JP2023040451A - Input sequence optimizing device, input sequence optimizing method and input order optimizing program - Google Patents

Abstract

To provide an input sequence optimizing device, etc. that optimizes a sequence of inputs of a workpiece to each step according to a process of a workpiece in each step in a production line and a progress state of a change in setup.SOLUTION: An input sequence optimizing device includes: an input sequence acquiring unit that acquires a sequence of inputs of a workpiece to each of steps in a production line; a progress data acquiring unit that acquires progress data of a process in each of the steps and a change in setup; an optimization range setting unit that sets an optimization range that is a range of a sequence of inputs for optimizing the sequence of inputs of the workpiece to each step; a production condition acquiring unit that acquires a production condition related to a production; and an input sequence optimization calculating unit that performs an input sequence optimization calculation for optimizing the sequence of inputs of the workpiece to each step, based on the sequence of inputs of the workpiece to each step, the optimized range, the progress data, and the production condition.SELECTED DRAWING: Figure 13

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a loading order optimizing device and the like, and more particularly to a loading order optimizing device and the like that optimizes the loading order according to the progress of preparation for production.

In recent years, in the manufacturing industry, high-mix low-volume production has become popular. In high-mix low-volume production, different types of products are produced on the same line. At this time, in each step of the production process, it is necessary to adjust the equipment and the like used for the processing so as to be suitable for the type of the product to be processed. In addition, in order to process the product, it is necessary to prepare parts, jigs, tools, etc. suitable for the type of the workpiece at the timing when the workpiece is sent to each process. These operations are generally called "setup". Among the setups, the setups that stop the equipment used for processing and make adjustments are called "inside setups", and the setups that are done outside the equipment used for processing, such as the preparation of parts and the preparation of jigs and tools It is called "outside setup". Also, changing the setup for changing the type of workpiece is called "changeover".

In high-mix low-volume production, the above-mentioned changeover frequently occurs. Here, by appropriately combining the input order of the types of workpieces to be input to each process, it is possible to reduce the number of changeovers and shorten the time required for each changeover. Therefore, a method of optimizing the input order of the types of workpieces to be processed is being studied so that the total production time, which is the sum of the machining time and the setup change time, is shortened. In such optimization of the loading order, the total production time is used as an objective function (evaluation function), and the loading order is used as a variable to search for an optimum set of variables. In other words, optimization of input order is a kind of combinatorial optimization problem. In this combinatorial optimization problem, the problem is that the amount of computation increases explosively as the number of combinations increases. However, recent advances in computer technology have made it possible to perform a large number of calculations, and methods of searching for the optimum solution with a feasible amount of calculation are being studied.

For example, Patent Literature 1 discloses a method of optimizing the order in which types (charges) are introduced. In the method described in Patent Document 1, in the steelmaking process, constraints on equipment, constraints on operation, and casting limit date (delivery date) are used as constraints, and a simulated annealing method is used to perform calculations. are trying to optimize

Further, Patent Document 2 discloses a method of optimizing the processing order. In the method described in Patent Document 2, the processing order of the materials to be processed in the continuous processing line is formulated as a mathematical programming problem, converted to an Ising model, and calculated by the quantum annealing method, thereby optimizing the processing order. there is

JP-A-2004-348436 JP 2020-042687 A

According to the technology of Patent Document 1 and the technology of Patent Document 2, it is possible to create a production plan in which the loading order is optimized. On the other hand, in the actual production, the production may be delayed due to the delivery delay of the parts, the malfunction of the equipment, and the like. Also, the process may be completed earlier than the production plan due to the skill of the workers. In such a case, the initially set input order may not be optimal.

The present invention has been made in view of the above problems, and optimizes the input order of workpieces to each process according to the progress of machining and setup change of workpieces in each process of a production line. It is an object of the present invention to provide an input order optimizing device and the like.

In order to solve the above-mentioned problems, the loading order optimization device of the present invention includes a loading order acquisition unit that acquires the loading order of workpieces to each process in a production line, and the progress of machining and setup change in each process. a progress data acquisition unit that acquires data; an optimization range setting unit that sets an optimization range that is a range of the input order for optimizing the input order of the workpiece to each process; and production conditions related to production. and a production condition acquisition unit that acquires the input order of the workpieces to each process based on the input order of the workpieces to each process, the optimization range, the progress data, and the production conditions. a loading order optimization calculation unit that performs loading order optimization calculation, which is a calculation to be optimized.

Further, the input order optimization method of the present invention acquires the input order of the workpiece to each process in the production line, acquires the progress data of machining and setup change in each process, Setting an optimization range that is a range of input order for optimizing the input order to the process, acquiring production conditions related to production, input order of the workpiece to each process, the optimization range, and the progress Based on the data and the production conditions, a loading order optimization calculation, which is a calculation for optimizing the loading order of the workpiece to each process, is performed.

Further, the input order optimization program of the present invention includes: a process of acquiring the input order of the workpieces to each process in the production line; a process of acquiring progress data of machining and setup change in each process; A process of setting an optimization range, which is the range of the input order for optimizing the input order of products to each process, a process of acquiring production conditions related to production, and an input order of the workpieces to each process. causing a computer to perform a loading order optimization calculation, which is a calculation for optimizing the loading order of the workpiece to each process, based on the optimization range, the progress data, and the production conditions. .

The effect of the present invention is that it is possible to provide an input order optimizing device or the like that optimizes the input order of workpieces to each process according to the progress of machining and setup change of workpieces in each process of the production line. is.

1 is a block diagram showing the overall configuration of a loading order optimization system using the loading order optimization device of the first embodiment; FIG. It is a block diagram showing the configuration of a production planning database of the first embodiment. 3 is a block diagram showing the configuration of a production condition database according to the first embodiment; FIG. It is a block diagram showing the configuration of the progress database of the first embodiment. It is a block diagram which shows the structure of the injection|throwing-in order optimization apparatus of 1st Embodiment. It is a block diagram which shows the structure of the injection|throwing-in order optimization calculation part of 1st Embodiment. 3 is a block diagram showing the configuration of an optimization calculation unit according to the first embodiment; FIG. It is a flow chart which shows operation of the input order optimization device of a 1st embodiment. It is a flowchart which shows operation|movement of the injection|throwing-up order optimal calculation part of 1st Embodiment. It is a block diagram which shows the hardware constitutions of the injection|throwing-in order optimization apparatus of 1st Embodiment. It is a block diagram which shows the structure of the modification 1 of the injection order optimization system using the injection order optimization apparatus of 1st Embodiment. 4 is a graph schematically showing the relationship between fatigue level β and time. It is a block diagram which shows the structure of the injection|throwing-in order optimization apparatus of 4th Embodiment. It is a flowchart which shows operation|movement of the injection|throwing-in order optimization apparatus of 4th Embodiment.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. However, the embodiments described below are technically preferable for carrying out the present invention, but the scope of the invention is not limited to the following. In addition, the same number may be attached|subjected to the same component of each drawing, and description may be abbreviate|omitted.

(First embodiment)
FIG. 1 is a block diagram showing the overall configuration of a loading order optimization system 10000 using the loading order optimization device 1000 of the first embodiment. The loading sequence optimization system 10000 has a loading sequence optimization device 1000 , a production plan database 2000 , a production condition database 3000 and a progress database 4000 .

FIG. 2 is a block diagram showing the configuration of the production planning database 2000 of the first embodiment. The production plan database 2000 holds data on production plans for each type of product to be produced on the production line. The data on the production plan includes an input order 2100, a scheduled production start time 2200 for each product type, and a scheduled production end time 2300 for each product type. The input order 2100 is the order in which each type of workpiece is input to each process. The scheduled production start time for each product type 2200 is the scheduled production start time set in advance for each product type of the workpiece. The scheduled production end time 2300 for each product type is the estimated production end time set in advance for each product type of the processed product.

FIG. 3 is a block diagram showing the configuration of the production condition database 3000 of the first embodiment. The production condition database 3000 holds various production conditions related to production. The production conditions are data used by the loading order optimization device 1000 for loading order optimization calculation, which is a calculation for optimizing the loading order for each type of workpiece to be loaded into each process. The production conditions include, for example, internal setup standard time 3100, external setup standard time 3200, processing standard time 3300, production volume/delivery date by product type 3400, possible production start date by product type 3500, constraint conditions 3600, and the like. The internal setup standard time 3100 is the standard required time for internal setup. Here, the internal setup is to stop the equipment and adjust the equipment, etc., when switching the type of the workpiece. The external setup standard time 3200 is the standard time required for external setup. Here, the off-line setup means preparatory work performed outside the equipment without stopping the equipment. Off-line setup includes, for example, the work of arranging the parts used in the process in order to process a certain type of workpiece, and the work of arranging the parts on carts and cassettes to facilitate processing. . The standard processing time 3300 is the standard processing time per machine for each process of each product type. Constraints 3600 are constraints when performing optimization calculations, such as the number of workers who perform setup work, and the prohibition of duplication of setup changes that cannot be performed at the same time. Note that these data are examples, and are set in accordance with the calculation method of the loading order optimization calculation.

FIG. 4 is a block diagram showing the configuration of the progress database 4000 of the first embodiment. The progress database 4000 holds data on the progress of setup according to the type of workpiece in each process and data on the progress of machining of the workpiece. Here, setup includes internal setup and external setup.

The progress database 4000 holds internal setup start time 4100 and internal setup completion status 4200 as data related to progress. When the internal setup is completed, that is, when the internal setup completion presence/absence 4200 is present, the completion time may be retained. Furthermore, an alarm may be raised when the internal setup completion status 4200 remains "absent" even after a predetermined time has passed from the start time, or when it becomes "yes" earlier than a predetermined time.

The progress database 4000 also holds external setup start time 4300 and external setup completion status 4400 . When the external setup is completed, that is, when the external setup completion presence/absence 4400 is present, the completion time may be retained. Furthermore, an alarm may be raised when the external setup completion status 4400 remains "no" even after a predetermined time has passed from the start time of the work, or when it becomes "yes" earlier than a predetermined time.

In addition, the progress database 4000 holds process start time 4500 and process completion status 4600 as data relating to the progress of processing of workpieces for each product type in each process. The process start time is the time when the work or treatment of the target process is started for the target workpiece. If the process has been completed, that is, if the process completion presence/absence 4600 is present, the completion time may be retained. Note that the above steps may include a plurality of sub-steps.

FIG. 5 is a block diagram showing the configuration of the input order optimization device 1000. As shown in FIG. The loading order optimization device 1000 includes a loading order acquisition unit 1100, a progress data acquisition unit 1200, an optimization range setting unit 1300, a production condition acquisition unit 1400, a loading order optimization calculation unit 1500, and a loading order change request. and a negative determination unit 1600 .

The placing order acquisition unit 1100 acquires the placing order 2100 held in the production planning database 2000 at a predetermined timing.

The progress data acquisition unit 1200 obtains from the progress database 4000 an internal setup start time 4100, an internal setup completion status 4200, an external setup start time 4300, an external setup completion status 4400, a process start time 4500, and a process completion status 4600. and get.

The optimization range setting unit 1300 sets the optimization range as the range of the loading order in which the optimization calculation of the loading order is performed. Here, the optimization range will be explained. Products for which the process has been completed are, of course, excluded from the optimization range. On the other hand, there are several stages in the progress of the setup change before starting the processing of the process. for example,
1) Internal setup has been started but not completed 2) Internal setup has been completed but external setup has not been completed 2) External setup has been started but not completed State 3) A state in which external setup is completed but internal setup is not completed.

When internal setup and external setup are halfway progressed as described above, the optimization range is a) Exclude the input order of processes for which internal setup has already started from the optimization range b) Processes for which external setup has already started from the optimization range c) Include the input sequence of the process for which internal setup is underway in the optimization range d) Include the input sequence for the process for which external setup is underway within the optimization range e) Include in the optimization range the input order of processes for which either internal setup or external setup has been completed.
Other settings are possible. The optimization range setting section 1300 sets one of these optimization ranges. The setting of the optimization range may be fixed, or a plurality of different optimization ranges may be set, and the input order optimization calculation may be performed for each of the optimization ranges.

Another cause of the delay in off-line setup is, for example, a shortage of parts. In this case, if the delay is about the processing time of one process, the input order of the process is included in the optimization range, but if the delay is in days, it is better to exclude the product type from the optimization range. . Since such judgments and operations are performed by humans, the optimization range setting unit 1300 may be provided with a mechanism for receiving input from the outside, and may be configured to set varieties to be excluded from recalculation.

The production condition acquisition unit 1400 acquires production conditions from the production condition database 3000 . As described above, the production conditions include, for example, internal setup standard time 3100, external setup standard time 3200, processing standard time 3300, production volume/delivery date by product type 3400, production start possible date by product type 3500, and constraint conditions 3600. However, these are only examples, and can be changed as appropriate according to the calculation method for optimizing the loading order.

The loading order optimization calculation unit 1500 performs loading order optimization calculation for the loading order of the product type and process set by the optimization range setting unit 1300 using the acquired production conditions and progress data. Input order optimization calculation can be performed using, for example, simulated annealing, quantum annealing, mathematical optimization, and genetic algorithm. Alternatively, it can be done using a combination of at least two of these.

FIG. 6 is a block diagram showing the configuration of the loading order optimization calculation unit 1500 of the first embodiment. The loading order optimization calculation unit 1500 has an optimization range reading unit 1510 , a production condition reading unit 1520 , a progress data reading unit 1530 , an optimization calculation unit 1540 and a result output unit 1550 .

FIG. 7 is a block diagram showing details of the optimization calculation unit 1540. As shown in FIG. The optimization calculation unit 1540 has a remaining time/discharge time calculation unit 1541 and a combination optimization calculation unit 1542 . If the optimization range includes a range in which internal setup or external setup has already started, the remaining time/breakdown time calculation unit 1541 calculates the degree of progress of the setup. Then, the remaining time for the setup change is calculated. In addition, the remaining time until completion of a setup that has progressed halfway from the already started setup and the break-down time required for canceling the setup and returning it to its original state are calculated. The remaining time can be calculated from the difference between the elapsed time from the start time of the inner (outer) setup and the standard inner (outer) setup time. For the unloading time, for example, the elapsed time from the start time can be used as it is, but it is also possible to set a standard time for the unloading work and calculate it based on the degree of progress and the standard unloading time.

Then, the combination optimization calculation unit 1542 uses the read production conditions and the calculated remaining time/breakdown time to perform combination Perform optimization calculations. Combinatorial optimization calculations can be performed using simulated annealing, quantum annealing, mathematical optimization, genetic algorithms, and combinations thereof, as described above.

The charging order change necessity determining unit 1600 compares the total production time in the charging order before the charging order optimization calculation acquired by the charging order acquiring unit 1100 with the total production time in the charging order after the charging order optimization calculation. . Then, if the total production time is shortened by the loading order optimization calculation, the loading sequence change necessity determination unit 1600 determines that the loading sequence change is necessary, and the loading sequence 2100 held in the production planning database 2000 to update. In addition, even when a product type to be introduced is deleted or added by an input from the outside, the introduction sequence change necessity determination unit 1600 determines that the introduction sequence needs to be changed, and the production plan database 2000 retains it. Then, the input order 2100 is updated. On the other hand, if the above conditions are not met and the total production time after the recalculation is not shorter than before the recalculation, the input sequence change necessity determination unit 1600 determines that the input sequence change is unnecessary, and terminates.

Next, the operation of the input order optimization device 1000 will be described. FIG. 8 is a flow chart showing the operation of the input order optimization device 1000 of the first embodiment. First, the loading order acquisition unit 1100 acquires the loading order 2100, which is the loading order of the workpieces to each process held in the production planning database 2000 (S101). Next, the progress data acquisition unit 1200 acquires progress data from the progress database 4000 (S102). Next, the optimization range setting unit sets the optimization range of the loading order in which the loading order optimization calculation is performed (S103). Next, the production condition acquisition unit 1400 acquires production conditions from the production condition database 3000 (S104). Note that the steps from S102 to S104 may be performed in any order. Next, the loading order optimization calculation unit 1500 uses the loading order 2100, progress data, and production conditions to perform loading order optimization calculations for the product types within the set optimization range (S105). Next, the loading order change necessity determination unit 1600 determines whether the total production time calculated based on the loading order after the loading order optimization calculation has been shortened from the total production time by the original loading order (S106). Here, if the total production time is shortened (S106_Yes), the input sequence change necessity determination unit 1600 determines that the input sequence needs to be updated, and updates the input sequence 2100 held in the production planning database 2000 ( S107). On the other hand, if the total production time has not been shortened, the input order change necessity determination unit 1600 determines whether or not there has been an increase or decrease in the product type due to input from the outside (S108). If there is an increase or decrease in the product type (S108_Yes), the input order change necessity determination unit 1600 determines that the input order needs to be changed, and updates the input order (S107). On the other hand, if there is no increase or decrease in the number of product types, the input order change necessity determining unit 1600 determines that the input order need not be changed, and ends the process. Note that the above-described input order optimization operation may be performed periodically at a predetermined timing, or triggered by an alarm from the progress database 4000 indicating delay or premature progress in machining progress or setup change. You can go as

Next, the operation of the loading order optimization calculation unit 1500 of the loading order optimization device 1000 will be described. FIG. 9 is a flow chart showing the operation of the loading order optimization calculator 1500 of the first embodiment. First, the optimization range reading unit 1510 reads the optimization range (S201). Next, the production condition reading unit 1520 reads production conditions (S202). Next, the progress data reading unit 1530 reads the progress data (S203). Next, the remaining time/discharged time calculation unit 1541 calculates the calculated remaining time/discharged time (S204). Next, the combination optimization calculation unit 1542 performs combination optimization calculation (S205).

Next, the hardware of the input order optimization device 1000 will be explained. FIG. 10 is a block diagram showing the hardware configuration of the input order optimization device 1000 of the first embodiment. The input order optimization device 1000 is implemented in a general computer having a processor 1910, a main storage device 1920, an auxiliary storage device 1930, and an input/output interface 1940, for example.

(Modification 1)
When the input order is changed, it is necessary to notify the workers of the production line. FIG. 11 is a block diagram showing the configuration of Modification 1 of the loading order optimization system using the loading order optimization device of the first embodiment. The loading order optimization system 10001 of the modification includes, in addition to the configuration of the loading order optimization system 10000, a loading order change notification device 5000 that notifies the worker that the loading order has been changed. The input order change notification device 5000 controls the output device and notifies the operator of the input order change information. The output device can be, for example, an indicator light, a display, a buzzer. Alternatively, it may be a smart device carried by the worker. Information to be notified may be, for example, whether or not the input order has been changed, and the input order before and after the change.

(Modification 2)
The start and completion of internal setup work and external setup work can also be automatically detected by detecting the locations of jigs and tools unique to the external setup change of the target product type. In Modified Example 2, a mechanism for automatically recording the start time and completion time of off-line setup will be described. Here, it is assumed that the target jigs and tools are reused in a plurality of production lines.

An RFID (Radio Frequency Identifier) tag is attached to the tool. An RFID reader is installed in each of the preparatory work area for external setup and the preparatory work completion area for storing jigs and tools. When the RFID of a tool is detected in the preparation work area of a certain production line, the progress database 4000 determines that the off-line setup for the product type has started on the line, and the RFID reader records the start time of the off-line setup. . Further, when the RFID tag of the tool is detected by the RFID reader in the work completion area after starting, the progress database 4000 determines that the external setup has been completed. Then, the presence or absence of the external setup is recorded as "yes", and the completion time is also recorded.

(Specific example 1)
Next, a specific example of the operation of the remaining time/split time calculation unit 1541 of the optimization calculation unit 1540 will be described. If the optimization range includes a range in which internal setup or external setup has already started, the remaining time/breakdown time calculation unit 1541 calculates the degree of progress of the setup. Then, the remaining time/breakdown time calculating unit 1541 calculates the remaining time for the changeover of the setup. In the following description, the remaining time and release time of the external setup will be described, but the same can be applied to the internal setup.

The remaining time/breakdown time calculation unit 1541 calculates the elapsed time from the start to the present for the external setup change that has already been started. Then, the remaining time for the external changeover is calculated by the following equation.
(Remaining time) = (Outside setup standard time) - (Elapsed time) (Formula 1)
Also, the dismantling time can be calculated by Equation 1, for example, assuming that preparation and dismantling proceed at the same speed. Also, if a standard time is defined for the dismantling work, it can be calculated by the following formula.
(Unloading time) = (standard unloading time) x (elapsed time) / (outside setup standard time) (Formula 2)
It should be noted that internal setup change can be similarly calculated. By performing the above calculations, it is possible to quantitatively estimate the degree of progress of the outside (inside) setup change work.

(Specific example 2)
Since setup change is accompanied by work by workers, the work speed changes depending on the skill level and fatigue level of each worker. By adjusting the standard work time by reflecting this skill level and fatigue level, it is possible to estimate the setup change preparation time and dismantling time closer to the actual situation.

Here, the skill level α of the worker is determined in the range of 0<α, with 1 being the case where the worker can work according to the standard time. take. The skill level α is set in advance according to the skill level of each worker.

The degree of fatigue β of the worker takes a range of 0≦β, with 0 being 0 when the worker has a skill level of 1 and can complete the standard work time.

FIG. 12 is a graph schematically showing the relationship between fatigue level β and time. As shown in FIG. 12, the fatigue level β is 0 at the start of work, but increases as time elapses. In addition, taking breaks reduces fatigue. Transition data of the degree of fatigue β is measured and set for each worker based on the transition of the work results for each hour, and is registered as data of the constraint condition 3600 of the production condition database 3000 . The proficiency level α and the fatigue level β are used to correct the outside (inside) setup standard time as shown in the following equation.
(Corrected external setup standard time) = (standard work time) x α x (1 + β) (Formula 3)
The proficiency level α and the fatigue level β may be updated based on the work record, for example. Alternatively, α and β may be obtained by multiple regression analysis using the outside (inside) setup change work progress as an objective variable. By reflecting the proficiency level α and the fatigue level β in the outside (inside) setup standard time, it is possible to estimate the setup change preparation time and release time close to the actual situation.

(Specific example 3)
The worker's work efficiency in the external setup change and the internal setup change is related not only to the skill level α and the fatigue level β but also to the willingness and motivation for the work. If something that has been prepared over a long period of time has to be dismantled due to external factors, it will affect the motivation of the worker and ultimately lead to a decrease in work efficiency. Therefore, a motivation decline index γ is introduced. The motivation decline index γ is determined in the range of 0≦γ, with 0 being the highest motivation. The post-correction external setup standard time can be expressed by the following equation using the proficiency level α, the fatigue level β, and the motivation decrease index γ.
(Standard time for outside setup after correction) = (Standard time for outside setup) x α x (1 + β) x (1 + γ)
(Formula 4)
Motivation is considered to decrease as the number of unpacking tasks increases. Therefore, the motivation decline index γ can be calculated, for example, by the following equation, where n is the number of times of unpacking work that day. The coefficient y can be obtained, for example, using regression analysis or the like from the actual work results.
γ=y×n (Formula 5)
By reflecting the decrease in worker's motivation in the standard time for outside (inside) setup, it is possible to estimate the preparation time and release time for outside (inside) setup change that is close to the actual situation.

According to the above configuration, since the standard time for changeover is corrected by reflecting the decrease in motivation of the worker, it is possible to estimate the progress of changeover that is closer to the actual situation.

The input order optimization device and the like according to the first embodiment of the present invention have been described above.

A loading order optimization device 1000 according to the first embodiment of the present invention includes a loading order acquisition unit 1100, a progress data acquisition unit 1200, an optimization range setting unit 1300, a production condition acquisition unit 1400, and a loading order optimization unit. and a calculation unit 1500 . The input order acquisition unit 1100 acquires the input order of the workpieces to each process in the production line. The progress data acquisition unit 1200 acquires progress data of machining and setup changes in each process. The optimization range setting unit 1300 sets an optimization range, which is a range of loading order for optimizing the loading order of workpieces to each process. The production condition acquisition unit 1400 acquires production conditions related to production. The loading order optimization calculation unit 1500 performs loading order optimization calculation based on the loading order of the workpiece to each process, the optimization range, the progress data, and the production conditions. Therefore, it is possible to optimize the input order of the workpieces to each process according to the progress of the machining of the workpieces and the setup change in each process of the production line.

Further, according to one aspect, the progress data includes the presence/absence of setup completion indicating the presence/absence of completion of the setup change. Therefore, the completion of the setup change is reflected in the optimization of the loading order, and the loading order optimizing device 1000 can optimize the loading order according to the progress of the setup change.

In addition, according to one aspect, the progress data includes the start time when the setup change was started. Therefore, the start time of setup change is reflected in the optimization, and the loading order optimizing device 1000 can perform the optimization calculation of the loading order according to the progress of the setup change.

Further, according to one aspect, the production conditions include a standard time that is the standard of the setup change time required for setup change, and the input order optimization calculation unit 1500 calculates the progress of the setup change based on the standard time and the start time. . Therefore, the input order optimization device 1000 can estimate the progress of the changeover with high accuracy.

Further, according to one aspect, the loading order optimization calculation unit 1500 corrects the standard time based on at least one of the worker's skill level and fatigue level. By considering at least one of the skill level and the fatigue level, the input order optimization device 1000 can estimate the progress of the changeover with high accuracy.

Further, according to one aspect, the loading order optimization calculation unit 1500 corrects the standard time based on the quantified degree of decrease in worker motivation. The input order optimization device 1000 can estimate the progress of the setup change with higher accuracy by considering the skill level.

In addition, according to one aspect, the injection order optimization calculation unit 1500 performs injection order optimization using simulated annealing, quantum annealing, mathematical optimization, genetic algorithm, or a combination of at least two of them. calculation. Therefore, the loading order optimization device 1000 can efficiently perform combination optimization calculations for optimizing the loading order.

Further, the loading order optimization system of the first embodiment of the present invention has the aforementioned loading order optimization device 1000, production plan database 2000, production condition database 3000, and progress database 4000. The production plan database 2000 holds production plan data including the current input order. The production condition database 3000 holds production conditions. The progress database 4000 holds progress data. By adopting such an input order optimization system, the input order of workpieces to each process is optimized according to the progress of machining and setup change of workpieces in each process of the production line. be able to.

Also, the input order optimization method of the first embodiment of the present invention acquires the input order of the workpieces to each process in the production line, and acquires the progress data of production and setup change in the production line. In addition, the input order optimization method sets an optimization range, which is a range of input order for optimizing the input order of workpieces to each process, and acquires production conditions related to production. Then, a loading order optimization calculation is performed, which is a calculation for optimizing the loading order of the processed products to each process based on the loading order of the processed products to each process, the optimization range, the progress data, and the production conditions. . Therefore, it is possible to optimize the input order of the workpieces to each process according to the progress of the machining of the workpieces and the setup change in each process of the production line.

In addition, the input order optimization program of the first embodiment of the present invention includes a process of acquiring the input order of workpieces to each process in the production line, and a process of acquiring progress data of machining and setup change in each process. run on the computer. In addition, the input order optimization program includes a process of setting an optimization range, which is the range of the input order for optimizing the input order of workpieces to each process, and a process of acquiring production conditions related to production. let the computer do it. In addition, the input order optimization program is a calculation for optimizing the input order of the workpieces to each process based on the input order of the workpieces to each process, the optimization range, the progress data, and the production conditions. The computer is caused to execute a certain loading order optimization calculation. By adopting such a configuration, the computer is caused to execute processing for optimizing the input order of the workpieces to each process according to the progress of the machining of the workpieces and the setup change in each process of the production line. be able to.

(Second embodiment)
FIG. 13 is a block diagram showing the configuration of the input order optimization device 10 of the fourth embodiment. The loading order optimization device 10 has a loading order acquisition unit 1 , a progress data acquisition unit 2 , an optimization range setting unit 3 , a production condition acquisition unit 4 , and a loading order optimization calculation unit 5 . The loading order optimization device 1000 of the first embodiment is a specific example of the loading order optimization device 10 . In addition, the input order acquisition unit 1100, the progress data acquisition unit 1200, the optimization range setting unit 1300, and the production condition acquisition unit 1400 are respectively a progress data acquisition unit 2, an optimization range setting unit 3, a production condition acquisition unit 4, It is one specific example of the loading order optimization calculation unit 5 .

A loading order acquisition unit 1 acquires the loading order of workpieces to each process in a production line. The progress data acquisition unit 2 acquires progress data of machining and setup changes in each process. The optimization range setting unit 3 sets an optimization range, which is a range of loading order for optimizing the loading order of workpieces to each process. The production condition acquisition unit 4 acquires production conditions related to production. The loading order optimization calculation unit 5 performs loading order optimization calculation based on the loading order of the workpiece to each process, the optimization range, the progress data, and the production conditions.

FIG. 14 is a flow chart showing the operation of the input order optimization device of the fourth embodiment. First, the loading order acquisition unit 1 acquires the loading order of the workpieces to each process in the production line (S301). Next, the progress data acquisition unit 2 acquires progress data of machining and setup changes in each process (S302). An optimization range, which is the range of the input order to be used, is set (S303). Next, the production condition acquisition unit 4 acquires production conditions related to production (S304). Next, the input order optimization calculation unit 5 optimizes the input order of the workpieces to each process based on the input order of the workpieces to each process, the optimization range, the progress data, and the production conditions. A loading order optimization calculation, which is a calculation, is performed (S305).

The input order optimization device 10 and the like of the second embodiment have been described above.

A loading order optimization device 10 according to the second embodiment of the present invention includes a loading order acquisition unit 1, a progress data acquisition unit 2, an optimization range setting unit 3, a production condition acquisition unit 4, and a loading order optimization unit. and a calculation unit 5 . A loading order acquisition unit 1 acquires the loading order of workpieces to each process in a production line. The progress data acquisition unit 2 acquires progress data of machining and setup changes in each process. The optimization range setting unit 3 sets an optimization range, which is a range of loading order for optimizing the loading order of workpieces to each process. The production condition acquisition unit 4 acquires production conditions related to production. The loading order optimization calculation unit 5 performs loading order optimization calculation, which is a calculation for optimizing the loading order of workpieces to each process based on the current loading order, optimization range, progress data, and production conditions. do According to this configuration, the loading order optimization calculation section 5 performs loading order optimization calculation based on the current loading order, the optimization range, the progress data, and the production conditions. Therefore, it is possible to optimize the input order of the product types to the production line according to the progress of machining and setup change in each process.

The input order optimization method of the second embodiment of the present invention acquires the input order of workpieces to each process in the production line, and acquires the progress data of machining and setup change in each process. Next, the optimization range, which is the range of the input order for optimizing the input order of the workpiece to each process, is set, and the production conditions related to production are acquired. Then, a loading order optimization calculation is performed, which is a calculation for optimizing the loading order of the processed products to each process based on the loading order of the processed products to each process, the optimization range, the progress data, and the production conditions. . Therefore, it is possible to optimize the input order of the product types to the production line according to the progress of production and setup change.

The input order optimization program of the second embodiment of the present invention includes a process of acquiring the input order of workpieces to each process in the production line, and a process of acquiring progress data of machining and setup change in each process. run on the computer. In addition, the input order optimization program includes a process of setting an optimization range, which is the range of the input order for optimizing the input order of workpieces to each process, and a process of acquiring production conditions related to production. let the computer do it. In addition, the input order optimization program is a calculation for optimizing the input order of the workpieces to each process based on the input order of the workpieces to each process, the optimization range, the progress data, and the production conditions. The computer is caused to execute a certain loading order optimization calculation. By adopting such a configuration, the computer is caused to execute processing for optimizing the input order of the workpieces to each process according to the progress of the machining of the workpieces and the setup change in each process of the production line. be able to.

The scope of the present invention also includes a program for causing a computer to execute the processes of the first and second embodiments described above and a recording medium storing the program. Examples of recording media that can be used include magnetic disks, magnetic tapes, optical disks, magneto-optical disks, and semiconductor memories.

The present invention has been described above using the above-described embodiments as exemplary examples. However, the invention is not limited to the above embodiments. That is, within the scope of the present invention, various aspects that can be understood by those skilled in the art can be applied to the present invention.

Some or all of the above-described embodiments can also be described in the following supplementary remarks, but are not limited to the following.

REFERENCE SIGNS LIST 1 loading order acquisition unit 2 progress data acquisition unit 3 optimization range setting unit 4 production condition acquisition unit 5 loading order optimization calculation unit 10, 1000 loading order optimization device 1100 loading order acquisition unit 1200 progress data acquisition unit 1300 optimization range Setting unit 1400 Production condition acquisition unit 1500 Loading order optimization calculation unit 1600 Loading order change necessity determination unit 2000 Production planning database 3000 Production condition database 4000 Progress database 10000 Loading order optimization system

Claims (10)

an input order acquisition unit that acquires the input order of the workpieces to each process in the production line;
a progress data acquisition unit that acquires progress data of machining and setup change in each process;
an optimization range setting unit for setting an optimization range, which is a range of the input order for optimizing the input order of the workpiece to each process;
a production condition acquisition unit that acquires production conditions related to production;
Input order optimization, which is a calculation for optimizing the input order of the workpiece to each process based on the input order of the workpiece to each process, the optimization range, the progress data, and the production conditions. an input order optimization calculation unit that performs optimization calculation;
An input order optimization device, characterized by comprising: 2. The input order optimization device according to claim 1, wherein the progress data includes whether or not the setup is completed, which indicates whether or not the setup change is completed. 3. The input sequence optimization device according to claim 1, wherein the progress data includes start time when the changeover is started. The production conditions include a standard time that is the standard of the changeover time required for changeover,
The input order optimization calculation unit,
4. The loading order optimization device according to claim 3, wherein the progress of said setup change is calculated based on said standard time and said starting time. The input order optimization calculation unit,
The loading order optimization device according to claim 4, wherein the standard time is corrected based on at least one of the worker's skill level and fatigue level. The input order optimization calculation unit,
The loading order optimization device according to claim 4 or 5, wherein the standard time is corrected based on the quantified degree of decrease in worker's motivation. The input order optimization calculation unit,
6. The input order optimization calculation is performed using any one of simulated annealing, quantum annealing, mathematical optimization, and genetic algorithm, or a combination of at least two of them. The input order optimization device according to any one of . The input order optimization device according to any one of claims 1 to 7;
a production planning database holding production planning data including the order in which the workpieces are introduced into each process;
a production condition database holding the production conditions;
a progress database holding the progress data;
An input order optimization system characterized by comprising: Acquire the input order of processed products to each process in the production line,
Acquiring progress data of machining and setup change in each process,
setting an optimization range that is a range of input order for optimizing the input order of the workpiece to each process;
Acquiring production conditions related to production,
Input order optimization, which is a calculation for optimizing the input order of the workpiece to each process based on the input order of the workpiece to each process, the optimization range, the progress data, and the production conditions. perform conversion calculations,
An injection order optimization method characterized by: A process of acquiring the input order of the processed products to each process in the production line;
A process of acquiring progress data of machining and setup change in each process;
A process of setting an optimization range, which is a range of input order for optimizing the input order of the workpiece to each process;
a process of acquiring production conditions related to production;
Input order optimization, which is a calculation for optimizing the input order of the workpiece to each process based on the input order of the workpiece to each process, the optimization range, the progress data, and the production conditions. and
An input order optimization program characterized by causing a computer to execute

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