described in Technique 7 or 8.

[0143] This provides the same effects as the management device 100 according to the first technique.

[0144] In addition, the comprehensive or specific aspects of the present disclosure may be realized as a system, a method, an integrated circuit, a computer program, or a non-transitory recording medium such as a computer-readable CD-ROM, or may be realized as any combination of a system, a method, an integrated circuit, a computer program, and a recording medium.

[0145] (Other embodiments) Although the management device and the like according to the present embodiment have been described based on the above embodiment, the present invention is not limited to the above embodiment.

[0146] For example, some or all of the components of the management device may be configured with dedicated hardware, or may be implemented by executing a software program appropriate for each component. Each component may be implemented by a program execution unit such as a CPU (Central Processing Unit) or processor reading and executing a software program recorded on a recording medium such as a hard disk drive or semiconductor memory.

[0147] Furthermore, the components of the management device may be configured with one or more electronic circuits, each of which may be a general-purpose circuit or a dedicated circuit.

[0148] Furthermore, for example, the implementation system may be realized as a client-server system. For example, information indicating a problem detected by the management device may be provided as a cloud service to a terminal used by an operator, a production line, or the like.

[0149] In addition, the present invention also includes forms obtained by applying various modifications to each embodiment that a person skilled in the art would think of, and forms realized by arbitrarily combining the components and functions of each embodiment within the scope of the present invention. [Industrial Applicability]

[0150] The present invention can be used in an apparatus for managing a mounting line that mounts components on a board. [Explanation of symbols]

[0151] 10 Mounting System 100 Management device 110 Monitoring Department 120 Setting section 130 Problem Detection Unit 140 Output section 150 Storage section 200 production lines 210 Display section M1 PCB Stocker M2 adhesive applicator M3 cream solder printing device M4, M5 component mounting equipment M6 Reflow Machine M7 visual inspection device

Claims

1. a monitoring unit that monitors the production status of a production line that produces circuit boards by mounting components on the boards; a setting unit that sets a first production cost required when producing the circuit board; a problem detection unit that detects a problem related to the production cost by comparing a second production cost based on the production status with the first production cost, Management device.

2. the setting unit sets a first productivity required when producing the circuit board; the problem detection unit detects a problem related to productivity by comparing a second productivity based on the production status with the first productivity. The management device according to claim 1 .

3. the problem detection unit calculates the second production cost based on information indicating an error related to component pickup monitored as the production status and information indicating a unit price of the component in which the error occurred, and detects a problem related to the production cost based on the calculated second production cost. The management device according to claim 1 .

4. the problem detection unit further calculates the second production cost based on the number of components mounted on the board after the production status is acquired. The management device according to claim 3 .

5. The information indicating the unit price of the part is obtained by inputting the production conditions of the production line into a learning model generated by learning information indicating the unit price of the part and the type of the part as supervised data. The management device according to claim 4 .

6. an output unit that displays on a display unit the second production cost of the production line for which a problem related to the production cost has been detected by the problem detection unit; The management device according to any one of claims 1 to 5.

7. Monitor the production status of a production line that produces circuit boards by mounting components on the boards, setting a first production cost required when producing the circuit board; detecting a problem with the production cost by comparing a second production cost based on the production status with the first production cost; Management method.

8. displaying, on a display unit, the second production cost of the production line in which the problem regarding the production cost has been detected; The management method according to claim 7.

9. A computer-implemented method for managing a computer according to claim 7 or 8, program.

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