Control rule generation device, performance reflection device, and control rule generation system

Abstract

To ensure robustness against production fluctuation.SOLUTION: A control rule generation device for generating a control rule for a production facility including at least a production device comprises: a rule storage unit that stores a control program for realizing a candidate of dispatching rule as a control rule available for each production facility and the dispatching rule; and a control rule allocation unit that identifies a dispatching rule as the dispatching rule to be applied to each production facility, according to a prescribed production plan from among the candidates of dispatching rule, and that transfers the control program corresponding to the identified dispatching rule to the production facility.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a control rule generation device, a performance reflection device, and a control rule generation system. [Background technology]

[0002] In recent years, businesses, not just corporations, have tended to be required to achieve both resilience and improved management efficiency. One solution to this is to build an open supply chain that starts from the customer.

[0003] From the perspective of computer systems, a supply chain provides a system or device that serves as the foundation for building a supply chain in which at least two or more business entities participate, from material procurement to sales of products. In a supply chain system, the participating business entities (also called suppliers) are expected to dynamically manufacture the various parts and products they supply.

[0004] In such supply chains, it is important for suppliers to flexibly formulate production plans and carry out production quickly. It is particularly important to reflect production plans in specific control rules for production equipment without impairing production efficiency, and to quickly control the specific operations of the production equipment. It is known that flexible lines and job shop lines, in particular, require rapid changes to control rules to converge on the effects of production fluctuations, such as delays.

[0005] Patent Document 1 describes a technique in which a production plan is broken down into events, the events are classified according to whether or not a changeover is required, and a start time is set for each classification to generate an operation plan. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Publication No. 2019-168763 Summary of the Invention [Problem to be solved by the invention]

[0007] In the technology described in Patent Document 1, when a delay occurs, the order of events included in the operation plan is slightly changed, but an operation plan is generated in which each event is delayed according to fixed rules. Therefore, in production sites typified by job shops, even if the operation plan is revised, it is not possible to prevent a decline in production efficiency. This is because the impact of the delay propagates and affects multiple production facilities responsible for downstream processes and the progress of the products scheduled to be processed there.

[0008] An object of the present invention is to ensure robustness against production fluctuations. [Means for solving the problem]

[0009] In order to solve the above-mentioned problems, the present application employs, for example, the means set forth in the claims. The present invention includes a plurality of means for solving the above-mentioned problems, and one example thereof is a control rule generation device that generates control rules for production facilities including at least production equipment, the device comprising: a rule storage unit that stores candidate dispatching rules as control rules available for each of the production facilities and control programs that realize the dispatching rules; and a control rule allocation unit that identifies, for each of the production facilities, a dispatching rule that corresponds to a predetermined production plan from the candidate dispatching rules as the dispatching rule to be applied, and transfers the control program that corresponds to the identified dispatching rule to the production facilities. [Effects of the Invention]

[0010] According to the present invention, it is possible to provide a technique for ensuring robustness against production fluctuations.

[0011] Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a control rule generation system. [Figure 2] FIG. 10 illustrates an example of a data structure of a rule storage unit; [Figure 3] FIG. 2 is a diagram illustrating an example of a data structure of a production plan storage unit. [Figure 4] FIG. 10 is a diagram illustrating an example of a data structure of an ST distribution storage unit. [Figure 5] FIG. 10 illustrates an example of a data structure of an allocation storage unit. [Figure 6] FIG. 2 illustrates an example of a hardware configuration of a control rule generation device. [Figure 7] FIG. 10 is a diagram illustrating an example of a flowchart of a control rule allocation process. [Figure 8] FIG. 10 illustrates an example of a data structure of a threshold storage unit. [Figure 9] FIG. 2 is a diagram illustrating an example of a data structure of a production performance storage unit. [Figure 10] FIG. 10 illustrates an example of a data structure of an update history storage unit; [Figure 11] FIG. 10 is a diagram illustrating an example of a flowchart of a deviation determination process. [Figure 12] FIG. 10 illustrates an example of a flowchart of an update instruction process. [Figure 13] FIG. 10 is a diagram illustrating an example of a flowchart of a control rule update evaluation process. [Figure 14] FIG. 10 is a diagram illustrating an example of a flowchart of a performance reflection process. [Figure 15] FIG. 10 is a diagram showing an example of a control rule generation result screen. DETAILED DESCRIPTION OF THE INVENTION

[0013] In the following embodiments, for convenience, when necessary, the description will be divided into multiple sections or embodiments, but unless otherwise expressly stated, they are not unrelated to each other, and one is a partial or complete variation, detail, supplementary explanation, etc. of the other.

[0014] Furthermore, in the following embodiments, when referring to the number of elements (including the number, numerical value, amount, range, etc.), unless otherwise specified or when it is clearly limited to a specific number in principle, it is not limited to that specific number and may be more or less than the specific number.

[0015] Furthermore, in the following embodiments, the components (including element steps, etc.) are not necessarily essential unless otherwise specified or unless they are clearly considered essential in principle.

[0016] Similarly, in the following embodiments, when referring to the shapes, positional relationships, etc. of components, etc., it is intended to include those that are substantially similar or similar to those shapes, etc., unless otherwise specified or when it is considered that this is clearly not the case in principle. This also applies to the above numerical values ​​and ranges.

[0017] In addition, in all the drawings for explaining the embodiments, the same components are generally given the same reference numerals, and repeated explanations thereof will be omitted. However, when there is a high possibility of confusion arising from environmental changes, etc., if the same components share the same names as the components before the change, different reference numerals or names may be given to the same components.

[0018] In the following embodiments, the "input / output interface unit" may be one or more interface devices. The one or more interface devices may be at least one of the following: One or more I / O (Input / Output) interface devices. The I / O interface device is an interface device for at least one of the I / O device and a remote display computer. The I / O interface device for the display computer may be a communications interface device. The at least one I / O device may be a user interface device, for example, either an input device such as a keyboard and a pointing device, or an output device such as a display device. One or more communication interface devices. The one or more communication interface devices may be one or more homogeneous communication interface devices (e.g., one or more NICs (Network Interface Cards)) or two or more heterogeneous communication interface devices (e.g., an NIC and an HBA (Host Bus Adapter)).

[0019] In the following description, "memory" refers to one or more memory devices, which are an example of one or more storage devices, and may typically be a primary storage device. At least one memory device in the memory may be a volatile memory device or a non-volatile memory device.

[0020] In the following description, a "persistent storage device" may refer to one or more persistent storage devices, which are an example of one or more storage devices. A persistent storage device may typically be a non-volatile storage device (e.g., an auxiliary storage device), and specifically may be, for example, a hard disk drive (HDD), a solid state drive (SSD), a non-volatile memory express (NVME) drive, or a storage class memory (SCM).

[0021] In the following description, a "storage unit" or a "storage device" may refer to either a memory or a persistent storage device, or both.

[0022] Also, in the following description, a "processing unit" or a "processor" may refer to one or more processor devices. The at least one processor device may typically be a microprocessor device such as a CPU (Central Processing Unit). However, it may also be another type of processor device such as a GPU (Graphics Processing Unit). The at least one processor device may be a single-core or multi-core. The at least one processor device may also be a processor core. The at least one processor device may also be a processor device in a broader sense, such as a circuit that is a collection of gate arrays written in a hardware description language that performs some or all of the processing (e.g., an FPGA (Field-Programmable Gate Array), a CPLD (Complex Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit)).

[0023] Furthermore, in the following description, functions may be described using the expression "yyy unit." However, the functions may be realized by one or more computer programs executed by a processor, by one or more hardware circuits (e.g., FPGAs or ASICs), or by a combination thereof. When a function is realized by a program executed by a processor, the specified processing is performed using a storage device and / or an interface device, etc., as appropriate, and therefore the function may be considered to be at least a part of the processor. Processing described using a function as the subject may be processing performed by a processor or a device having the processor. A program may be installed from a program source. The program source may be, for example, a computer from which the program is distributed or a computer-readable recording medium (e.g., a non-transitory recording medium). The description of each function is merely an example; multiple functions may be combined into one function, or one function may be divided into multiple functions.

[0024] In the following description, processing may be described using a "program" or a "processing unit" as the subject, but processing described using a program as the subject may also be processing performed by a processor or a device having that processor. Two or more programs may be realized as one program, or one program may be realized as two or more programs.

[0025] In the following description, information that provides an output for an input may be described using expressions such as "xxx table," but this information may be a table of any structure, or may be a neural network that generates an output for an input, or a learning model such as a genetic algorithm or random forest. Therefore, the "xxx table" may be referred to as "xxx information." In the following description, the structure of each table is an example, and one table may be divided into two or more tables, or all or part of two or more tables may be one table.

[0026] Furthermore, in the following description, the "control rule generation device" and the "achievement reflection device" may be a system configured with one or more physical computers, or may be a system (e.g., a cloud computing system) realized on a group of physical computing resources (e.g., a cloud infrastructure). When the control rule generation device 100 "displays" the display information, it may mean that the display information is displayed on a display device possessed by the computer, or that the computer transmits the display information to a display computer. In the latter case, the display information is displayed by the display computer. Hereinafter, each embodiment of the present invention will be described with reference to the drawings.

[0027] 1 is a diagram showing an example of the configuration of a control rule generation system 10. The control rule generation system 10 includes a control rule generation device 100, a performance reflection device 200, a schedule generation device 300, an MES (Manufacturing Execution System) 310, a control device 400, production equipment 410, transportation equipment 420, and a network 50 that connects these devices together so that they can communicate with each other.

[0028] The network 50 is, for example, any one of a LAN (Local Area Network), a WAN (Wide Area Network), a VPN (Virtual Private Network), a communication network that uses a general public line such as the Internet in part or in whole, a mobile phone communication network, etc. The network may also be a wireless communication network such as Wi-Fi (registered trademark) or 5G (Generation).

[0029] The control rule generation device 100 includes a storage unit 110, a processing unit 120, an input / output interface unit 130, and a communication unit 140. The storage unit 110 includes a rule storage unit 111, a production plan storage unit 112, an ST distribution storage unit 113, and an allocation storage unit 114. The processing unit 120 includes a control rule allocation unit 121.

[0030] 2 is a diagram showing an example of the data structure of the rule storage unit. The rule storage unit 111 stores candidate dispatching rules as control rules that can be used for each production facility 410 and transport facility 420, which include at least production equipment, and control programs that implement the dispatching rules. Specifically, the rule storage unit 111 has an equipment ID column 111a, a rule name column 111b, and a control program ID column 111c. The equipment ID column 111a, the rule name column 111b, and the control program ID column 111c are associated with each other.

[0031] The facility ID column 111a stores information specifying a facility ID, which is identification information that uniquely identifies the production facility 410 or the production resource of the production area, the transport facility 420 or the transport resource of the production area.

[0032] The rule name column 111b stores the name of a dispatching rule that can be used by the production equipment 410 and the transport equipment 420 identified in the equipment ID column 111a. A dispatching rule is a rule that determines the processing order of products in progress. Examples of dispatching rules include existing rules such as FIFO (First In First Out), EDD (Earliest Due Date), SLACK, and SPT (Shortest Processing Time).

[0033] The control program ID column 111c stores information that identifies a control program that implements the dispatching rule identified in the rule name column 111b.

[0034] 3 is a diagram showing an example of the data structure of the production plan storage unit 112. The production plan storage unit 112 stores information acquired from the schedule generation device 300. The production plan storage unit 112 has an equipment ID column 112a, a product ID column 112b, a quantity column 112c, a process ID column 112d, a scheduled start time column 112e, and a scheduled end time column 112f.

[0035] The equipment ID column 112a, the product ID column 112b, the quantity column 112c, the process ID column 112d, the scheduled start time column 112e, and the scheduled end time column 112f are associated with each other.

[0036] The facility ID column 112a stores information specifying a facility ID, which is identification information that uniquely identifies the production facility 410 or the production resource of the production area, the transport facility 420 or the transport resource of the production area.

[0037] The product ID column 112b stores a product ID that identifies a product. The product ID is information that uniquely identifies a product, part, or other product that is produced or transported by the production facility 410 or transport facility 420 identified in the facility ID column 112a.

[0038] The quantity column 112c stores information specifying the quantity of the product specified by the product ID column 112b.

[0039] The process ID column 112d stores a process ID that identifies a process. The process ID is information that uniquely identifies a process in which a product identified in the product ID column 112b is processed in the production equipment 410 and the transport equipment 420 identified in the equipment ID column 112a.

[0040] The scheduled start time column 112e stores information specifying the scheduled start time of the process specified in the process ID column 112d. The process is a process for the product specified in the product ID column 112b in the production facility 410 specified in the facility ID column 112a.

[0041] The estimated end time column 112f stores information specifying the estimated time when processing of the process specified in the process ID column 112d is to be completed. The process is a process for the product specified in the product ID column 112b in the production facility 410 specified in the facility ID column 112a.

[0042] 4 is a diagram showing an example of the data structure of the ST distribution storage unit 113. The ST distribution storage unit 113 stores information acquired from the performance result reflection device 200. The ST distribution storage unit 113 has an equipment ID column 113a, a process ID column 113b, an ST average column 113c, and an ST variance column 113d.

[0043] The equipment ID column 113a, the process ID column 113b, the ST average column 113c, and the ST variance column 113d are associated with each other.

[0044] The facility ID column 113a stores information specifying a facility ID, which is identification information that uniquely identifies the production facility 410 or the production resource of the production area, the transport facility 420 or the transport resource of the production area.

[0045] The process ID column 113b stores a process ID that identifies a process. The process ID is information that uniquely identifies a process that is performed by the production equipment 410 and the transport equipment 420 identified by the equipment ID column 113a.

[0046] The ST average column 113c stores the average value of ST (Standard Time) required for processing a process. The process is the process identified by the process ID column 113b in the production facility 410 identified by the facility ID column 113a.

[0047] The ST variance column 113d stores the variance value of the ST for processing in a process, which is the process specified by the process ID column 113b in the production facility 410 specified by the facility ID column 113a.

[0048] Note that an example in which representative values ​​(mean and variance) assuming a normal distribution as the ST distribution are stored has been shown as an example of the ST distribution storage unit 113. However, in the case of other distributions, it is sufficient that representative values ​​of the distribution are stored.

[0049] 5 is a diagram showing an example of the data structure of the allocation storage unit. The allocation storage unit 114 stores an equipment ID column 114a, a time period column 114b, an allocation rule name column 114c, and a control program ID column 114d. The equipment ID column 114a, the time period column 114b, the allocation rule name column 114c, and the control program ID column 114d are associated with each other.

[0050] The facility ID column 114a stores information specifying a facility ID, which is identification information that uniquely identifies the production facility 410 or the production resource of the production area, the transport facility 420 or the transport resource of the production area.

[0051] The time period column 114b stores information indicating a specific period of a day, such as "9:00-15:00." This time period is the time period during which the dispatching rule specified in the allocation rule name column 114c is applied to the production equipment 410 and transport equipment 420 specified in the equipment ID column 114a.

[0052] The allocation rule name column 114c stores the rule name of the dispatching rule allocated to the production facility 410 or the transport facility 420 identified by the facility ID column 114a.

[0053] The control program ID column 114d stores information that identifies the control program that implements the dispatching rule identified in the allocation rule name column 114c.

[0054] Returning to the explanation of Fig. 1, the control rule allocation unit 121 of the processing unit 120 identifies a dispatching rule corresponding to a predetermined production plan from among candidate dispatching rules as a dispatching rule to be applied to each production facility 410 or each transport facility 420. Then, the control rule allocation unit 121 transfers a control program corresponding to the identified dispatching rule to the production facility 410 or each transport facility 420.

[0055] Furthermore, in the process of identifying a dispatching rule, the control rule allocation unit 121 estimates the work time of the production process included in the production plan using statistical errors, and identifies the dispatching rule using the compliance rate with the production plan (robust optimization).Alternatively, in the process of identifying a dispatching rule, the control rule allocation unit 121 performs a simulation in which the dispatching rule is applied to each time period, and identifies the dispatching rule using the compliance rate with the production plan.

[0056] In the process of identifying a dispatching rule, the control rule allocation unit 121 can determine the dispatching rule by, for example, investigating all possible combinations of rules for each production facility 410 or transport facility 420 and finding an index. Alternatively, the control rule allocation unit 121 can efficiently find the optimal dispatching rule for each facility by searching using genetic programming.

[0057] The input / output interface unit 130 receives input of various data. Specifically, the input / output interface unit 130 receives input of information to be stored in the production plan storage unit 112 from a user.

[0058] The communication unit 140 communicates with other devices via the network 50. The other devices include the performance reflection device 200, the schedule generation device 300, the MES 310, the control device 400, the production equipment 410, and the transport equipment 420.

[0059] 6 is a diagram showing an example of the hardware configuration of a control rule generation device. The control rule generation device 100 can be realized as a general computer 900 including a processor (e.g., a central processing unit (CPU) or a graphics processing unit (GPU)) 901, a memory 902 such as a random access memory (RAM), an external storage device 903 such as a hard disk drive (HDD) or a solid state drive (SSD), a reading device 905 that reads information from a portable storage medium 904 such as a compact disk (CD) or a digital versatile disk (DVD), an input device 906 such as a keyboard, mouse, barcode reader, or touch panel, an output device 907 such as a display, and a communication device 908 that communicates with other computers via a communication network such as a LAN or the Internet, or as a network system including a plurality of such computers 900. Note that the reading device 905 may be capable of not only reading but also writing to the portable storage medium 904.

[0060] The processor 901 performs various processes by executing a predetermined control rule generation program loaded from the external storage device 903 into the memory 902. The control rule generation program is, for example, an application program that can be executed on an OS (Operating System) program. The control rule generation program may be installed into the external storage device 903 from a portable storage medium 904 via the reading device 905, or may be downloaded from a network via the communication device 908 and executed by the processor 901.

[0061] For example, the control rule allocation unit 121 can be realized by loading a control rule generation program stored in an external storage device 903 into the memory 902 and executing it with the processor 901. The input / output interface unit 130 can be realized by the processor 901 using the input device 906, the output device 907, and the communication device 908. The storage unit 110 can be realized by the processor 901 using the memory 902 or the external storage device 903. The communication unit 140 can be realized by the processor 901 using the communication device 908.

[0062] 7 is a diagram showing an example of a flowchart of the control rule allocation process. The control rule allocation process is started when a start instruction is received from a user or the like. Alternatively, the control rule allocation process may be started at a predetermined date and time (e.g., 6:00 AM every day) or at predetermined intervals (e.g., every 12 hours).

[0063] First, the control rule allocation unit 121 reads a production plan (step S111). Specifically, the control rule allocation unit 121 reads the production plan stored in the production plan storage unit 112.

[0064] Then, the control rule allocation unit 121 acquires candidate dispatching rules for each facility (step S112). Specifically, the control rule allocation unit 121 reads candidate dispatching rules for each production facility 410 and each transport facility 420 from the rule storage unit 111.

[0065] Then, the control rule allocation unit 121 allocates a dispatching rule for each piece of equipment (step S113). Specifically, the control rule allocation unit 121 determines a dispatching rule for each piece of production equipment 410 and each piece of transport equipment that best reproduces the production plan. For example, the control rule allocation unit 121 uses a simulator and determines a dispatching rule for each piece of equipment so as to maximize the degree of agreement using an index that indicates the degree of agreement between the simulation results and the production plan stored in the production plan storage unit 112. The control rule allocation unit 121 stores the allocation results in the allocation storage unit 114.

[0066] Here, the control rule allocation unit 121 uses, as the simulator, a discrete event simulator that simulates the operations of the control device 400, the production equipment 410, and the transport equipment 420. An index representing the degree of agreement can be, for example, plan adherence rate = Σ_(all equipment) (number of tasks that adhered to the scheduled completion time of the equipment's production plan) / (total number of tasks for the equipment). Alternatively, for example, plan sequence agreement rate = Σ_(all equipment) (number of tasks that agreed with the work order in the production plan for the equipment) / (total number of tasks for the equipment). Alternatively, a weighted sum of the plan adherence rate and the plan sequence agreement rate can be used as an index.

[0067] Then, the control rule allocation unit 121 transmits a control program corresponding to the dispatching rule for each facility to the control device 400, the production facility 410, and the transport facility 420 (step S114). Specifically, the control rule allocation unit 121 identifies a control program corresponding to the dispatching rule allocated for each facility by referring to the allocation storage unit 114, and transmits the control program to the control device 400, the production facility 410, and the transport facility 420.

[0068] This is the flow of the control rule allocation process. The control rule allocation process makes it possible to rearrange the processing order between and within processes when a delay occurs, thereby ensuring robustness against production fluctuations.

[0069] Returning to the explanation of Fig. 1, the performance reflecting device 200 includes a storage unit 210, a processing unit 220, an input / output interface unit 230, and a communication unit 240. The storage unit 210 includes a threshold value storage unit 211, a production performance storage unit 212, and an update history storage unit 213. The processing unit 220 includes a deviation determination unit 221, an update instruction unit 222, a control rule update evaluation unit 223, and a performance reflecting unit 224.

[0070] 8 is a diagram showing an example of the data structure of the threshold storage unit. The threshold storage unit 211 stores an equipment ID column 211a, an index column 211b, a control change threshold column 211c, and a plan change threshold column 211d. The equipment ID column 211a, the index column 211b, the control change threshold column 211c, and the plan change threshold column 211d are associated with each other. Furthermore, these thresholds are threshold information used for deviation determination, which will be described later.

[0071] The facility ID column 211a stores information specifying a facility ID, which is identification information that uniquely identifies the production facility 410 or the production resource of the production area, the transport facility, or the transport resource of the production area.

[0072] The indicator column 211b stores information specifying an indicator for evaluating the appropriateness of operation of the equipment specified in the equipment ID column 211a. The aforementioned plan adherence rate and plan order match rate are indicators of the appropriateness of operation.

[0073] The control change threshold column 211c stores a threshold for a predetermined index for each facility. The threshold is a threshold for determining whether or not to change the control rule. The facility is identified by the facility ID column 211a, and the index is identified by the index column 211b.

[0074] The plan change threshold column 211d stores a threshold value for a predetermined index for each facility. The threshold value is a threshold value for determining whether or not to change the production plan. The facility is identified by the facility ID column 211a, and the index is identified by the index column 211b.

[0075] 9 is a diagram showing an example of the data structure of the production record storage unit. The production record storage unit 212 stores information acquired from the MES 310, which will be described later. Specifically, the production record storage unit 212 stores an equipment ID column 212a, a product ID column 212b, a quantity column 212c, a process ID column 212d, a start time column 212e, an end time column 212f, and a production in progress flag column 212g.

[0076] The equipment ID column 212a, the product ID column 212b, the quantity column 212c, the process ID column 212d, the start time column 212e, the end time column 212f, and the construction in progress flag column 212g are associated with each other.

[0077] The facility ID column 212a stores information specifying a facility ID, which is identification information that uniquely identifies the production facility 410 or the production resource of the production area, and the transport facility 420 or the transport resource of the production area.

[0078] The product ID column 212b stores a product ID that identifies a product. The product ID is information that uniquely identifies a product, part, or other product produced or transported by the production facility 410 or transport facility 420 identified in the facility ID column 212a.

[0079] The quantity column 212c stores information specifying the quantity of the product specified by the product ID column 212b.

[0080] The process ID column 212d stores a process ID that identifies a process. The process ID is information that uniquely identifies a process in which a product identified in the product ID column 212b is processed in the production equipment 410 and the transport equipment 420 identified in the equipment ID column 212a.

[0081] The start time column 212e stores information specifying the time at which processing of the process specified in the process ID column 212d started. This process is a process for the product specified in the product ID column 212b in the production facility 410 specified in the facility ID column 212a.

[0082] The end time column 212f stores information specifying the time when the processing of the process specified in the process ID column 212d was completed. If the processing is incomplete, this column is left blank. The process is a process for the product specified in the product ID column 212b in the production equipment 410 specified in the equipment ID column 212a.

[0083] The in-process flag column 212g stores information identifying whether the processing of the process identified by the process ID column 212d is in progress or has been completed. The process is a process for the product identified by the product ID column 212b in the production facility 410 identified by the facility ID column 212a. For example, if the processing is complete, the value of the in-process flag column 212g is "0," and if the processing has started, the value of the in-process flag column 212g is "1."

[0084] 10 is a diagram showing an example of the data structure of the update history storage unit 213. The update history storage unit 213 stores a facility ID column 213a, a change instruction time column 213b, and a change type column 213c.

[0085] The equipment ID column 213a, the change instruction time column 213b, and the change type column 213c are associated with each other.

[0086] The facility ID column 213a stores information specifying a facility ID, which is identification information that uniquely identifies the production facility 410 or the production resource of the production area, and the transport facility 420 or the transport resource of the production area.

[0087] The change instruction time column 213b stores information specifying the time when the update instruction unit 222 issued a change instruction, which will be described later, for the production equipment 410 or the transport equipment 420 specified in the equipment ID column 213a.

[0088] The change type column 213c stores information that identifies the type of change instruction issued in the change instruction time column 213b for the production equipment 410 or transport equipment 420 identified in the equipment ID column 213a. There are two types of change instructions: "control" which corresponds to a change in the control program, and "plan" which corresponds to a change in the production plan.

[0089] Returning to the explanation of Fig. 1, the deviation determination unit 221 identifies the deviation between a predetermined production plan for a predetermined period and the actual production results related to the production plan, and determines whether or not the control rules for the production equipment 410 or the production plan need to be updated based on the degree of deviation. In this deviation determination process, the deviation determination unit 221 executes a production simulation within a specified planning period, starting from the progress of the execution time. The deviation determination unit 221 calculates the degree of deviation between the simulation results and the production plan stored in the production plan storage unit 112.

[0090] Here, the deviation determination unit 221 uses a discrete event simulator that simulates the operations of the control device 400, the production equipment 410, and the transport equipment 420 as the simulator. An index representing the degree of deviation can be, for example, 1 - plan adherence rate. Here, plan adherence rate = Σ_(all equipment) (number of tasks that adhered to the scheduled completion time of the equipment's production plan) / (total number of tasks for the equipment). Alternatively, for example, the index can be 1 - plan sequence consistency rate. Here, plan sequence consistency rate = Σ_(all equipment) (number of tasks that match the task sequence in the equipment's production plan) / (total number of tasks for the equipment). Alternatively, the index can be 1 - (weighted sum of plan adherence rate and plan sequence consistency rate).

[0091] Furthermore, in the process of determining whether or not the control rule or production plan of the production equipment 410 needs to be updated, the deviation determination unit 221 compares the deviation described above with the control change threshold column 211c and the plan change threshold column 211d for each piece of equipment stored in the threshold storage unit 211. Then, the deviation determination unit 221 determines that an update is required for equipment whose deviation exceeds either of the thresholds.

[0092] When the control rules or the production plan need to be updated, the update instruction unit 222 instructs a predetermined control rule generation device 100, which determines the control rules for the production equipment 410 for the production plan, to update the control rules, depending on the degree of deviation, or instructs a predetermined schedule generation device that generated the production plan to update the production plan.

[0093] In the process of determining whether to update the control rule or the production plan of the production equipment 410, the update instruction unit 222 compares the deviation degree with the control change threshold value column 211c and the plan change threshold value column 211d for each piece of equipment stored in the threshold value storage unit 211. Then, the update instruction unit 222 determines whether to update based on the threshold value that the deviation degree exceeds.

[0094] That is, the update instruction unit 222 determines that the production plan needs to be updated when the deviation exceeds both the control change threshold value field 211c and the plan change threshold value field 211d. Also, the update instruction unit 222 determines that the control rule needs to be updated when the deviation exceeds the control change threshold value field 211c but does not meet the plan change threshold value field 211d.

[0095] If the production plan needs to be updated, the update instruction unit 222 instructs the schedule generation device 300 to update the production plan, and if the control rule needs to be updated, it instructs the control rule generation device 100 to update the control rule.

[0096] The control rule update evaluation unit 223 updates the thresholds for determining the degree of deviation. Specifically, the control rule update evaluation unit 223 resets the control change threshold field 211c and the plan change threshold field 211d, giving top priority to preventing delays and second priority to preventing excessive updates. More specifically, the control rule update evaluation unit 223 performs a production simulation using production results for each state in which the thresholds in the control change threshold field 211c and the plan change threshold field 211d are varied for the time period in which an update instruction is issued, and identifies the thresholds according to the priority criteria described above.

[0097] The actual result reflecting unit 224 updates the statistics of the operation time of the process in the production plan using the production actual result. Specifically, for each process performed by the equipment, the ST average and ST variance are calculated based on the statistics of the operation time results, and the ST distribution storage unit 113 is updated.

[0098] The input / output interface unit 230 receives input of various data. Specifically, the input / output interface unit 230 receives input of information to be stored in the threshold value storage unit 211 or the like from a user.

[0099] The communication unit 240 communicates with other devices via the network 50. The other devices include the control rule generation device 100, the schedule generation device 300, the MES 310, the control device 400, the production equipment 410, and the transport equipment 420.

[0100] The performance result reflecting device 200 has the same hardware configuration as the control rule generation device 100. For example, the deviation determination unit 221, the update instruction unit 222, the control rule update evaluation unit 223, and the performance result reflecting unit 224 can be realized by loading programs stored in an external storage device 903 into a memory 902 and executing them with a processor 901, the input / output interface unit 230 can be realized by the processor 901 using an input device 906, an output device 907, and a communication device 908, and the storage unit 210 can be realized by the processor 901 using the memory 902 or the external storage device 903. The communication unit 240 can be realized by the processor 901 using the communication device 908.

[0101] 11 is a diagram showing an example of a flowchart of the deviation determination process. The deviation determination process is started when a start instruction is received from a user or the like. Alternatively, the deviation determination process may be started at a predetermined date and time (e.g., 6:00 AM every day) or at predetermined intervals (e.g., every 12 hours).

[0102] First, the deviation determination unit 221 reads the production results stored in the production result storage unit 212 (step S211).

[0103] Then, the deviation determination unit 221 executes a simulation within the specified planning period, starting from the progress of the execution time (step S212).

[0104] Then, the deviation determining unit 221 uses the simulation results to calculate the degree of deviation for each piece of equipment within the planning period with respect to the predetermined index (step S213).

[0105] Then, the deviation determining unit 221 compares the deviation degree with the threshold values ​​for the production equipment 410 and the transport equipment 420 stored in the threshold storage unit 211 to determine whether or not updating is necessary (step S214).

[0106] Then, the deviation determination unit 221 transmits the determination result to the update instruction unit 222 (step S215).

[0107] The above is the flow of the deviation determination process. The deviation determination process makes it possible to determine whether the actual production results deviate from the production plan, and if so, how much the deviation is.

[0108] 12 is a diagram showing an example of a flowchart of the update instruction process. The update instruction process is started after step S215 of the deviation determination process is performed.

[0109] First, the update instruction unit 222 acquires the determination result of the deviation determination unit 221 (step S221). Then, the update instruction unit 222 determines whether the deviation calculated by the deviation determination unit 221 exceeds the control change threshold value field 211c (step S222). If the deviation value does not exceed the control change threshold value field 211c ("No" in step S222), the update instruction unit 222 advances the control to step S227.

[0110] If the deviation exceeds the value in the control change threshold field 211c ("Yes" in step S222), the update instruction unit 222 determines whether the deviation calculated by the deviation determination unit 221 exceeds the value in the plan change threshold field 211d (step S223). If the deviation does not exceed the value in the plan change threshold field 211d ("No" in step S223), the update instruction unit 222 advances the control to step S225.

[0111] If the deviation exceeds the plan change threshold value field 211d (if "Yes" in step S223), the update instruction unit 222 issues a reschedule instruction to the schedule generation device 300 (step S224).

[0112] If the deviation does not exceed the plan change threshold field 211d ("No" in step S223), the update instruction unit 222 issues an instruction to update the dispatching rules to the control rule generation device 100 (step S225).

[0113] Then, the control rule allocation unit 121 of the control rule generation device 100, which receives the request to update the dispatching rules from the update instruction unit 222, executes processing (step S226). Specifically, the control rule allocation unit 121 reflects the production status (process status including not yet started, in progress, and finished) at the execution time, and reallocates dispatching rules to be applied to related equipment for the production plan for a predetermined period after the execution time. The same algorithm as that used in step S113 of the control rule allocation process is applied to this dispatching rule allocation.

[0114] Then, the update instruction unit 222 stores the update history in the update history storage unit 213 (step S227).

[0115] The above is the flow of the update instruction process. According to the update instruction process, it is possible to instruct the reassignment of control rules depending on the degree of deviation of the actual production results from the production plan, or to instruct the replanning of the production plan if the degree of deviation is greater than a predetermined value.

[0116] 13 is a diagram showing an example of a flowchart of the control rule update evaluation process. The control rule update evaluation process is started when a start instruction is received from a user or the like. Alternatively, the control rule update evaluation process may be started at a predetermined date and time (for example, 4:00 AM every day) or at predetermined intervals (for example, every 12 hours).

[0117] First, the control rule update evaluation unit 223 reads the production record of a predetermined facility for a predetermined period (step S231). Specifically, the control rule update evaluation unit 223 reads the production record stored in the production record storage unit 212 for the predetermined period for the predetermined production facility 410.

[0118] Then, the control rule update evaluation unit 223 acquires the update history stored in the update history storage unit 213 for the control rule of the predetermined production equipment 410 during the predetermined period (step S232).

[0119] Then, the control rule update evaluation unit 223 calculates a control change threshold value and a plan change threshold value for the predetermined production equipment 410 and transport equipment 420. Based on the results, the control rule update evaluation unit 223 updates the control change threshold value field 211c and the plan change threshold value field 211d in the threshold value storage unit 211 (step S233).

[0120] Here, the control rule update evaluation unit 223 varies the threshold value in various ways in predetermined production cycle units such as daily or weekly, and compares it with the deviation. Then, the control rule update evaluation unit 223 may count the number of times an instruction to update a dispatching rule is issued to the control rule generation device 100 and an instruction to reschedule is issued to the schedule generation device 300, and calculate a threshold value that minimizes the number of times an instruction is issued while the plan compliance rate and the plan sequence consistency rate satisfy predetermined standards.

[0121] The above is an example of a flowchart of the control rule update evaluation process. The control rule update evaluation process can automatically optimize the control change threshold value that triggers a control change of equipment and the plan change threshold value that triggers a change in the production plan.

[0122] 14 is a diagram showing an example of a flowchart of the performance record reflection process. The performance record reflection process is started when a start instruction is received from a user or the like. Alternatively, the performance record reflection process may be started at a predetermined date and time (for example, 4:00 AM every day) or at predetermined intervals (for example, every 12 hours).

[0123] First, the performance reflecting unit 224 reads the production performance stored in the production performance storage unit 212 for a predetermined production facility 410 during a predetermined period (step S241).

[0124] Then, the performance reflecting unit 224 calculates statistical values ​​(for example, ST average, ST variance) of the operation time for each process for the predetermined production equipment 410 (step S242).

[0125] Then, the performance reflecting unit 224 stores the calculated statistical values ​​in the ST distribution storage unit 113 of the control rule generation device 100 for each process of the production equipment 410 (step S243).

[0126] Then, the performance reflecting unit 224 reflects the statistical value in the master value of the simulator of the control rule generation device 100 (step S244).

[0127] The above is an example of a flowchart of the performance reflection process. The performance reflection process makes it possible to automatically make the statistical values ​​that are the basis for use in the facility simulation correspond to the actual situation.

[0128] The schedule generation device 300 is a device that creates a production plan (production schedule) for each process for each production facility 410, targeting the factory, production system, production process, and manufacturing site for which the production plan is to be generated. For example, similar to that used in existing technologies, the schedule generation device 300 creates a future production plan using information such as the process flow for each product type, the standard work time for each process, production facility information used in each process, a factory production facility list and maintenance plan, a list of facilities for which workers are responsible, worker shift plans, master information including the factory operation calendar, information on products in process at the planned date and time, and information on input plans to the factory, and displays the plan as a Gantt chart.

[0129] The control rule generation device 100 may receive production plan data and the like from an MES 310 connected to the network, instead of the schedule generation device 300. The MES 310 collects or manages production performance information, equipment information, and worker information. In addition, the MES 310 transfers the production performance information, equipment information, and worker information to the control rule generation device 100 and the performance reflection device 200 in response to requests from the control rule generation device 100 and the performance reflection device 200.

[0130] The control device 400 uses a control program to control the production equipment 410 and the transport equipment 420. The control device 400 receives the control program from an operator or a higher-level system.

[0131] FIG. 15 is a diagram showing an example of a control rule generation result screen. The control rule generation result screen 600 is an example of a screen that accepts input of a facility ID identifying a production facility 410 or a transport facility 420 and displays a production plan and a control plan for the facility. The input area 610 is an area for selectively accepting a facility ID identifying the production facility 410 or the transport facility 420 to be displayed. The date and time display area 620 displays the current time. The summary display area 630 displays the planned value of a predetermined indicator, such as the plan adherence rate or the plan sequence match rate, and the most recently calculated current value. The production plan display area 640 displays the production plan stored in the production plan storage unit 112 in a Gantt chart for the facility ID entered in the input area 610. The control plan display area 650 displays a control plan including a dispatching rule (displayed as an adoption rule for each time period in the figure) generated by the control rule generation device 100 for the facility ID entered in the input area 610. This concludes the example of the control rule generation result screen.

[0132] The above is an example of the configuration of the control rule generation system according to the embodiment of the present invention. The control rule generation system 10 makes it possible to ensure robustness against production fluctuations.

[0133] It should be noted that the present invention is not limited to the above-described examples, and various modifications are included. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. It is possible to replace part of the configuration of an embodiment with another configuration, and it is also possible to add the configuration of another embodiment to the configuration of an embodiment. It is also possible to delete part of the configuration of an embodiment.

[0134] Furthermore, some or all of the above-described units, configurations, functions, processing units, etc. may be implemented in hardware, for example, by designing them as integrated circuits. Furthermore, the above-described units, configurations, functions, etc. may be implemented in software by a processor interpreting and executing a program that implements each function. Information such as the programs, tables, and files that implement each function can be stored in a memory, a recording device such as a hard disk, or a recording medium such as an IC card, SD card, or DVD.

[0135] It should be noted that the control lines and information lines in the above-described embodiments are those considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the product. In reality, it can be considered that almost all components are interconnected. The present invention has been described above, focusing on the embodiments. [Explanation of symbols]

[0136] 10: control rule generation system, 50: network, 100: control rule generation device, 110: memory unit, 111: rule memory unit, 112: production plan memory unit, 113: ST distribution memory unit, 114: allocation memory unit, 120: processing unit, 121: control rule allocation unit, 130: input / output interface unit, 140: communication unit, 200: performance reflection device, 210: memory unit, 211: threshold value memory unit, 212: production performance memory unit, 213: update history memory unit, 220: processing unit, 221: deviation determination unit, 222: update instruction unit, 223: control rule update evaluation unit, 224: performance reflection unit, 230: input / output interface unit, 240: communication unit, 300: schedule generation device, 310: MES, 400: control device, 410: production equipment, 420: conveyance equipment.

Claims

1. A control rule generation device that generates control rules for a production facility including at least a production device, a rule storage unit that stores candidate dispatching rules as control rules available for each piece of production equipment and control programs that implement the dispatching rules; a control rule allocation unit that identifies, for each of the production facilities, the dispatching rule corresponding to a predetermined production plan from among the dispatching rule candidates as the dispatching rule to be applied, and transfers the control program corresponding to the identified dispatching rule to the production facility; Equipped with In the process of identifying the dispatching rule, the control rule allocation unit estimates working times of production processes included in the production plan using a statistical error, and identifies the dispatching rule using an adherence rate to the production plan. A control rule generating device comprising:

2. A control rule generation device for generating control rules for production equipment including at least a production device, a rule storage unit that stores candidate dispatching rules as control rules available for each piece of production equipment and control programs that implement the dispatching rules; a control rule allocation unit that identifies, for each of the production facilities, the dispatching rule corresponding to a predetermined production plan from among the dispatching rule candidates as the dispatching rule to be applied, and transfers the control program corresponding to the identified dispatching rule to the production facility; Equipped with the control rule allocation unit, in the process of identifying the dispatching rule, performs a simulation in which the dispatching rule is applied to each time period, and identifies the dispatching rule using an adherence rate to the production plan. A control rule generating device comprising:

3. a deviation determination unit that identifies a deviation between a predetermined production plan and actual production results related to the production plan for a predetermined period, and determines whether or not a control rule for production equipment or the production plan needs to be updated based on the degree of the deviation; an update instruction unit that, when an update of a control rule for the production equipment or the production plan is necessary, instructs a predetermined control rule generation device that determines the control rule for the production equipment related to the production plan to update the control rule, or instructs a predetermined schedule generation device that generated the production plan to update the production plan, depending on the degree of deviation; a control rule update evaluation unit that updates the threshold value for determining the degree of deviation, with priority given to preventing delay; A performance reflection device comprising:

4. A deviation determination unit that identifies a deviation between a predetermined production plan for a predetermined period and actual production results related to the production plan, and determines whether or not a control rule for production equipment or the production plan needs to be updated based on the degree of the deviation; an update instruction unit that, when an update of a control rule for the production equipment or the production plan is necessary, instructs a predetermined control rule generation device that determines the control rule for the production equipment related to the production plan to update the control rule, or instructs a predetermined schedule generation device that generated the production plan to update the production plan, depending on the degree of deviation; a performance reflecting unit that updates statistics of work times of processes in the production plan using production performance; A performance reflection device comprising:

5. A control rule generation system including a control rule generation device that generates control rules for production equipment including at least a production device, and a performance reflection device, The control rule generation device a rule storage unit that stores candidate dispatching rules as control rules available for each piece of production equipment and control programs that implement the dispatching rules; a control rule allocation unit that identifies, for each of the production facilities, the dispatching rule corresponding to a predetermined production plan from among the dispatching rule candidates as the dispatching rule to be applied, and transfers the control program corresponding to the identified dispatching rule to the production facility; The performance reflection device is a deviation determination unit that identifies a deviation between the production plan and actual production results related to the production plan for a predetermined period and determines whether or not the control rule for the production equipment or the production plan needs to be updated based on the degree of the deviation; an update instruction unit that, when the control rule for the production equipment or the production plan needs to be updated, instructs the control rule generation device that determines the control rule for the production equipment related to the production plan to update the control rule, or instructs a predetermined schedule generation device that generated the production plan to update the production plan, depending on the degree of deviation. A control rule generation system comprising:

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