Information processing device, information processing method, and program
The information processing device optimizes input plans for multi-product manufacturing lines by iteratively adjusting and classifying sequences using simulation and random shuffling, addressing bottlenecks and reducing redundant evaluations for improved efficiency.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- KK TOSHIBA
- Filing Date
- 2023-04-12
- Publication Date
- 2026-06-08
AI Technical Summary
Existing technologies face challenges in efficiently generating input plans for multi-product manufacturing lines, leading to potential bottlenecks and repeated evaluation of similar plans, especially as the number of product varieties increases.
An information processing device that includes a simulation unit, calculation unit, classification unit, and modification units to iteratively adjust and classify product input plans based on productivity evaluation, using methods like unsupervised learning and random shuffling to avoid loop structures and optimize the input sequence.
This approach allows for the efficient generation of optimized input plans that minimize bottlenecks and reduce redundant evaluations, resulting in more appropriate and efficient manufacturing sequences.
Smart Images
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Abstract
Description
Technical Field
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[0001] Embodiments of the present invention relate to an information processing apparatus, an information processing method, and a program.
Background Art
[0007] The information processing device of the embodiment includes a processing unit. The processing unit performs a simulation of manufacturing by the manufacturing line using a first input plan for a manufacturing line that manufactures multiple types of products. The processing unit performs a calculation process for evaluation values representing the productivity of each of the multiple products using the results of the simulation. If the evaluation values do not meet predetermined conditions, the processing unit performs a first modification process to generate a second input plan by modifying the first input plan so that the difference between the first input plan and the second input plan (a modified input plan) falls within a specified range. If the evaluation values meet the conditions, the processing unit performs a second modification process to generate a second input plan by modifying the first input plan using a method different from the first modification process. The processing unit repeatedly performs the simulation, calculation process, first modification process, and second modification process. [Brief explanation of the drawing]
[0008] [Figure 1] Block diagram of an information processing device according to an embodiment. [Figure 2] A diagram showing an example of an input plan. [Figure 3] A diagram showing an example of the output result. [Figure 4] A diagram showing an example of evaluation values. [Figure 5] A diagram showing an example of data stored in the memory unit. [Figure 6] A diagram showing an example of the classification results. [Figure 7] A diagram showing an example of a revised input plan. [Figure 8] A diagram showing an example of the result of sorting the integrated input plan in order. [Figure 9] A diagram showing an example of an input plan after rearranging the order. [Figure 10] A diagram illustrating an example where the order of inputs in the plan is randomly changed. [Figure 11] Flowchart of the input plan generation process in the embodiment. [Figure 12]Hardware configuration diagram of the information processing device according to the embodiment. [Modes for carrying out the invention]
[0009] A preferred embodiment of the information processing device according to this invention will be described in detail below with reference to the attached drawings.
[0010] The following explanation uses the example of determining an input plan for a multi-product manufacturing line that produces multiple types of products using at least one piece of equipment. The input plan includes, for example, the order in which multiple types of products are introduced into the manufacturing line. The applicable manufacturing lines (systems, equipment) and input plans are not limited to those described above. Any manufacturing line other than a multi-product manufacturing line, and any input plan showing the plan for the products to be introduced into that manufacturing line, may be used. For example, a product P_1 may have multiple specifications depending on the customer, etc. In such a case, this embodiment can be applied by interpreting each of the multiple specifications of product P_1 as multiple types of products.
[0011] The information processing device of this embodiment repeatedly makes minor adjustments to the input plan (an example of a first modification process) based on productivity evaluation values (indicators) corresponding to multiple product varieties. Furthermore, to avoid the input plan becoming loop-structured and the same input plan being evaluated repeatedly due to repeated minor adjustments, the input plan is randomly changed (shuffled) (an example of a second modification process). This makes it possible to obtain an appropriate input plan more efficiently.
[0012] Furthermore, the information processing device in this embodiment classifies each product into multiple groups (ranks, categories) using product productivity evaluation values, and modifies the input plan for each group using different modification methods. This makes it possible to avoid bottlenecks in specific processes, which is one of the challenges in technologies that create input plans by combining common processes.
[0013] FIG. 1 is a block diagram showing an example of the configuration of the information processing apparatus 100 according to the embodiment. As shown in FIG. 1, the information processing apparatus 100 includes a simulation unit 101, a calculation unit 102, a classification unit 103, a change unit 104, a change unit 105, a control unit 106, a display control unit 111, a storage unit 121, and a display unit 122.
[0014] The storage unit 121 stores various types of information used in the information processing apparatus 100. For example, the storage unit 121 stores the results of the simulation by the simulation unit 101 and the evaluation values of each product calculated by the calculation unit 102.
[0015] The storage unit 121 can be configured by any generally used storage medium such as a flash memory, a memory card, a RAM (Random Access Memory), a HDD (Hard Disk Drive), and an optical disk.
[0016] The display unit 122 is a display device for displaying various types of information used in the information processing apparatus 100, and is realized by, for example, a liquid crystal display.
[0017] The simulation unit 101 executes a simulation of manufacturing by a production line using, for example, a simulation model. For example, the simulation unit 101 inputs an input plan (first input plan) of the production line. The input plan includes, for example, the order in which products of a plurality of varieties are input to the production line.
[0018] FIG. 2 is a diagram showing an example of an input plan. As shown in FIG. 2, the input plan includes an order, a product, and a quantity. The order is, for example, a numerical value indicating the order in which the product is input. The product is information for identifying the variety of the product, and is, for example, a product name and an identifier. In FIG. 2, an example of an input plan for inputting 51 types of products is shown, but the number of products (the number of varieties of products) is not limited to this. The input quantity represents the number input to the production line.
[0019] The initial input plan can be created in any way, for example, based on user insights, or in a random order.
[0020] Returning to Figure 1, the simulation unit 101 executes a simulation that simulates each process (internal process) for manufacturing each product in the order indicated in the input input plan, and outputs the simulation results (output results). The output results include, for example, the time when manufacturing for each of the multiple product varieties is completed (completion time), and the number of completed products.
[0021] Figure 3 shows an example of the output results. As shown in Figure 3, the output results include the completion time and number of completed products for each product. The number of completed products corresponds to the number of products that were processed in the internal process during the simulation period according to the input plan, for example, as shown in Figure 2, and were completed during the simulation period. The number of completed products may be greater than or equal to the number of inputs. The unit of completion time is not limited to the example shown in Figure 3, and may be expressed in milliseconds, for example. The order in which the output results are displayed does not have to match the order indicated in the input plan. For example, products may be displayed in the order according to the start rules of the internal process.
[0022] Returning to Figure 1, the calculation unit 102 uses the simulation output results to perform the calculation of evaluation values for each of the multiple product varieties. The evaluation values can be any indicator that represents the productivity of each product, but examples include the number of completed products, the time of completion, the number of days until the delivery date, and the sufficiency rate which shows the ratio of the number of completed products to the number of inputs.
[0023] Figure 4 shows an example of an evaluation value. In Figure 4, an example is shown where the number of completed products for each product is calculated as an evaluation value. The number of completed products for each product is obtained by aggregating the number of completed products for each product and for each completion time. For example, for the first product (product P_1), if 50 units were input, the evaluation value reached 30 during the simulation period. As mentioned above, the number of completed products may be greater than or equal to the number of units input, and therefore the evaluation value may also be greater than or equal to the number of units input.
[0024] The memory unit 121 stores, for example, the input plan entered for the simulation and the evaluation values for each product output from the calculation unit 102, in the order of the input plan (ascending order). Figure 5 shows an example of the stored data stored in the memory unit 121 in this way. The memory unit 121 may also store the number of times the simulation has been run.
[0025] Returning to Figure 1, the classification unit 103 uses the evaluation values for each of the multiple product varieties to classify (rank) each of the multiple product varieties into one of multiple groups (ranks). The number of groups to be classified into may be two or three or more. Any classification method may be used, but for example, the following method can be used. A method for classifying multiple product varieties into one of several groups based on the comparison results between the evaluation values of each product variety and one or more thresholds (first thresholds). • Methods using unsupervised learning classifiers (such as support vector machines and K-means). • A method of classification based on priorities such as delivery date and demand volume.
[0026] Figure 6 shows an example of the classification results when classifying into three groups using thresholds. In the example in Figure 6, two thresholds, 30 and 50, are used for classification, and multiple product varieties are divided into three groups: Group G_1, where the evaluation value is 50 or higher; Group G_2, where the evaluation value is between 30 and 50; and Group G_3, where the evaluation value is less than 30. The number of elements in each classified group (the number of products classified into a group) can take any value.
[0027] Returning to Figure 1, the modification unit 104 modifies the input plan based on the evaluation value for each product. For example, if the evaluation value does not satisfy condition C1, the modification unit 104 uses the evaluation value to modify the input plan PA (first input plan) before modification and the modified input plan PB (second input plan) after modification, thereby generating the input plan PB. This modification process (first modification process) generates the input plan PB.
[0028] Furthermore, the modification unit 104 modifies the product launch plans for products classified into groups by using mutually different modification methods for multiple groups.
[0029] Figure 7 shows an example of an input plan modified using different modification methods for each group. In Figure 7, the order of each product in group G_1 is moved forward by one, and the order of each product in group G_2 is moved back by one. The order of each product in group G_3 remains unchanged. Thus, the modification method may include not changing the order. The method of modifying the input plan for each group (moving the order forward, not changing it, moving the order back, etc.) can be determined in any way.
[0030] Note that an input plan with a sequence number of 1 cannot be moved forward any further, so even if it was classified in the group that needs to be moved forward, its sequence does not need to be changed. Similarly, an input plan with a sequence number at the end cannot be moved backward any further, so even if it was classified in the group that needs to be moved backward, its sequence does not need to be changed. As a result of this process, at the time the input plans for each group are changed, multiple groups may contain input plans with the same sequence.
[0031] Condition C1 can be interpreted as a condition indicating that the calculation of the evaluation value has converged. Convergence in the calculation of the evaluation value means that, for example, repeated minor adjustments have resulted in a loop structure in the input plan, and evaluating the same input plan reduces the fluctuation of the evaluation value. A loop structure refers to a situation where, after modifying an input plan Plan_1 two or more times, the input plan returns to input plan Plan_1.
[0032] Condition C1 is a condition that indicates that the number of times the statistical value of the evaluation value falls below a threshold (second threshold) when the simulation by the simulation unit 101, the calculation of evaluation values by the calculation unit 102, the modification process by the modification unit 104 (first modification process), and the modification process by the modification unit 105 (second modification process), described later, are repeatedly executed is greater than or equal to a specified number. The statistical value is, for example, one of the mean, maximum, minimum, median, standard deviation, and variance.
[0033] The number of trials used for the determination is, for example, the most recent N trials. N and the specified number may be determined, for example, as a ratio to the total computing resources (such as the upper limit on the number of simulation runs) (e.g., 1 / 10), or as a fixed value (e.g., 3 to 10 trials).
[0034] The above condition C1 is just an example and is not limited to it. Condition C1 may be any other condition that can be used to determine that the calculation of the evaluation value has converged, or in other words, that the fluctuation of the evaluation value has become small.
[0035] The modification unit 104 executes a modification process if the number of times the statistical value of the evaluation value falls below the threshold is less than a specified number, that is, if the evaluation value does not satisfy condition C1 (if the calculation of the evaluation value has not converged). If the number of times the statistical value of the evaluation value falls below the threshold is equal to or greater than a specified number, that is, if the evaluation value satisfies condition C1 (if the calculation of the evaluation value has converged), the modification process by the modification unit 105, described later, is executed.
[0036] The specified range is determined so that the input plan PB becomes similar to the input plan PA. For example, the specified range represents the range of change in order. The range of change may be a fixed value (e.g., 1) or it may be determined as a predetermined percentage (e.g., 1 / 10) of the total number of products. The total number of products may be the total number of products classified into all groups, or the total number of products classified into each group. Thus, the specified range may be determined based on the total number of products of multiple varieties. The modification unit 104 changing the input plan within the specified range can be interpreted as making minor adjustments to the input plan.
[0037] Furthermore, the modification unit 104 may change the order of all products in a group, or it may change the order of only some of the products in a group. The products to be changed may be selected according to their evaluation values, or they may be selected randomly. Also, the modification unit 104 may change the order of each product in a group by a different margin. For example, the modification unit 104 may change the order of products classified into a group that have an evaluation value above a threshold by a larger margin than that of products with an evaluation value below the threshold.
[0038] The modification unit 104 rearranges the order of each group and then integrates (combines) the input plans of each group. The integration method can be any method, but for example, multiple groups can be combined in order of their evaluation value. The order of integration is not limited to this. The modification unit 104 further sorts (rearranges) the integrated input plans according to the order.
[0039] Figure 8 shows an example of the result of sorting the integrated input plan in order. As shown in Figure 8, by changing the order in different ways for each of the multiple groups, it may be possible to have products with the same order. In Figure 8, an example is shown where the order of product P_4 and product P_3 is 3. In such cases, the modification unit 104 may, for example, reorder from top to bottom.
[0040] Figure 9 shows an example of an input plan after rearranging the order. In the example in Figure 9, the order of product P_3 is rearranged from 3 to 4.
[0041] Returning to Figure 1, the modification unit 105 executes processing to prevent the input plan from becoming a loop structure. As described above, if the modification processing (minor adjustments to the input plan) by the modification unit 104 is repeated, the modified input plan may become a loop structure. The occurrence of a loop structure can be determined, for example, by condition C1.
[0042] Therefore, if the evaluation value satisfies condition C1, the modification unit 105 executes a modification process (second modification process) to modify the input plan PA and generate the input plan PB using a method different from the modification process by the modification unit 104. The modification process by the modification unit 105 is, for example, a process that randomly changes the order indicated by the input plan PA (a process that shuffles the order). For example, the modification unit 105 randomly changes the order by random sampling using random numbers.
[0043] The modification process performed by the modification unit 105 is not limited to the above, and may also include, for example, a method using a genetic algorithm, or a method of changing the order of some randomly selected products.
[0044] Figure 10 shows an example where the order of the input plan in Figure 2 is randomly changed. The modification unit 105 reorders the input plans in ascending order to match the order of the modified input plans and generates the input plan PB.
[0045] Up until now, we have explained an example of changing the input order as a way to modify the input plan, but other elements may be changed instead of, or along with, the input order. Other elements include, for example, the number of units to be input and the timing (time) of input. The timing of input may be defined in units of multiple quantities obtained by further dividing the number of units to be input. For example, if the number of units to be input for product P_1 is 50, the 50 units of product may be divided into 10 units, 20 units, and 20 units, and each of these products may be input at different times.
[0046] Returning to Figure 1, the control unit 106 controls the repeated execution of each of the following processes: simulation by the simulation unit 101, calculation of evaluation values by the calculation unit 102, modification processing by the modification unit 104 (first modification processing), and modification processing by the modification unit 105 (second modification processing). For example, the control unit 106 repeats each process until the termination condition is met, and finds an input plan that yields the optimal evaluation value.
[0047] The termination condition can be anything, but for example, the following conditions can be used. • The number of times each process (simulation) is executed exceeds the threshold. • The elapsed time since the start of the simulation exceeds the threshold. • The evaluation value is above (or below) the threshold.
[0048] The control unit 106 may use conditions that combine two or more of the above-mentioned conditions.
[0049] The display control unit 111 controls the display of information on the display unit 122. For example, the display control unit 111 displays the modified input plan PB on the display unit 122. The display control unit 111 may also display input plan PB from among the multiple input plan PBs obtained in the simulation whose evaluation value is greater than that of other input plans (for example, whose evaluation value is above a threshold, whose evaluation value is the maximum, etc.). The display control unit 111 may display the input plan PA before the change and the input plan PB after the change in a manner that allows for comparison.
[0050] At least a portion of each of the above parts (simulation unit 101, calculation unit 102, classification unit 103, modification unit 104, control unit 106, modification unit 105, and display control unit 111) may be implemented by a single processing unit. Each of the above parts may be implemented by, for example, one or more processors. For example, each of the above parts may be implemented by having a processor such as a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit) execute a program, i.e., by software. Each of the above parts may be implemented by a processor such as a dedicated IC (Integrated Circuit), i.e., by hardware. Each of the above parts may be implemented by using both software and hardware. When multiple processors are used, each processor may implement one of the above parts, or two or more of the above parts.
[0051] Furthermore, the information processing device 100 may be composed of one physical device or multiple physical devices. For example, the information processing device 100 may be built on a cloud environment. Alternatively, each part of the information processing device 100 may be distributed and provided on multiple devices.
[0052] Next, the information processing by the information processing device 100 of the embodiment will be described. Figure 11 is a flowchart showing an example of the input plan generation process in the embodiment.
[0053] The simulation unit 101 executes a simulation using the input plan PA (step S101). For example, the simulation unit 101 inputs the input plan PA into the simulation model and executes the simulation.
[0054] The calculation unit 102 calculates an evaluation value from the simulation output results (step S102). For example, the calculation unit 102 aggregates the completion times included in the output results for each product and calculates an evaluation value. The evaluation value may also be the number of completed products or the satisfaction rate.
[0055] The calculation unit 102 stores the calculated evaluation value and the input plan PA in the storage unit 121 (step S103). Figure 5 above shows an example of the stored data at this time.
[0056] The modification unit 105 determines whether the evaluation value satisfies condition C1 (step S104). If the evaluation value satisfies condition C1 (step S104: Yes), the modification unit 105 modifies the stored input plan PA (for example, by shuffling the order) to create a new input plan PB (step S109).
[0057] If the evaluation value does not satisfy condition C1 (step S104: No), the classification unit 103 classifies each of the multiple product varieties into one of the multiple groups (step S105).
[0058] The modification unit 104 modifies the input plan for each of the classified groups (step S106). For example, if the products are classified into three groups as shown in Figure 6, the modification unit 104 modifies the input order of each of the three groups, either by moving it forward by one step, by moving it back by one step, or by leaving it unchanged.
[0059] The modification unit 104 integrates the input plans of each group whose order has been changed (step S107). For example, the modification unit 104 combines the input plans in the following order: the group whose order was moved earlier, the group whose order was moved later, and the group whose order was not changed. If the combined input plans contain products in the same order, the modification unit 104 may reorder them from top to bottom.
[0060] The modification unit 104 determines and outputs the integrated input plan as the modified input plan PB (step S108).
[0061] After steps S108 and S109, the control unit 106 determines whether or not to terminate the simulation (step S110). For example, the control unit 106 determines whether termination conditions are met, such as the number of simulation executions exceeding a threshold.
[0062] If the simulation is not terminated (step S110: No), the process returns to step S101 and is repeated. If the simulation is terminated (step S110: Yes), the input plan generation process is terminated.
[0063] In this embodiment, by repeatedly making minor adjustments to the input plan, it is possible to evaluate an input plan similar to the previous one. Furthermore, by changing the input plan when certain conditions are met, it is possible to avoid evaluating the same input plan repeatedly and to start making minor adjustments to a new input plan. This makes it possible to evaluate input plans that show various combinations of sequences more efficiently, even when the number of sequence combinations increases due to an increase in the number of products, and to obtain a more appropriate input plan.
[0064] As described above, according to the embodiment, an input plan can be obtained more efficiently.
[0065] Next, the hardware configuration of the information processing device of the embodiment will be described using Figure 12. Figure 12 is an explanatory diagram showing an example of the hardware configuration of the information processing device of the embodiment.
[0066] The information processing device of this embodiment includes a control device such as a CPU 51, a storage device such as a ROM (Read Only Memory) 52 and RAM 53, a communication I / F 54 that connects to a network for communication, and a bus 61 that connects each part.
[0067] The program to be executed in the information processing device of this embodiment is provided pre-installed in a ROM 52 or the like.
[0068] The program executed by the information processing device of this embodiment may be configured to be provided as a computer program product by recording it in an installable or executable file format onto a computer-readable recording medium such as a CD-ROM (Compact Disk Read Only Memory), a flexible disk (FD), a CD-R (Compact Disk Recordable), or a DVD (Digital Versatile Disk).
[0069] Furthermore, the program executed by the information processing device of the embodiment may be stored on a computer connected to a network such as the Internet and provided by downloading it via the network. Alternatively, the program executed by the information processing device of the embodiment may be provided or distributed via a network such as the Internet.
[0070] The program executed in the information processing device of this embodiment can cause the computer to function as a component of the information processing device described above. This computer can read the program from a computer-readable storage medium onto the main memory and execute it using the CPU 51.
[0071] An example of the configuration of the embodiment is described below. (Configuration Example 1) Using a first input plan for a manufacturing line that produces multiple types of products, a simulation of manufacturing by the said manufacturing line is performed. Using the results of the simulation, a process is performed to calculate evaluation values representing the productivity of each of the multiple products. If the aforementioned evaluation value does not meet the predetermined conditions, the first modification process is executed to modify the first input plan and generate the second input plan so that the difference between the modified input plan (the second input plan) and the first input plan falls within the specified range. If the evaluation value satisfies the conditions, a second modification process is executed to modify the first input plan and generate the second input plan in a manner different from the first modification process. The simulation, the calculation process, the first modification process, and the second modification process are repeatedly executed. Processing section An information processing device equipped with the following features. (Configuration example 2) The aforementioned processing unit, Using the evaluation values for each of the multiple products, the multiple products are classified into one of the multiple groups, The first input plan for the products classified into the group is modified by modifying each of the multiple groups using mutually different modification methods. The information processing device described in Configuration Example 1. (Configuration Example 3) The processing unit classifies the multiple products into one of the multiple groups based on the comparison result between the evaluation value for each of the multiple products and one or more first threshold values. The information processing device described in Configuration Example 2. (Configuration example 4) The aforementioned range is determined based on the total number of the multiple products. The information processing device described in Configuration Example 2. (Configuration example 5) The processing unit displays the second input plan on a display device. An information processing device as described in any one of Configuration Examples 1 to 4. (Configuration example 6) The aforementioned condition is a condition that indicates that the number of times the statistical quantity of the evaluation value falls below the second threshold when the simulation, calculation process, first modification process, and second modification process are repeatedly executed is greater than or equal to a specified number. An information processing device as described in any one of Configuration Examples 1 to 5. (Configuration example 7) The first input plan and the second input plan represent at least one of the following: the order in which multiple products are introduced into the manufacturing line, the number of products to be introduced, and the timing of the introduction. An information processing device as described in any one of Configuration Examples 1 to 6. (Configuration example 8) The first input plan and the second input plan represent the sequence in which multiple products are input into the manufacturing line. The second modification process is a process that randomly changes the order indicated by the first input plan. The information processing device described in Configuration Example 7. (Configuration example 9) The aforementioned processing unit, A simulation unit that performs the aforementioned simulation, A calculation unit that performs the aforementioned calculation process, A first modification unit that performs the first modification process, A second modification unit that performs the second modification process described above, A control unit that repeatedly performs the simulation, the calculation process, the first modification process, and the second modification process, Equipped with, An information processing device as described in any one of Configuration Examples 1 to 8. (Configuration example 10) An information processing method performed by an information processing device, Using a first input plan for a manufacturing line that produces multiple types of products, a simulation of manufacturing by the said manufacturing line is performed. Using the results of the simulation, a process is performed to calculate evaluation values representing the productivity of each of the multiple products. If the aforementioned evaluation value does not meet the predetermined conditions, the first modification process is executed to modify the first input plan and generate the second input plan so that the difference between the modified input plan (the second input plan) and the first input plan falls within the specified range. If the evaluation value satisfies the conditions, a second modification process is executed to modify the first input plan and generate the second input plan in a manner different from the first modification process. The simulation, the calculation process, the first modification process, and the second modification process are repeatedly executed. Information processing methods that include the following. (Configuration Example 11) On the computer, A step of running a simulation of manufacturing by a manufacturing line using a first input plan for a manufacturing line that manufactures multiple types of products, The steps include: using the results of the simulation, performing a process to calculate evaluation values representing the productivity of each of the multiple products; If the aforementioned evaluation value does not meet predetermined conditions, the first modification process is performed to modify the first input plan and generate the second input plan so that the difference between the modified input plan (the second input plan) and the first input plan falls within a specified range. If the evaluation value satisfies the conditions, the step of executing a second change process to modify the first input plan and generate the second input plan in a method different from the first change process, The steps include repeatedly executing the simulation, the calculation process, the first modification process, and the second modification process, A program to execute.
[0072] While several embodiments of the present invention have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be carried out in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims of the invention and its equivalents. [Explanation of Symbols]
[0073] 100 Information Processing Devices 101 Simulation Department 102 Calculation Unit 103 Classification Department 104 Changes 105 Changes 106 Control Unit 111 Display Control Unit 121 Storage section 122 Display section
Claims
1. Using a first input plan for a manufacturing line that produces multiple types of products, a simulation of manufacturing by the said manufacturing line is performed. Using the results of the simulation, a process is performed to calculate evaluation values representing the productivity of each of the multiple products. If the aforementioned evaluation value does not meet the predetermined conditions, the first modification process is executed to modify the first input plan and generate the second input plan so that the difference between the modified input plan (the second input plan) and the first input plan falls within a specified range. If the evaluation value satisfies the conditions, a second modification process is executed to modify the first input plan and generate the second input plan in a manner different from the first modification process. The simulation, the calculation process, the first modification process, and the second modification process are repeatedly executed. Equipped with a processing unit, The aforementioned condition is a condition that indicates that the number of times the statistical quantity of the evaluation value falls below the second threshold when the simulation, calculation process, first modification process, and second modification process are repeatedly executed is greater than or equal to a specified number. Information processing device.
2. The aforementioned processing unit, Using the evaluation values for each of the multiple products, the multiple products are classified into one of the multiple groups, The first input plan for the products classified into a group is modified by modifying each of the aforementioned groups using mutually different modification methods. The information processing apparatus according to claim 1.
3. The processing unit classifies the multiple products into one of the multiple groups based on the comparison result between the evaluation value for each of the multiple products and one or more first threshold values. The information processing apparatus according to claim 2.
4. The aforementioned range is determined based on the total number of the multiple products. The information processing apparatus according to claim 2.
5. The processing unit displays the second input plan on a display device. The information processing apparatus according to claim 1.
6. The first input plan and the second input plan represent at least one of the following: the order in which multiple products are introduced into the manufacturing line, the number of products to be introduced, and the timing of the introduction. The information processing apparatus according to claim 1.
7. The first input plan and the second input plan represent the sequence in which multiple products are input into the manufacturing line. The second modification process is a process that randomly changes the order indicated by the first input plan. The information processing apparatus according to claim 6.
8. The aforementioned processing unit, A simulation unit that performs the aforementioned simulation, A calculation unit that performs the aforementioned calculation process, A first modification unit that performs the first modification process, A second modification unit that performs the second modification process, A control unit that repeatedly performs the simulation, the calculation process, the first modification process, and the second modification process, Equipped with, The information processing apparatus according to claim 1.
9. An information processing method performed by an information processing device, Using a first input plan for a manufacturing line that produces multiple types of products, a simulation of manufacturing by the said manufacturing line is performed. Using the results of the simulation, a process is performed to calculate evaluation values representing the productivity of each of the multiple products. If the aforementioned evaluation value does not meet the predetermined conditions, the first modification process is executed to modify the first input plan and generate the second input plan so that the difference between the modified input plan (the second input plan) and the first input plan falls within a specified range. If the evaluation value satisfies the conditions, a second modification process is executed to modify the first input plan and generate the second input plan in a manner different from the first modification process. This includes repeatedly executing the simulation, the calculation process, the first modification process, and the second modification process, The aforementioned condition is a condition that indicates that the number of times the statistical quantity of the evaluation value falls below the second threshold when the simulation, calculation process, first modification process, and second modification process are repeatedly executed is greater than or equal to a specified number. Information processing methods.
10. On the computer, The steps include: running a simulation of manufacturing by a manufacturing line using a first input plan for a manufacturing line that manufactures multiple types of products; The steps include: using the results of the simulation, performing a process to calculate evaluation values representing the productivity of each of the multiple products; If the aforementioned evaluation value does not meet predetermined conditions, the first modification process is performed to modify the first input plan and generate the second input plan so that the difference between the modified input plan (the second input plan) and the first input plan falls within a specified range. If the evaluation value satisfies the conditions, the step of executing a second modification process to modify the first input plan and generate the second input plan in a method different from the first modification process, The steps of repeatedly executing the simulation, the calculation process, the first modification process, and the second modification process are performed. The aforementioned condition is a condition that indicates that the number of times the statistical quantity of the evaluation value falls below the second threshold when the simulation, calculation process, first modification process, and second modification process are repeatedly executed is greater than or equal to a specified number. program.