WO2023276108A1

WO2023276108A1 - Simulation program, simulation method, and information processing device

Info

Publication number: WO2023276108A1
Application number: PCT/JP2021/024939
Authority: WO
Inventors: 猪谷宜彦; 長門毅; 山▲崎▼貴司
Original assignee: 富士通株式会社
Priority date: 2021-07-01
Filing date: 2021-07-01
Publication date: 2023-01-05

Abstract

The present invention causes a computer to execute: a process that, along a movement route on which a plurality of work bodies are provided that perform work in sequence on each of a plurality of objects, performs a simulation relating to the time until the plurality of objects reach a prescribed point on the movement route in accordance with the order in which the plurality of objects are introduced onto the movement route, the simulation being performed under the condition that, for each of the plurality of work bodies, the work time required for processing each of the plurality of objects is set, and a non-operation time period is set for at least one of the plurality of work bodies; a process that determines, in individual time units in the simulation, whether or not there has been detection of an object among the plurality of objects for which the work could not be completed within a time period over which the work could have been completed by any of the work bodies; and a process that, when an object for which the work could not be completed within the work-completable time period has been detected, excludes this object from the simulation.　

Description

Simulation program, simulation method, and information processing device

This case relates to a simulation program, a simulation method, and an information processing device.

Techniques for simulating work plans for work lines such as manufacturing lines have been disclosed (see

Patent Documents

1 and 2, for example).

Japanese Patent Application Laid-Open No. 2001-209420 JP-A-2000-246599

For example, by simulating while changing the processing order of objects on the work line, it is conceivable to search for the processing order so that KPIs (Key Performance Indicators) such as work completion time and work cost meet the desired conditions.

If a non-operating time period is set for each device that works on an object in the work line, there may be objects that cannot complete the work within the workable time of the device. If such an object cannot be assigned to the device and remains during the calculation during the simulation, the calculation time will be extended.

In one aspect, an object of the present invention is to provide an information processing device, a specifying method, and a specifying program capable of reducing unnecessary calculation time.

In one aspect, a simulation program is provided in a computer, for a movement route provided with a plurality of work subjects that sequentially work on a plurality of objects, each of the plurality of work subjects includes: of the plurality of objects to the movement route on the condition that the work time required to process each of them is defined and that at least one of the plurality of work subjects has a non-operating time zone defined. A process of simulating the time required for the plurality of objects to reach a predetermined point on the movement route according to the input order; a process of determining whether or not an object whose work cannot be completed within the workable time period is detected for each time unit of the simulation; If it is detected, a process of excluding the object from the simulation is executed.

It is possible to reduce unnecessary calculation time.

(a) is an example of a work line, and (b) is a diagram exemplifying the relationship between work time and work availability for each product. FIG. 5 is a diagram illustrating optimization processing; (a) to (c) are diagrams illustrating product movement rules in simulation. FIG. 10 is a diagram exemplifying the details of a simulation when products A, B, C, and D are put into a work line in this order; 5 is a diagram showing the simulation procedure of FIG. 4 as a flow chart; FIG. FIG. 10 is a flowchart showing a procedure for optimizing the loading order; (a) to (c) are diagrams for explaining non-operating time periods and unallocated items. 1A is a functional block diagram showing the overall configuration of an information processing apparatus according to a first embodiment, and FIG. 1B is a block diagram illustrating the hardware configuration of each part of the information processing apparatus; FIG. FIG. 4 is a diagram illustrating non-operating time zones for each device; FIG. 4 is a diagram illustrating cost factors for each device; It is the figure which represented the optimization process as a flowchart. (a) to (c) are diagrams illustrating detection of unallocated items. It is a flowchart showing the detail of the simulation process of step S23. It is a figure for demonstrating an effect.

First, I will explain the outline of the work line. FIG. 1(a) is an example of a work line. As exemplified in FIG. 1(a), each product, which is an object of work, advances from Start to Goal. A work line is a movement route provided with one or more devices that sequentially work on each of a plurality of products. In the example of FIG. 1(a), each product passes through an apparatus 1-1 in which step 1 is carried out, and further through an apparatus 2-1 or 2-2 in which step 2 is carried out.

In recent years, high-mix low-volume production has been practiced. Therefore, the work time and the like to be performed differ for each product number (type of product). For example, as exemplified in FIG. 1(b), product A is processed in units of 20 hours by device 1-1. The product A can be worked on either the device 2-1 or the device 2-2, but the work time differs between the device 2-1 and the device 2-2. Product C can be worked with the device 2-1, but cannot be worked with the device 2-2. Therefore, product C cannot pass through device 2-2. In this way, whether work is possible or not is determined for each product.

Because one device cannot work on multiple products at the same time, depending on the order in which the products are put into the work line, waiting time may occur for the products on the way, causing congestion. As a result, KPI (Key Performance Indicator) such as work completion time and work cost from the start of the first product introduction to the completion of work on all products and reaching the goal for each order of product introduction to the work line becomes different.

Therefore, it is conceivable to determine the order in which each product is put into the work line and to calculate the KPI for that order by performing a simulation. For example, as exemplified in FIG. 2, a plurality of input orders are generated by sequentially changing the input order, and the KPI is calculated by performing a simulation for each input order. By optimizing the injection order, the injection order can be specified such that the KPIs meet the desired values.

FIGS. 3(a) to 3(c) are diagrams illustrating product movement rules in the simulation. FIG. 3(a) shows the work line illustrated in FIG. 1(a). FIG. 3(b) is a model representing the work line of FIG. 3(a) with a plurality of cells. FIG. 3(c) is a diagram exemplifying the relationship between work time and workability for each product in FIG. 1(b).

As illustrated in FIG. 3(b), the work line model includes moving cells, equipment cells, and allocation cells. The operations of mobile cells, equipment cells, and allocation cells are on a time unit basis. The moving cell is a cell for moving the product in the direction of the arrow for each time unit. An equipment cell is a cell that performs work on a product. The product stays in the device cell for the working time designated in FIG. 3(c). If one product stays in the equipment cell, other products cannot enter the equipment cell.

The assigned cell is the cell located at the beginning of each process. Multiple products can reside in an allocation cell. The allocation cell determines the device to be moved and the timing for each unit of time according to the operating status of the device and whether or not the work can be performed as specified in FIG. 3(c). The allocation cell moves each product to the equipment cell in order, giving priority to the order of loading.

For example, if the order of product A, product B, and product C is specified in the input order, it is assumed that product A is being worked on by device 1-1. In this case, product B and product C will arrive at the first allocated cell in process 1 . When the work of product A in device 1-1 is completed, the assigned cell gives priority to product B over product C if the work of product B can be completed within the workable time of device 1-1. and move it to the device 1-1. If the work for product B cannot be completed within the workable time of device 1-1 and the work for product C can be completed, the assigned cell does not move product B and to the device 1-1.

For example, if the order of product A, product B, and product C is specified in the input order, it is assumed that product A is being worked on by device 2-1. In this case, it is assumed that the work-completed product B and product C arrive at the top allocation cell of step 2. If the work for product B can be completed within the workable time of device 2-2, the assignment cell moves product B to device 2-2 in preference to product C. If the work for product B cannot be completed within the workable time of device 2-2 and the work for product C can be completed, the assigned cell does not move product B and to the device 2-2.

FIG. 4 is a diagram exemplifying the details of a simulation when products A, B, C, and D are put into the work line in this order. In the example of FIG. 4, it is assumed that a non-operating time zone, which will be described later, is not set for each device. First, the product A moves to the device 1-1. In the apparatus 1-1, work is performed on the product A for the designated work time. While the product A is being worked on, the product B cannot be moved to the device 1-1 and waits. When the work on the product A in the device 1-1 is completed, the product A moves to the device 2-1. In the device 2-1, work is performed on the product A for the designated work time unit. Product B moves to device 1-1. In the apparatus 1-1, work is performed on the product B for the designated work time unit. When all the products reach the goal by such procedures, the simulation ends.

Each diagram on the right side of FIG. 4 is a diagram exemplifying the status of allocation of each product to each device. The horizontal axis indicates elapsed time. If no product has been moved to the device yet, no product is assigned to each device. When the product A is transferred to the device 1-1, the device 1-1 allocates a schedule for the work time unit of the product A. When product A moves to device 2-1 and product B moves to device 2-1, a schedule for the unit of work time for product A is assigned in device 2-1, and the work time for product B in device 1-1 is assigned. A schedule for the unit will be assigned. In this way, each product is assigned to each device.

FIG. 5 is a diagram showing the simulation procedure of FIG. 4 as a flow chart. As exemplified in FIG. 5, when a simulation is started for a specified order of loading, time t, which is a time variable, is set to 1 (step S1). Next, the process for the t-th time unit is executed (step S2). Next, it is determined whether or not the simulation has ended (step S3). If "No" is determined in step S3, 1 is added to time t (step S4). After that, the process is executed again from step S2. If it is determined as "Yes" in step S3, KPIs such as work completion time and cost are calculated (step S5). After that, the flow chart ends.

For example, if the device 1-1 performs work for 20 hours on product A, steps S2 to S4 are repeated 20 times. When the time t reaches 21, the work for the time unit specified by the device 1-1 is performed on the product B, and the work for the time unit specified by the device 2-1 or the device 2-2 is performed on the product A. done. When the work for all the products is completed and all the products reach the goal, it is judged as "Yes" in step S3.

FIG. 6 is a flowchart showing the procedure for optimizing the input order. As exemplified in FIG. 6, first, an initial value for the order in which each product is to be supplied to the work line is set (step S11). Next, the simulation process of FIG. 5 is executed using the specified input order (step S12). Next, it is determined whether or not the number of repetitions has reached a predetermined value (step S13). The number of repetitions is the number of times step S12 is executed. If it is determined as "No" in step S13, the next injection order is set by the optimization algorithm (step S14). After that, the process is executed again from step S13. If "Yes" is determined in step S13, an optimum work plan is selected based on the KPI values (step S15). Execution of the flowchart then ends.

By these procedures, it becomes possible to specify the input order that satisfies the desired value of the KPI. However, when the work planning deadline is set, the workable time becomes finite. Here, the work planning deadline is a deadline for the time range for each product to reach the goal after the first product is put into the work line. If the deadline for drafting the work plan is exceeded, the work cannot be carried out. Furthermore, if non-operating time periods such as break time and maintenance time are set, there is a possibility that a specific device may not be able to work on products requiring long working hours. Therefore, if a non-operating time zone is set, there is a possibility that some products (hereinafter referred to as unassigned products) cannot be worked on no matter how the products are rearranged. This unallocated item continues to remain during the calculation during the simulation, which extends the calculation time.

For example, as exemplified in FIG. 7(a), it is assumed that each device is set with a non-operating time zone during which work cannot be performed. If the work time for product B in process 2 is set to be long, the work may not be completed within the workable time of devices 2-1 and 2-2 by the work planning deadline. In this case, the product B cannot be moved to either the device 2-1 or the device 2-2. As described above, although priority is given to the order in which products are placed in the assigned cell, products that cannot be moved to the next device are allowed to stay in the assigned cell.

In the example of FIG. 7( a ), both

processes

1 and 2 are performed for product A, product C, and product D, but for product B, the process 2 is performed after the process 1 is performed. I am unable to do In this case, as exemplified in FIG. 7(b), the product B cannot be moved from the first allocated cell in step 2. In this case, even after the products A, C, and D have reached their goals, the simulation continues until the work planning deadline under the condition that the product B cannot proceed to the step 2. That is, even after product A, product C, and product D reach the goal, the process of confirming that product B cannot proceed to process 2 is repeatedly performed in each time unit until the deadline for creating the work plan. It will be. Therefore, as exemplified in FIG. 7(a), extra calculation time is generated.

Therefore, it is conceivable to set a threshold for the time range in which a product stays in an assigned cell without being assigned to a device, and exclude products that have stayed in the assigned cell longer than the threshold as unassigned items from the calculation. For example, as exemplified in FIG. 7(c), when the time range in which neither the device 2-1 nor the device 2-2 can be assigned to the product B exceeds the threshold, the product B is excluded from the calculation. . In this case, since the other products have reached their goal at the time of the threshold, the simulation in the target order of introduction ends. However, even in this case, there may be extra computation time in which the simulation continues after the other products have reached their goals.

Therefore, an information processing device, a simulation method, and a simulation program that can reduce unnecessary calculation time by detecting unallocated items that cannot be allocated to the next device will be described below.

FIG. 8(a) is a functional block diagram showing the overall configuration of the information processing apparatus 100 according to the first embodiment. The information processing apparatus 100 is a server or the like for optimization processing. As illustrated in FIG. 8A, the information processing apparatus 100 includes a model storage unit 10, a work master storage unit 20, a non-operating time zone storage unit 30, an input order storage unit 40, a cost coefficient storage unit 50, a work time It includes a band calculation unit 60, an optimization execution unit 70, an identification unit 80, a result output unit 90, and the like. The optimization execution unit 70 includes a simulation unit 71 , a determination unit 72 and an exclusion unit 73 .

FIG. 8(b) is a block diagram illustrating the hardware configuration of each part of the information processing device 100. As shown in FIG. As illustrated in FIG. 8B, the information processing apparatus 100 includes a CPU 101, a RAM 102, a storage device 103, an input device 104, a display device 105, and the like.

A CPU (Central Processing Unit) 101 is a central processing unit. CPU 101 includes one or more cores. A RAM (Random Access Memory) 102 is a volatile memory that temporarily stores programs executed by the CPU 101, data processed by the CPU 101, and the like. The storage device 103 is a non-volatile storage device. As the storage device 103, for example, a ROM (Read Only Memory), a solid state drive (SSD) such as a flash memory, a hard disk driven by a hard disk drive, or the like can be used. The storage device 103 stores a simulation program according to this embodiment. The input device 104 is an input device such as a mouse and keyboard. The display device 105 is a display device such as a liquid crystal display. The display device 105 displays the results output by the result output unit 90 . Each unit in FIG. 8A is implemented by the CPU 101 executing a specific program. Note that hardware such as a dedicated circuit may be used as each unit in FIG. 8A.

The model storage unit 10 stores a work line model as exemplified in FIG. 3(b). The work line model may be input in advance by the user using the input device 104, for example.

The work master storage unit 20 stores, as a work master, the relationship between work time and work availability for each product illustrated in FIG. 3(c). The work master may be input in advance by the user using the input device 104, for example.

The non-operating time period storage unit 30 stores non-operating time periods as a table or the like for each device. FIG. 9 is a diagram illustrating non-operating time zones for each device. As illustrated in FIG. 9, the start time and end time of the non-operating time period are stored for each device. The non-operating hours may be input in advance by the user using the input device 104, for example.

The loading order storage unit 40 stores the initial loading order of each product included in the work master stored in the work master storage unit 20 . The initial input order is, for example, the order in which the products are arranged according to the order received from the customer, and may be input in advance by the user using the input device 104 . Alternatively, the initial injection order may be generated by random numbers.

The cost coefficient storage unit 50 stores the cost coefficient of each device as a table or the like. FIG. 10 is a diagram illustrating cost factors for each device. As illustrated in FIG. 10, a cost factor is stored for each device. For example, by calculating the operating time of the device times the cost coefficient, it is possible to calculate the total cost generated by each device. The "operating time of the device" is the total value of the working time performed by the device on each product. The cost factor may be input in advance by the user using the input device 104, for example.

The optimization process will be described below along the flowchart of FIG. First, the work time slot calculation unit 60 calculates a work startable time slot in which work can be started in each device for each product (step S21). The work-startable time zone can be calculated from the work master and the non-operating time zone. First, the working time slot calculation unit 60 reads the non-operating time slot for each device from the non-operating time slot storage unit 30 . Next, the work time slot calculation unit 60 reads the work master from the work master storage unit 20 and calculates the work startable time slot for each device in a state where no product has been placed on the work line yet.

For example, for product D, the work time of device 1-1 is assumed to be in units of 30 hours. As exemplified in FIG. 12(a), during the period from the simulation start time to 30 time units before the non-operating time zone start time, the work for the product D can be completed using the device 1-1. Since it is possible, it is the time when work can be started. In addition, since the device 1-1 can be used to complete the work for the product D during the period from the end of the non-operating time period to 30 hours before the time of the work planning deadline, the work can be started. possible time period. The work-startable time period can be similarly calculated for the devices 2-1 and 2-2 as well. For device 2-2, the period from the start time of the simulation to the start time of the first non-operating time period is shorter than the working time for product D using device 2-2, so the first non-operating time period Until then, there will be no time slot in which work can be started. Since the period from the end time of the second non-operating time period to the work planning deadline is also shorter than the work time for working on the product D using the device 2-2, there is no work startable time period. .

Next, the optimization execution unit 70 reads the initial placement order from the placement order storage unit 40 (step S22). Next, the optimization execution unit 70 stores the work model stored in the model storage unit 10 , the work master stored in the work master storage unit 20 , and the non-working model stored in the non-operating time storage unit 30 . A simulation is performed using the time zone (step S23).

Next, the optimization execution unit 70 determines whether or not the number of repetitions of step S23 has reached a specified value (step S24). When it is determined as "No" in step S24, the optimization execution unit 70 sets the next input order using an optimization algorithm such as a genetic algorithm (step S25). For example, the input order is optimized so that the production completion time is short and the cost is low. After that, the process is executed again from step S23. By executing steps S23 to S25, the simulation is repeated for the prescribed number of input orders.

If "Yes" is determined in step S24, the specifying unit 80 selects the optimum production plan (step S26). For example, the specifying unit 80 specifies the input order in which the KPI satisfies the desired value (step S26). The result output unit 90 outputs the input order specified by the specifying unit 80 together with the KPI and the like in the input order. Execution of the flowchart then ends.

FIG. 13 is a flowchart showing the details of the simulation process in step S23. As illustrated in FIG. 13, the simulation unit 71 sets the time t, which is a time variable, to 1 (step S31). Next, the simulation unit 71 executes processing for the t-th time unit (step S32).

Next, the determination unit 72 updates the status of allocation of each product to each device (step S33). Next, the determination unit 72 checks the current process for each product and whether or not there is a work-startable time period after the current time (step S34). For example, as exemplified in FIG. 12(b), product A, product B, and product C have already been assigned to device 1 at the present time, and product A has also been assigned to device 2-1. Since product A has already been assigned to device 2-1, whether it is possible to complete the work for product B within the time range from the work completion time for product A in device 2-1 to the non-operating time zone is determined. In FIG. 12(c), product C is assigned to device 2-1, product B is assigned to device 2-2, and workable time is short for both device 2-1 and device 2-2. . In this state, neither the device 2-1 nor the device 2-2 can complete the work for the product D within the workable time. Therefore, there is no time slot in which work can be started for the product D.

Next, the judgment unit 72 judges whether or not a product (unallocated product) with no work-startable time slot has been detected (step S35). If it is determined "No" in step S35, the simulation unit 71 determines whether or not the simulation has ended (step S36). If determined as "No" in step S36, the simulation unit 71 adds 1 to time t (step S37). After that, the process is executed again from step S32. If it is determined as "Yes" in step S36, the simulation unit 71 calculates KPI such as work completion time and cost (step S38). After that, the flow chart ends.

If "Yes" is determined in step S35, the exclusion unit 73 excludes the unallocated item from the simulation (step S39). In the example of FIG. 12(c), product D is detected as an unallocated item. Next, the judging section 72 judges whether or not all products have completed work or become unallocated (step S40). If the determination in step S40 is "Yes", step S38 is executed. If "No" is determined in step S40, step S36 is executed.

According to this embodiment, the presence or absence of unallocated items is checked for each unit of time, and when an unallocated item is detected, the unallocated item is excluded from the simulation. In this case, it is possible to omit the calculation time from the time when the work for all the other products is completed and the goal is reached to the time limit for drafting the work plan. For example, as exemplified in FIG. 14, when product D is detected as an unallocated product, when the work for product A, product B, and product C is completed and the goal is reached, simulation ends. Therefore, unnecessary calculations are omitted, and the calculation time required for optimization can be reduced.

In the above example, work completion time and work cost are used as KPIs, but they are not limited to this. For example, if a delivery date is set for each product, the number of delivery delays can be used as a KPI. Delivery delay means that the product cannot reach the goal by the delivery date. Alternatively, the operating time of each device can be used as a KPI.

In the above example, each device on the work line is an example of a work subject that sequentially works on each of a plurality of objects. A work line is an example of a movement route provided with a plurality of the work subjects. The simulation unit 71 determines that each of the plurality of work subjects has a working time required to process each of the plurality of objects, and that at least one of the plurality of work subjects has a non-operating time period. An example of a simulation unit that performs a simulation on the time required for the plurality of objects to reach a predetermined point on the movement route according to the order in which the plurality of objects are thrown onto the movement route, under the condition that is. For each time unit of the simulation, the determination unit 72 detects whether or not an object whose work cannot be completed in a workable time zone of any of the plurality of work subjects is detected among the plurality of objects. It is an example of a judgment unit that judges. The excluding unit 73 is an example of an excluding unit that, when an object whose work cannot be completed within the workable time zone is detected, excludes the object from the simulation.

Although the embodiments of the present invention have been described in detail above, the present invention is not limited to such specific embodiments, and various modifications and variations can be made within the scope of the gist of the present invention described in the scope of claims. Change is possible.

10 model storage unit 20 work master storage unit 30 non-operating time period storage unit 40 input order storage unit 50 cost coefficient storage unit 60 work time period calculation unit 70 optimization execution unit 71 simulation unit 72 determination unit 73 exclusion unit 80 identification unit 90 Result output unit 100 Information processing device 101 CPU
102 RAMs
103 storage device 104 input device 105 display device

Claims

to the computer,
With respect to a movement route provided with a plurality of work subjects that sequentially work on a plurality of objects, each of the plurality of work subjects has a predetermined work time required to process each of the plurality of objects. and a non-operating time zone is defined for at least one of the plurality of work subjects, according to the order of input of the plurality of objects to the movement route, the plurality of objects A process of simulating the time it takes to reach a predetermined point on the movement route;
It is determined for each time unit of the simulation whether or not an object whose work cannot be completed in a workable time zone of any one of the plurality of work subjects is detected among the plurality of objects. processing;
A simulation program for excluding an object from the simulation when an object whose work cannot be completed within the workable time zone is detected.
The simulation program according to claim 1, characterized in that, in the simulation, a deadline is set for a time range for moving the plurality of objects on the movement route for each input order.
2. The movement route includes a branching point branching into two or more routes, and one of the plurality of workers is arranged on each of the two or more routes. The simulation program according to claim 2.
4. The computer according to any one of claims 1 to 3, characterized in that it causes the computer to execute a process of sequentially updating the input order so that the evaluation index of the results of the simulation for each input order satisfies a desired value. or the simulation program according to item 1.
With respect to a movement route provided with a plurality of work subjects that sequentially work on a plurality of objects, each of the plurality of work subjects has a predetermined work time required to process each of the plurality of objects. and a non-operating time zone is defined for at least one of the plurality of work subjects, according to the order of input of the plurality of objects to the movement route, the plurality of objects performs a simulation on the time it takes to reach a predetermined point on the movement route,
It is determined for each time unit of the simulation whether or not an object whose work cannot be completed in a workable time zone of any one of the plurality of work subjects is detected among the plurality of objects. ,
A simulation method, wherein when an object whose work cannot be completed within the workable time zone is detected, the object is excluded from the simulation.
6. The simulation method according to claim 5, characterized in that, in the simulation, a deadline is set for a time range for moving the plurality of objects on the movement route for each input order.
6. The movement route includes a branching point branching into two or more routes, and one of the plurality of workers is arranged on each of the two or more routes. The simulation method according to claim 6.
the computer
8. A process of sequentially updating the input order so that the evaluation index of the result of the simulation for each input order satisfies a desired value. The simulation method described in .
With respect to a movement route provided with a plurality of work subjects that sequentially work on a plurality of objects, each of the plurality of work subjects has a predetermined work time required to process each of the plurality of objects. and a non-operating time zone is defined for at least one of the plurality of work subjects, according to the order of input of the plurality of objects to the movement route, the plurality of objects a simulation unit that performs a simulation regarding the time it takes for the to reach a predetermined point on the movement route;
It is determined for each time unit of the simulation whether or not an object whose work cannot be completed in a workable time zone of any one of the plurality of work subjects is detected among the plurality of objects. a judgment unit;
An information processing apparatus, comprising: an exclusion unit that excludes an object whose work cannot be completed within the workable time zone from the simulation when the object is detected.
10. The information processing apparatus according to claim 9, wherein, in the simulation, a time limit is set for a time range in which the plurality of objects are moved on the movement route for each input order.
10. The movement route includes a branching point branching into two or more routes, and one of the plurality of workers is arranged in each of the two or more routes. The information processing apparatus according to claim 10.
12. The simulation unit sequentially updates the input order so that an evaluation index of the simulation result for each input order satisfies a desired value. The information processing device according to .