Production management system and operation method thereof

Abstract

The invention provides a production management system and an operation method thereof. The production management system comprises a memory and a processor. The processor executes a plurality of modules stored in the memory. The plurality of modules generate a plurality of result matrixes according to production data from the application system and the production line system based on the plurality of process parameters, respectively. Each result matrix comprises abnormal information or normal information between the plurality of process parameters and the plurality of receipts. A control module of the plurality of modules generates an intersection matrix according to the plurality of result matrices, and manipulates the production line system according to the intersection matrix. The production management system can monitor various process parameters, so that the production efficiency is improved.

Description

Technical Field

[0001] The present invention relates to a management system, and in particular to a production management system applied to a production line and an operation method thereof. Background Art

[0002] Enterprises can manage production lines through management systems. Generally speaking, management systems control production lines based on the various resources required by the production line, the currently executable resources, and the demand for orders. However, when problems occur in any production link of Work In Process (WIP), the current management system cannot monitor the influencing factors in the production process, so it cannot know and solve the aforementioned problems. As a result, the current management system causes insufficient and wasteful production capacity, which in turn reduces production efficiency. Summary of the invention

[0003] The present invention is directed to a production management system capable of monitoring various process parameters to thereby improve production efficiency.

[0004] According to an embodiment of the present invention, the production management system of the present invention includes a memory and a processor. The memory stores multiple modules. The processor couples the memory, the application system, and the production line system. The processor executes multiple modules. The multiple modules are respectively based on multiple process parameters to generate multiple result matrices according to the production data from the application system and the production line system. Each result matrix includes abnormal information or normal information between multiple process parameters and multiple documents respectively. The control module in the multiple modules generates a delivery matrix according to the multiple result matrices, and controls the production line system according to the delivery matrix.

[0005] According to an embodiment of the present invention, an operating method of a production management system of the present invention. The operating method comprises the following steps. A processor executes a plurality of modules in a memory so that the plurality of modules are respectively based on a plurality of process parameters to generate a plurality of result matrices according to production data from an application system and a production line system. Each of the plurality of result matrices comprises respectively abnormal information or normal information between a plurality of process parameters and a plurality of documents. A processor executes a control module in the plurality of modules so that the control module generates a delivery matrix according to the plurality of result matrices. A processor executes the control module so that the control module controls the production line system according to the delivery matrix.

[0006] Based on the above, the production management system and its operation method of the present invention establish multiple result matrices through multiple modules, and can obtain the documents with abnormalities and the corresponding process parameters based on the abnormal information indicated by these result matrices. In this way, the control module can establish a delivery matrix associated with multiple result matrices, and control the production line system based on the delivery matrix to eliminate the abnormalities occurring in a single process program, thereby improving production efficiency.

[0007] In order to make the above features and advantages of the present invention more clearly understood, embodiments are given below with reference to the accompanying drawings for detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 is a block diagram of a production management system according to an embodiment of the present invention;

[0009] Figure 2 is a flow chart of an operating method of a production management system according to an embodiment of the present invention;

[0010] Figure 3 is a block diagram of a production management system according to another embodiment of the present invention;

[0011] Figure 4 The present invention Figure 3 Operation diagram of the resource simulation module and the capacity simulation module in the embodiment;

[0012] FIG. 5A to FIG. 5D The present invention Figure 3 Operation diagram of the production management system of the embodiment;

[0013] FIG. 6A to FIG. 6B The present invention Figure 3 Operation diagram of the production management system of the embodiment;

[0014] Figure 7 The present invention Figure 3 Operation diagram of the production management system of the embodiment;

[0015] Figure 8 The present invention Figure 3 A schematic diagram of the operation of the production management system of the embodiment.

[0016] Description of Reference Numerals

[0017] 100, 300: production management system;

[0018] 110, 310: processor;

[0019] 120, 320: memory;

[0020] 121~12N: multiple modules;

[0021] 123: control module;

[0022] 210, 410, 411~41M: application system;

[0023] 220, 420: production line system;

[0024] 321: Resource simulation module;

[0025] 322: Capacity simulation module;

[0026] 323: control module;

[0027] 324: application system agent;

[0028] 421: Field resource agent;

[0029] 422a, 422Q, 822a-822c: OT control points;

[0030] 431~433, 43i~43j, 831~833, 83i~83j: equipment;

[0031] 611: Programming series;

[0032] 612-613, 731: blocks;

[0033] 613', 614: sequence;

[0034] 621~623: Process delivery results;

[0035] 711~713: module code;

[0036] 721-723: status information;

[0037] 732: Delivery status information;

[0038] 811: delivery result sequence;

[0039] AC1: First Cause Matrix;

[0040] AC2: Second cause matrix;

[0041] AOF: Agreement Matrix;

[0042] AR1: first result matrix;

[0043] AR1~ARN: result matrix;

[0044] AR2: second result matrix;

[0045] AR3: third result matrix;

[0046] BL1~BL2: first cause information;

[0047] CL1, CL2, CL4: first dimension;

[0048] DIN, DIN1, DIN2, DIN1': production data;

[0049] DS: production database;

[0050] RW1, RW2, RW4: second dimension;

[0051] RW11~RW31RW12~RW32: first result sequence;

[0052] RW12~RW32: second result sequence;

[0053] S1~SN: process parameters;

[0054] S210-S230: steps;

[0055] SC: control signal. DETAILED DESCRIPTION

[0056] Reference will now be made in detail to exemplary embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Whenever possible, the same reference numerals are used in the drawings and the description to refer to the same or like parts.

[0057] Figure 1 FIG. 1 is a block diagram of a production management system according to an embodiment of the present invention. Figure 1 The production management system 100 is applied to various manufacturing industries, and is particularly applied to semiconductor and high-tech industries. The production management system 100 can call the application system 210 and the production line system 220 through the application programming interface (API) to realize automated production. The production management system 100, the application system 210 and the production line system 220 can all be executed in electronic devices such as mobile phones, tablet computers, laptop computers, desktop computers and servers.

[0058] In this embodiment, the application system 210 may be, for example, an enterprise resource planning (ERP) system for executing various business services. The application system 210 is deployed in an information technology (IT) network. In this embodiment, the production line system 220 may be, for example, a management system for managing various equipment in a workshop. The production line system 220 is deployed in an operational technology (OT) network.

[0059] In this embodiment, the production management system 100 is deployed in an IT network. The production management system 100 includes a processor 110 and a memory 120. The memory 120 stores a plurality of modules 121-12N, where N is a positive integer. These modules 121-12N may be implemented, for example, by firmware or software, and have various functions. In this embodiment, the memory 120 may also store computing software and the like for implementing the algorithms, programs and data related to the functions of the present invention such as control and various calculations. The memory 120 may be, for example, a dynamic random access memory (DRAM), a flash memory, a non-volatile random access memory (NVRAM), or a combination of these memories.

[0060] In this embodiment, the processor 110 is coupled to the memory 120, the application system 210, and the production line system 220. The processor 110 accesses the memory 120 and can execute the data in the memory 120 and the multiple modules 121-12N. The processor 110 can also access the data in the application system 210 and the production line system 220 (for example, the production data DIN). In this embodiment, the processor 110 can be, for example, a signal converter, a field programmable gate array (FPGA), a central processing unit (CPU), or other programmable general-purpose or special-purpose microprocessor (Microprocessor), a digital signal processor (DSP), a programmable controller, an application specific integrated circuit (ASIC), a programmable logic device (PLD) or other similar devices or a combination of these devices, which can load and execute computer program related firmware or software to achieve control and various calculation functions.

[0061] Figure 2 FIG. 1 is a flowchart of an operating method of a production management system according to an embodiment of the present invention. Figure 1 as well as Figure 2 , the production management system 100 may execute steps S210 to S230. The order of these steps S210 to S230 is only an example and is not limited thereto.

[0062] In step S210 , the processor 110 executes the plurality of modules 121 ˜ 12N, so that the plurality of modules 121 ˜ 12N respectively generate a plurality of result matrices AR1 ˜ARN according to the production data DIN based on the plurality of process parameters.

[0063] In this embodiment, the production data DIN includes document data (eg, various orders) from the application system 210 and demand data such as materials and resources required for the document. The production data DIN also includes workshop data such as available materials and equipment resources from the production line system 220 .

[0064] In this embodiment, the plurality of process parameters respectively indicate a plurality of process procedures required to complete the target product or the re-product. For example, assuming that the target product is a wafer, the plurality of process parameters include a process procedure indicating a mask, a process procedure indicating a development, and a process procedure indicating an etching.

[0065] In this embodiment, each result matrix AR1-ARN includes status information between multiple process parameters and multiple documents, wherein the status information includes abnormal information or normal information. The document is used to indicate the product or re-product required in the order. Normal information indicates that no abnormality occurs in a certain document in the corresponding single process procedure. Abnormal information indicates that an abnormality occurs in a certain document in the corresponding single process procedure. The aforementioned abnormality may be, for example, insufficient materials, insufficient production capacity, or the current equipment is not completed.

[0066] That is, each module 121-12N generates respective result matrices AR1-ARN based on the same various process parameters according to the demand data and / or the workshop data (i.e., the production data DIN). Since different modules 121-12N can operate according to the production data DIN associated with the demand data and / or the workshop data, the multiple result matrices AR1-ARN can indicate whether the same document has abnormalities in different aspects (including demand planning and workshop resources).

[0067] For example, the first module 121 generates a result matrix AR1 based on a plurality of process parameters according to the production data DIN associated with the application system 210. Thus, in the case of considering demand planning, the result matrix AR1 indicates the status (i.e., abnormal or normal) of a plurality of documents in various process programs. For another example, the Nth module 12N generates another result matrix ARN based on the production data DIN associated with the production line system 220 based on a plurality of process parameters. Thus, in the case of considering workshop resources, the result matrix ARN indicates the status (i.e., abnormal or normal) of a plurality of documents in various process programs.

[0068] In step S220, the processor 110 executes the control module 123 in the plurality of modules 121-12N, so that the control module 123 generates the intersection matrix AOF according to the plurality of result matrices AR1-ARN. The control module 123 may be, for example, a module for implementing calculation and manipulation functions.

[0069] In this embodiment, the AOF matrix may be, for example, the superposition result of multiple result matrices AR1-ARN. The AOF matrix includes status information (i.e., abnormal information or normal information) between multiple process parameters and multiple documents. The AOF matrix indicates the status (i.e., abnormal or normal) of multiple documents in various process procedures considering multiple aspects (including demand planning and workshop resources).

[0070] In step S230, the processor 110 executes the control module 123 to control the production line system 220 according to the delivery matrix AOF. That is, the control module 123 adjusts the schedule of one or more devices in the production line system 220 based on the abnormal information indicated in the delivery matrix AOF.

[0071] It is worth mentioning that by establishing multiple result matrices AR1-ARN respectively through multiple modules 121-12N, the production management system 100 can monitor whether each document has an exception in each process program in multiple aspects (including demand planning and workshop resources). Through the control module 123, the delivery matrix AOF is further established based on these result matrices AR1-ARN. The production management system 100 can control the production line system 220 according to the delivery matrix AOF to eliminate the exceptions that occur in a single process program, thereby improving production efficiency.

[0072] Figure 3 FIG. 1 is a block diagram of a production management system according to another embodiment of the present invention. Figure 3 , the production management system 300 is coupled to the application system 410 and the production line system 420. The production management system 300 includes a processor 310 and a memory 320, wherein the memory 320 stores a plurality of modules 321-323. The processor 310, the memory 320, the plurality of modules 321-323, the application system 410 and the production line system 420 can refer to the relevant description of the production management system 100 and be deduced by analogy.

[0073] exist Figure 3 In the embodiment, the application system 410 may be, for example, a system composed of a plurality of application systems 411 - 41M, where M is a positive integer. Different application systems 411 - 41M may be applied to different products and share the same workshop (eg, production line system 420 ).

[0074] In this embodiment, the production line system 420 includes a field resource agent 421, a plurality of OT control points 422a-422Q, and a plurality of devices 431-433 and 43i-43j, where Q, i, and j are positive integers. The field resource agent 421 may be, for example, a switch deployed on an OT network to exchange information (e.g., production data DIN2) and / or signals (e.g., control signals SC) with a production management system 300 deployed on an IT network.

[0075] In this embodiment, multiple OT control points 422a~422Q are respectively applied to multiple production lines. These OT control points 422a~422Q can be implemented, for example, with firmware or software, and are used to realize the function of controlling multiple devices 431~433 and 43i~43j. For example, the OT control point 422a is used to control (for example, enable or disable) multiple devices 431~433. Another OT control point 422Q is used to control other multiple devices 43i~43j. The number of multiple OT control points 422a~422Q and multiple devices 431~433 and 43i~43j is only for example.

[0076] In this embodiment, the multiple modules 321-323 stored in the memory 320 include a resource simulation module 321, a capacity simulation module 322, and a control module 323. These modules 321-323 can be implemented in a programming language such as JSON (JavaScript Object Notation), Extensible Markup Language (XML), or YAML, but the present invention is not limited thereto.

[0077] In addition, the memory 320 also stores an application system agent 324. The application system agent 324 may be, for example, a switch deployed on an IT network. The application system agent 324 is used to access information (eg, production data DIN1) from the application system 410.

[0078] In this embodiment, the processor 310 executes multiple modules 321-323 and the application system agent 324 to realize automated production. The processor 310 also generates various data (including, for example, Figure 1 The result matrices AR1-ARN and the intersection matrix AOF are stored in the production database DS. In other embodiments, the production database DS is integrated with the memory 320.

[0079] In the process of automated production, the processor 310 executes the application system agent 324 so that the application system agent 324 accesses the production data DIN1 in the application system 410. The aforementioned production data DIN1 includes document data and demand data such as materials and resources required by the document. In addition, the application system agent 324 initializes the accessed production data DIN1 and loads the resource demand data such as the production plan and cycle planning indicated in the production data DIN1.

[0080] In this embodiment, the processor 310 executes the resource simulation module 321, so that the resource simulation module 321 plans the production resources according to the production data DIN1 to generate the production simulation results. That is, the resource simulation module 321 infers the resources and time required for multiple process programs according to the materials, equipment resources and supply and demand time required for each document in the production process. In this embodiment, the production simulation results indicate the material resources and equipment resources required for each document in multiple cycles in the corresponding production line. For example, the production simulation results include the possible delivery date of a certain order and the possible feeding time point of the required materials.

[0081] In this embodiment, the processor 310 executes the capacity simulation module 322, so that the capacity simulation module 322 performs capacity estimation according to the production data DIN1 and the production data DIN2 from the production line system 420 to generate a capacity simulation result. That is, the capacity simulation module 322 simulates the capacity status within a specific period according to the equipment and supply and demand time required for each document in the production process, and the multiple equipment 431-433 and 43i-43j set in the production line system 420. In this embodiment, the capacity simulation result indicates the predicted or simulated capacity of each document.

[0082] In this embodiment, the processor 310 executes the control module 323, so that the control module 323 calls the field resource agent 421 to access the production data DIN2 in the production line system 420. That is, based on the request of the control module 323, the field resource agent 421 accesses the current operation information (e.g., enabled, disabled, and in standby) of the plurality of devices 431-433 and 43i-43j, and feeds the aforementioned operation information back to the control module 323.

[0083] Next, the control module 323 performs capacity estimation based on the operation information and the production data DIN1 to generate the actual capacity result. That is, the control module 323 compares the materials, equipment resources and supply and demand time required for each document in the production process with the current operation status of various equipment 431-433 and 43i-43j to obtain the current capacity status. In this embodiment, the actual capacity result indicates the capacity that can be achieved by each document.

[0084] In addition, the processor 310 executes the control module 323, so that the control module 323 generates a control signal SC according to the actual production capacity result to control the production line system 420. The control module 323 outputs the control signal SC to the field resource agent 421, so as to transmit the control signal SC to the corresponding multiple devices 431-433 and 43i-43j through the field resource agent 421. In this way, the multiple devices 431-433 and 43i-43j are enabled, disabled or standby according to the control signal SC and have the latest schedule.

[0085] Figure 4 The present invention Figure 3 Operation diagram of resource simulation module and capacity simulation module in the embodiment. Figure 3 as well as Figure 4 The processor 310 executes the resource simulation module 321 and the capacity simulation module 322 to illustrate how the production management system 300 generates a plurality of result matrices AR1 and AR2 in the process of monitoring each process program.

[0086] exist Figure 4 In the embodiment, the resource simulation module 321 plans production resources based on the production data DIN1 from the application system 410 to generate the first result matrix AR1 based on the multiple process parameters S1-SN. In the present embodiment, the multiple process programs include multiple programs shown as "job 1" to "job N", and are set as multiple process parameters S1-SN, where N is a positive integer.

[0087] Specifically, the resource simulation module 321 infers the resources and time required for each process program according to the materials, equipment resources and supply and demand time (e.g., "raw materials, equipment resources" and other production data DIN1') required for each document (e.g., "order") during the production process (e.g., "journey"). Based on multiple process parameters S1~SN, the resource simulation module 321 represents the inference results corresponding to each document with status information (including abnormal information and / or normal information), and generates a first result matrix AR1 accordingly. In addition, the resource simulation module 321 stores the first result matrix AR1 in the production database DS.

[0088] In this embodiment, the capacity simulation module 322 plans the capacity based on the multiple process parameters S1-SN to generate the second result matrix AR2 according to the production data DIN1 from the application system 410 and the production data DIN2 from the production line system 420. In this embodiment, the multiple process procedures are the same as the multiple process procedures in the first result matrix AR1 and have the same multiple process parameters S1-SN.

[0089] Specifically, the capacity simulation module 322 simulates the capacity conditions of multiple process programs according to the equipment and supply and demand time (e.g., production data DIN1') required in the production process for each document (e.g., the "order" included in the production data DIN1), and the multiple devices 431-433 and 43i-43j set in the production line system 420. Based on multiple process parameters S1-SN, the capacity simulation module 322 represents the simulated capacity conditions corresponding to each document with status information (including abnormal information and / or normal information), and generates a second result matrix AR2 accordingly. In addition, the capacity simulation module 322 stores the second result matrix AR2 in the production database DS.

[0090] FIG. 5A to FIG. 5D The present invention Figure 3 Operation diagram of the production management system of the embodiment. Figure 3 as well as FIG. 5A to FIG. 5B , the processor 310 executes the resource simulation module 321 and the capacity simulation module 322 to generate a plurality of result matrices AR1-AR2, for example Figure 4 The implementation details of the first result matrix AR1 and the second result matrix AR2 in FIG. FIG. 5C to FIG. 5D , the processor 310 executes the resource simulation module 321 and the capacity simulation module 322 to generate a plurality of cause matrices AC1 ˜ AC2 based on the first result matrix AR1 and the second result matrix AR2 .

[0091] like Figure 5A As shown, the resource simulation module 321 represents multiple documents with a first dimension CL1, and multiple process parameters (ie, Figure 4 The plurality of process parameters S1-SN) shown are represented by the second dimension RW1. Thus, the first result matrix AR1 generated by the resource simulation module 321 may be, for example, a two-dimensional matrix to indicate the status information (including abnormal information and / or normal information) of the plurality of documents in various process procedures in terms of resource planning.

[0092] In detail, the first result matrix AR1 includes a plurality of first result sequences RW11-RW31 between a plurality of process parameters and each document. Each first result sequence RW11-RW31 includes abnormal information or normal information corresponding to a plurality of process parameters. Both the abnormal information and the normal information are represented by a single bit.

[0093] In this embodiment, the abnormal information is represented by, for example, a first logic code (e.g., 1) to indicate that an abnormality occurs in a single process sequence of a single document. The normal information is represented by, for example, a second logic code (e.g., 0) to indicate that an abnormality does not occur in a single process sequence of a single document. In other words, each first result sequence RW11-RW31 is represented by, for example, a byte to indicate the status (including abnormality and / or normality) of a single document in multiple process sequences.

[0094] For example, in the first result matrix AR1, the first result sequence RW11 indicates that the first document (i.e., "Document 1") has no abnormality (i.e., "000") in all process procedures. For another example, another first result sequence RW21 indicates that the second document (i.e., "Document 2") has no abnormality (i.e., "0") in the first process procedure, has an abnormality (i.e., "1") in the second process procedure, and has an abnormality (i.e., "1") in the third process procedure.

[0095] like Figure 5A as well as Figure 5C As shown, in the first result matrix AR1, when the number of the first logic code (i.e., "1") of any of the plurality of first result sequences RW11-RW31 is greater than a threshold value (e.g., 0), it indicates that an exception occurs in at least one process procedure of the corresponding document. At this time, the resource simulation module 321 establishes a first cause matrix AC1 based on the aforementioned first result sequences RW11-RW31 based on a plurality of cause parameters. The plurality of cause parameters may be, for example, preset possible abnormal causes, and are respectively stored in different blocks of the memory 320.

[0096] Continuing with the above description, the resource simulation module 321 represents the abnormal document (e.g., the second document) and the corresponding multiple process parameters with the first dimension CL2, and represents the multiple cause parameters with the second dimension RW2. In this way, the first cause matrix AC1 generated by the resource simulation module 321 can be, for example, a two-dimensional matrix to indicate the abnormal causes of the abnormal document in various process procedures (i.e., the first cause information) in consideration of resource planning.

[0097] In detail, the first cause matrix AC1 includes first cause information between a plurality of cause parameters and corresponding documents and a plurality of process parameters. The first cause information represented by a first code (e.g., "N") indicates that the cause of the abnormality of the document in a single process procedure is an empty set, that is, no abnormality occurs. The first cause information represented by a second code (e.g., "P") indicates that the cause of the abnormality of the document in a single process procedure is a single indicator and points to the corresponding cause block in the memory 320.

[0098] For example, in the first result matrix AR1, since the number (i.e., 2) of the first logic code (i.e., "1") of the first result sequence RW21 is greater than the threshold, the resource simulation module 321 establishes the first cause matrix AC1. The resource simulation module 321 analyzes the second document (i.e., "Document 2") corresponding to the first result sequence RW21 and finds that it does not meet the expected results or goals in the second process procedure (i.e., "Process 2") during the process of planning production resources. In this way, the resource simulation module 321 records the various reasons for the aforementioned non-compliance in at least one block in the memory 320, and generates at least one indicator for pointing to this block(s). The aforementioned indicator may be, for example, the first cause information BL1~BL2 represented by the second code "P".

[0099] like Figure 5B As shown, the capacity simulation module 322 represents multiple documents with a first dimension CL1, and multiple process parameters (ie, Figure 4 The plurality of process parameters S1-SN) shown are represented by the second dimension RW1. Thus, the second result matrix AR2 generated by the capacity simulation module 322 may be, for example, a two-dimensional matrix to indicate the status information (including abnormal information and / or normal information) of the plurality of documents in various process procedures in terms of the capacity simulation.

[0100] In detail, the second result matrix AR2 includes a plurality of second result sequences RW12-RW32 between the plurality of process parameters and each of the plurality of documents. Each second result sequence RW12-RW32 includes abnormal information (i.e., "1") or normal information (i.e., "0") corresponding to the plurality of process parameters. The second result matrix AR2 can refer to Figure 5A The relevant explanations of the first result matrix AR1 can be deduced by analogy.

[0101] like Figure 5B as well as Figure 5D As shown, in the second result matrix AR2, when the number of the first logic code (i.e., "1") of any of the plurality of second result sequences RW12-RW32 is greater than a threshold value (e.g., 0), it indicates that an abnormality occurs in at least one process procedure of the corresponding document. At this time, the capacity simulation module 322 establishes a second cause matrix AC2 according to the aforementioned second result sequences RW12-RW32 based on a plurality of cause parameters.

[0102] Continuing with the above description, the capacity simulation module 322 represents the abnormal document (e.g., the second document) and the corresponding multiple process parameters with the first dimension CL2, and represents the multiple cause parameters with the second dimension RW2. In this way, the second cause matrix AC2 generated by the capacity simulation module 322 can be, for example, a two-dimensional matrix to indicate the abnormal causes of the abnormal document in various process procedures (i.e., the second cause information) in consideration of the capacity simulation.

[0103] Specifically, the second cause matrix AC2 includes second cause information between a plurality of cause parameters and corresponding documents and a plurality of process parameters. The second cause information includes an empty set represented by a first code (e.g., "N") and an indicator represented by a second code (e.g., "P"). The second cause matrix AC2 can refer to Figure 5C The first cause matrix AC1 is explained and deduced accordingly.

[0104] FIG. 6A to FIG. 6B The present invention Figure 3 Operation diagram of the production management system of the embodiment. Figure 3 as well as FIG. 6A to FIG. 6B , the processor 310 executes the control module 323 to further analyze the abnormal status of the document in the single process procedure.

[0105] exist Fig. 6A In one embodiment, the control module 323 sets a plurality of process codes corresponding to a plurality of process parameters to establish a process sequence 611. These process codes are used to indicate different process procedures, that is, to indicate Figure 4 For example, in the process list 611, a plurality of process codes (ie, "421") respectively indicate a first process (ie, "process 1"), a second process (ie, "process 2"), and a third process (ie, "process 3").

[0106] In this embodiment, based on a plurality of process codes, the control module 323 calculates the sequence length of each first result sequence RW11 ˜ RW31 in the first result matrix AR1 , as shown in block 612 .

[0107] Specifically, in the first result matrix AR1, the control module 323 uses multiple process codes (i.e., "421") as weight values. Based on the weight values, the control module 323 calculates the weighted sum of the state information (i.e., "000") corresponding to all process programs (i.e., "Process 1" to "Process 3") in the first result sequence RW11 to generate a sequence length (i.e., "f(Document 1) = 0").

[0108] Specifically, based on the plurality of process codes (i.e., "421"), the control module 323 multiplies the state information (i.e., 0) corresponding to the first process procedure (i.e., "process 1") by the corresponding process code (i.e., "4"), multiplies the state information (i.e., 0) corresponding to the second process procedure (i.e., "process 2") by the corresponding process code (i.e., "2"), and multiplies the state information (i.e., 0) corresponding to the third process procedure (i.e., "process 3") by the corresponding process code (i.e., "1") to generate a plurality of multiplication results. The control module 323 adds the aforementioned plurality of multiplication results to obtain the sequence length of the first result sequence RW11.

[0109] Similarly, based on the weight value, the control module 323 calculates the weighted sum of the status information (i.e., "011") corresponding to all process procedures (i.e., "Process 1" to "Process 3") in the second result sequence RW21 to generate a sequence length (i.e., "f(Document 2) = 3"). In addition, based on the weight value, the control module 323 also calculates the weighted sum of the status information (i.e., "101") corresponding to all process procedures in the third result sequence RW31 to generate a sequence length (i.e., "f(Document 3) = 5").

[0110] In this embodiment, based on the plurality of process codes (ie, "421"), the control module 323 further calculates Figure 5B The sequence length of each result sequence RW12-RW32 in the second result matrix AR2 is shown. The aforementioned sequence length can refer to Fig. 6A The same applies to the relevant description of the first result matrix AR1 in .

[0111] In addition, the control module 323 calculates the completion check code of the ideal order after each process is completed, as shown in block 613. Specifically, the control module 323 adds up the multiple process codes (ie, "421") in the process sequence 611 to obtain the completion check code (ie, "7").

[0112] exist Figure 6B In the embodiment, the control module 323 performs a logical AND operation according to the process sequence 611 and any one of the first result sequences RW11-RW31 in the first result matrix AR1 to generate a corresponding process handover result. The process handover result indicates whether an exception occurs in one or more process sequences of a single document.

[0113] For example, the control module 323 performs a logical AND operation on the sequence 613' (i.e., "111") corresponding to the completion check code (i.e., "7") and the first result sequence RW11 to generate a process handover result 621 (i.e., "0"). The sequence 613' indicates all completed process procedures and has multiple default logic values ​​(i.e., "111") corresponding to multiple process parameters. The process handover result 621 indicates that the first document (i.e., "Document 1") corresponding to this sequence RW11 has no abnormalities in all process procedures (i.e., "Process 1" to "Process 3").

[0114] For another example, the control module 323 performs a logical AND operation on the sequence 613' corresponding to the completion check code (i.e., "7") and another first result sequence RW21 to generate a process handover result 622 (i.e., "3"). The process handover result 622 indicates that the second document (i.e., "Document 2") corresponding to this sequence RW21 has an exception in the second process procedure (i.e., "Process 2") and the third process procedure (i.e., "Process 3").

[0115] For another example, the control module 323 performs a logical AND operation on the sequence 614 (i.e., "100") corresponding to the first process program (i.e., "Process 1") and the first result sequence RW21 to generate a process handover result 623 (i.e., "0"). The process handover result 623 indicates that the second document (i.e., "Document 2") corresponding to the sequence RW21 has no abnormality in the first process program (i.e., "Process 1").

[0116] It should be noted that by performing a logical AND operation on multiple process programs (e.g., completion check code (i.e., "7")) and any first result sequence RW11-RW13, or by performing a logical AND operation on a single process program (e.g., "process 1") and any first result sequence RW11-RW13, the control module 323 can analyze in which process of a single document an abnormality occurs. In this way, the control module 323 can analyze based on the following example: FIG. 5C to FIG. 5D The various cause matrices AC1 to AC2 shown indicate the cause of the abnormality.

[0117] In this embodiment, the control module 323 also performs the following steps according to the programming sequence 611 and the Figure 5B A logical AND operation is performed on any of the plurality of second result sequences RW12-RW32 in the second result matrix AR2 to generate a corresponding process hand-in result. The aforementioned process hand-in result can refer to the above Figure 6B The relevant descriptions of the various process delivery results 621~623 are given and analogies are made.

[0118] Figure 7 The present invention Figure 3Operation diagram of the production management system of the embodiment. Figure 3 as well as Figure 7 The processor 310 executes the resource simulation module 321, the capacity simulation module 322 and the control module 323 to generate a plurality of result matrices AR1-AR3. The processor 310 also executes the control module 323 to generate an intersection matrix AOF according to the result matrices AR1-AR3.

[0119] exist Figure 7 In the embodiment, based on a plurality of process parameters, the resource simulation module 321 and the capacity simulation module 322 generate a first result matrix AR1 and a second result matrix AR2, respectively. Figure 4 as well as FIG. 5A to FIG. 5B In addition, the control module 323 is based on multiple process parameters (such as Figure 4 The plurality of process parameters S1-SN) shown are used to analyze the current production capacity of the production line system 420 according to the production data DIN2 from the production line system 420 to generate a third result matrix AR3.

[0120] Specifically, the control module 323 analyzes the current capacity status of the equipment and supply and demand time (for example, the number of work-in-progress that can be achieved by the multiple equipment 431-433 and 43i-43j) that can be used in the production process of the current production line system 420 according to each document (for example, the "order" included in the production data DIN1). Based on multiple process parameters, the control module 323 represents the current capacity status corresponding to each document with status information (including abnormal information and / or normal information), and generates a third result matrix AR3 accordingly. In addition, the control module 323 can also store the third result matrix AR3 in the production database DS.

[0121] like Figure 7 As shown, the control module 323 represents multiple documents with a first dimension CL1, and multiple process parameters (ie, Figure 4 The plurality of process parameters S1-SN) shown are represented by the second dimension RW1. Thus, the third result matrix AR3 generated by the control module 323 may be, for example, a two-dimensional matrix to indicate the status information (including abnormal information and / or normal information) of the plurality of documents in various process procedures in consideration of the current production capacity.

[0122] Specifically, the third result matrix AR3 includes a plurality of third result sequences RW13 to RW33 between a plurality of process parameters and each document. Each third result sequence RW13 to RW33 includes abnormal information (i.e., "1") or normal information (i.e., "0") corresponding to a plurality of process parameters. The third result matrix AR3 can refer to Figure 5AThe relevant explanations of the first result matrix AR1 can be deduced by analogy.

[0123] In this embodiment, in the third result matrix AR3, the control module 323 further determines whether the number of the first logic code (i.e., "1") of any one of the plurality of third result sequences RW13-RW33 is greater than a threshold value (e.g., 0), so as to establish a third cause matrix (not shown) according to the aforementioned third result sequences RW13-RW33 based on a plurality of cause parameters. The third cause matrix can refer to Figure 5C The first cause matrix AC1 is explained and deduced accordingly.

[0124] In this embodiment, the control module 323 sets a plurality of module codes 711-713 of the resource simulation module 321, the capacity simulation module 322, and the control module 323. These module codes 711-713 are used to indicate different functional modules 321-323. For example, the module code 711 of the resource simulation module 321 is "1", the module code 712 of the capacity simulation module 322 is "2", and the module code 712 of the control module 323 is "4".

[0125] It should be noted that since the multiple result matrices AR1-AR3 are represented by the same multiple process parameters and the same multiple documents, the control module 323 can perform calculations on these result matrices AR1-AR3. In this way, the control module 323 superimposes the first result matrix AR1, the second result matrix AR2 and the third result matrix AR3 based on the multiple module codes 711-713 to generate the intersection matrix AOF.

[0126] Specifically, the control module 323 uses the plurality of module codes 711-713 (ie, "124") as weight values. Based on the weight values, the control module 323 calculates the weighted sum of the state information (including "0" and "1") in the plurality of result matrices AR1-AR3 to generate the intersection matrix AOF.

[0127] like Figure 7 As shown, the control module 323 uses the first dimension CL1 of the multiple result matrices AR1-AR3 as the first dimension CL4 of the handover matrix AOF, and uses the second dimension RW1 of the multiple result matrices AR1-AR3 as the second dimension RW4 of the handover matrix AOF. In this way, the handover matrix AOF generated by the control module 323 can be, for example, a two-dimensional matrix to indicate the status information (including abnormal information and / or normal information) of multiple documents in various process procedures in multiple directions considering resource planning, capacity simulation and current resources.

[0128] In detail, the delivery matrix AOF includes delivery information between multiple process parameters and multiple documents. The delivery information is represented by a single bit. The delivery information includes multiple delivery values ​​corresponding to the multiple process parameters. The delivery value represented by 0 indicates that no abnormality occurs in a single document in a single process procedure. The delivery value represented by other values ​​indicates that an abnormality occurs in a single document in a single process procedure.

[0129] For example, as shown in block 731, the control module 323 captures status information 721 (i.e., 1) corresponding to the third process procedure (i.e., “Process 3”) in the first result matrix AR1, status information 722 (i.e., 1) corresponding to the third process procedure (i.e., “Process 3”) in the second result matrix AR2, and status information 723 (i.e., 1) corresponding to the third process procedure (i.e., “Process 3”) in the third result matrix AR3.

[0130] In this embodiment, based on the first cause matrix corresponding to the first result matrix AR1, the abnormal cause of the state information 721 (i.e., 1) may be, for example, insufficient raw materials in resource planning. Based on the second cause matrix corresponding to the second result matrix AR2, the abnormal cause of the state information 722 (i.e., 1) may be, for example, that no resources are available for simulation or prediction. Based on the third cause matrix corresponding to the third result matrix AR3, the abnormal cause of the state information 723 (i.e., 1) may be, for example, that the current process of the production line system 420 has not been completed.

[0131] Next, based on the multiple module codes 711-713 (i.e., "124"), the control module 323 multiplies the captured status information 721-723 (i.e., "111") by the corresponding module codes 711-713 (i.e., "124") to generate multiple multiplication results. The control module 323 adds the aforementioned multiple multiplication results to obtain the delivery status information 732 (i.e., "7") of the single document (i.e., "Document 3") in the third process procedure (i.e., "Process 3").

[0132] It should be noted that the above-mentioned result matrices AR1-AR3 and the handover matrix AOF all have the same multiple tags, that is, the same multiple production process parameters and the same multiple documents. In this way, the processor 310 can improve the efficiency of calculating these matrices AR1-AR3 and AOF, and can quickly present them to the user in a two-dimensional view. In addition, since the above-mentioned calculations are all performed in the memory 320, the processor 310 does not need to call other systems additionally, thereby improving the calculation efficiency.

[0133] Figure 8 The present invention Figure 3 Operation diagram of the production management system of the embodiment. Figure 3 as well as Figure 8,by Figure 7 The AOF shown in the embodiment is used as an example to explain that the processor 310 executes the control module 323 to control the production line system 420 according to the AOF.

[0134] exist Figure 8 In the embodiment, the control module 323 establishes a delivery result sequence 811 according to a plurality of process codes (i.e., process sequence 611) of a plurality of process parameters and the largest of the delivery values ​​(e.g., "7"). The largest of the delivery values ​​is, for example, represented by the delivery status information 732 (i.e., 7), indicating that an abnormality occurred in the third process procedure (i.e., "process 3") of the third document (i.e., "document 3").

[0135] In addition, the control module 323 performs a logical AND operation based on the multiple process codes (i.e., "421" shown in the process sequence 611) according to the delivery result sequence 811 and each of the multiple third result sequences in the third result matrix AR3 to obtain abnormality cause information. The abnormality cause information indicates that the multiple documents have abnormalities in one or more process procedures based on resource planning and capacity simulation applied in the current production line system 420.

[0136] Specifically, the control module 323 decomposes the handover status information 732 (ie, “7”) in the handover matrix AOF into a handover result sequence 811 (ie, “111”) as shown in block 731 based on multiple process codes (ie, “421”).

[0137] Taking the third result sequence RW33 in the third result matrix AR3 as an example, the control module 323 performs a logical AND operation on the delivery result sequence 811 (i.e., "111") and the third result sequence RW33 (i.e., "011") to generate abnormal reason information (i.e., "011"). This abnormal reason information indicates that the third document (i.e., "Document 3") has an abnormality in the second process procedure (i.e., "Process 2") and the third process procedure (i.e., "Process 3").

[0138] Next, the control module 323 accesses the third cause matrix corresponding to the third result matrix AR3 to learn the reasons why the third document (i.e., “Document 3”) has abnormalities in these process programs. Thus, the control module 323 generates a control signal SC according to the abnormality cause information, and transmits the control signal SC to at least one OT control point 822b-822c related to these process programs through the field resource agent 421 to control the production line system 420.

[0139] For example, the abnormality reason information indicates that the abnormality of the third document (i.e., "Document 3") in the third process procedure (i.e., "Process 3") is due to the influence of the previous second process procedure (i.e., "Process 2"). The abnormality reason information also indicates that the abnormality of the third document in the second process procedure is due to the process delay and is not completed. In this way, the control module 323 generates a control signal SC to indicate to increase the dispatch sequence of multiple devices 831-833 related to the second process procedure, so that the third document can be completed faster.

[0140] In summary, the operating method of the production management system of the present invention can integrate production planning, forecasting and on-site (i.e., workshop) information through multiple result matrices established by multiple modules and a delivery matrix based on the superposition of the aforementioned multiple result matrices, so as to monitor the status of each document in various manufacturing procedures. By calculating the aforementioned multiple matrices in the memory, the production management system can provide the monitoring information to the user in a simple and fast manner, thereby eliminating abnormalities and improving the efficiency of controlling production capacity. In some embodiments, by performing logical AND operations on multiple result matrices, the production management system can analyze whether a single document has an abnormality in a single manufacturing procedure, thereby analyzing the cause of the abnormality. In some embodiments, through the status of multiple result matrices represented by a single bit, different modules can quickly exchange information to improve the efficiency of information transmission.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or perform equivalent replacements on some or all of the technical features therein. However, these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A production management system, characterized in that: include: Memory, which stores multiple modules; as well as A processor is coupled to the memory, the application system and the production line system to execute the multiple modules. The plurality of modules are respectively based on a plurality of process parameters to generate a plurality of result matrices according to the production data from the application system and the production line system, wherein each of the plurality of result matrices includes abnormal information or normal information respectively between the plurality of process parameters and a plurality of documents, The control module among the multiple modules generates a delivery matrix according to the multiple result matrices, and controls the production line system according to the delivery matrix.

2. The production management system according to claim 1, characterized in that: The multiple modules also include a resource simulation module and a capacity simulation module. The resource simulation module plans production resources based on the multiple process parameters according to the production data from the application system to generate a first result matrix, wherein the first result matrix includes multiple first result sequences between the multiple process parameters and each of the multiple documents, and each of the multiple first result sequences includes the abnormal information or the normal information corresponding to the multiple process parameters. The capacity simulation module plans the capacity based on the multiple process parameters according to the production data from the application system and the production line system to generate a second result matrix, wherein the second result matrix includes multiple second result sequences between the multiple process parameters and each of the multiple documents, and each of the multiple second result sequences includes the abnormal information or the normal information corresponding to the multiple process parameters. The abnormal information is represented by a first logic code, and the normal information is represented by a second logic code.

3. The production management system according to claim 2, characterized in that: The control module sets a plurality of process codes corresponding to the plurality of process parameters to establish a process sequence. The control module performs a logic AND operation according to the process sequence and any one of the plurality of first result sequences or the plurality of second result sequences to generate a process delivery result.

4. The production management system according to claim 2, characterized in that: When the number of the first logic codes of any one of the plurality of first result sequences is greater than a threshold, the resource simulation module establishes a first cause matrix according to any one of the plurality of first result sequences based on a plurality of cause parameters, wherein the first cause matrix includes first cause information between the plurality of cause parameters and the corresponding documents and the plurality of process parameters, respectively. When the number of the first logic codes of any one of the multiple second result sequences is greater than the threshold, the capacity simulation module establishes a second cause matrix based on a plurality of cause parameters according to any one of the multiple second result sequences, wherein the second cause matrix includes second cause information between the multiple cause parameters and the corresponding documents and the multiple process parameters.

5. The production management system according to claim 2, characterized in that: The control module analyzes the current production capacity of the production line system according to the production data from the production line system based on the multiple process parameters to generate a third result matrix, wherein the third result matrix includes multiple third result sequences between the multiple process parameters and each of the multiple documents, and each of the multiple third result sequences includes the abnormal information or the normal information corresponding to the multiple process parameters.

6. The production management system according to claim 5, characterized in that: The control module superimposes the first result matrix, the second result matrix and the third result matrix to generate the delivery matrix based on the resource simulation module, the capacity simulation module and a plurality of module codes of the control module. The delivery matrix includes a plurality of delivery values ​​between the plurality of process parameters and the plurality of documents.

7. The production management system according to claim 6, characterized in that: The control module establishes a delivery result sequence according to a plurality of process codes of the plurality of process parameters and the maximum of the delivery values, performs a logical AND operation based on the plurality of process codes according to the delivery result sequence and each of the plurality of third result sequences to obtain abnormal cause information, and controls the production line system according to the abnormal cause information.

8. A method for operating a production management system, characterized in that: include: Executing a plurality of modules in the memory through a processor, so that the plurality of modules are respectively based on a plurality of process parameters to generate a plurality of result matrices according to production data from an application system and a production line system, wherein each of the plurality of result matrices includes abnormal information or normal information respectively between the plurality of process parameters and a plurality of documents; Executing a control module among the multiple modules by a processor so that the control module generates a handoff matrix according to the multiple result matrices; as well as The control module is executed by a processor so that the control module controls the production line system according to the delivery matrix.

9. The operating method according to claim 8, characterized in that: Also includes: Executing a resource simulation module among the multiple modules by a processor, so that the resource simulation module plans production resources according to the production data from the application system based on the multiple process parameters to generate a first result matrix, wherein the first result matrix includes multiple first result sequences between the multiple process parameters and each of the multiple documents, and each of the multiple first result sequences includes the abnormal information or the normal information corresponding to the multiple process parameters; as well as The processor executes a capacity simulation module among the multiple modules, so that the capacity simulation module plans the capacity based on the multiple process parameters according to the production data from the application system and the production line system to generate a second result matrix, wherein the second result matrix includes multiple second result sequences between the multiple process parameters and each of the multiple documents, and each of the multiple second result sequences includes the abnormal information or the normal information corresponding to the multiple process parameters. The abnormal information is represented by a first logic code, and the normal information is represented by a second logic code.

10. The operating method according to claim 9, characterized in that: Also includes: Executing the control module by a processor so that the control module sets a plurality of process codes corresponding to the plurality of process parameters to establish a process sequence; as well as The control module is executed by a processor so that the control module performs a logic AND operation according to the process sequence and any one of the plurality of first result sequences or the plurality of second result sequences to generate a process handoff result.

11. The operating method according to claim 9, characterized in that: Also includes: When the number of the first logic codes of any one of the plurality of first result sequences is greater than a threshold, the processor executes the resource simulation module so that the resource simulation module establishes a first cause matrix according to any one of the plurality of first result sequences based on a plurality of cause parameters, wherein the first cause matrix includes first cause information between the plurality of cause parameters and the corresponding documents and the plurality of process parameters; as well as When the number of the first logic codes of any one of the multiple second result sequences is greater than the threshold, the capacity simulation module is executed by the processor to enable the capacity simulation module to establish a second cause matrix based on a plurality of cause parameters according to any one of the multiple second result sequences, wherein the second cause matrix includes second cause information between the multiple cause parameters and the corresponding documents and the multiple process parameters.

12. The operating method according to claim 8, characterized in that: Also includes: The control module is executed by a processor so that the control module analyzes the current production capacity of the production line system according to the production data from the production line system based on the multiple process parameters to generate a third result matrix, wherein the third result matrix includes multiple third result sequences between the multiple process parameters and each of the multiple documents, and each of the multiple third result sequences includes the abnormal information or the normal information corresponding to the multiple process parameters.

13. The operating method according to claim 12, characterized in that: Also includes: The control module is executed by a processor so that the control module superimposes the first result matrix, the second result matrix and the third result matrix to generate the handover matrix based on the resource simulation module, the capacity simulation module and a plurality of module codes of the control module. The delivery matrix includes a plurality of delivery values ​​between the plurality of process parameters and the plurality of documents.

14. The operating method according to claim 13, characterized in that: Also includes: Executing the control module by a processor so that the control module establishes a delivery result sequence according to a plurality of process codes of the plurality of process parameters and a maximum of the delivery values; Executing the control module by a processor so that the control module performs a logic AND operation based on the plurality of process codes according to the delivery result sequence and each of the plurality of third result sequences to obtain abnormality cause information; as well as The control module is executed by a processor so that the control module controls the production line system according to the abnormal cause information.

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