Intelligent production scheduling management system and method
Through the intelligent production scheduling management system, parallel process groups and serial process groups are divided, and combined with real-time monitoring and scheduling models, the problems of unreasonable scheduling and waste of resources in traditional production scheduling systems are solved, and efficient and accurate production scheduling plans are achieved.
Patent Information
- Application Number
- CN202510498545.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-21
- Publication Date
- 2025-08-05
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
Traditional production scheduling systems rely on manual scheduling, resulting in unreasonable scheduling, waste of resources, unbalanced equipment load, lack of real-time monitoring and automatic scheduling, which is prone to production scheduling conflicts and human errors, making it difficult to ensure production efficiency and accuracy.
The intelligent production scheduling management system is adopted, and order data and workpiece demand information are obtained through the information acquisition unit, parallel process groups and serial process groups are divided, and real-time monitoring and dynamic adjustments are carried out in combination with the status monitoring and scheduling units, and parallel production scheduling models are built to optimize equipment utilization and production scheduling plans.
Reasonable production scheduling arrangements have been achieved, production efficiency has been improved, equipment resources have been avoided, equipment has been resourced, equipment has been operated efficiently, human errors have been reduced, production scheduling has been improved, and production scheduling has been adapted to production emergencies.
Smart Images
Figure CN120430552A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of production management, and in particular to an intelligent production scheduling management system and method. Background Art
[0002] Traditional systems usually rely on manual production planning and scheduling, which is often affected by human factors and can easily lead to unreasonable scheduling, production scheduling conflicts, idle equipment or long waiting times; and traditional systems usually do not have the ability to make real-time judgments and scheduling, and can easily ignore the collaboration between parallel processes and the reasonable arrangement of serial processes, resulting in waiting and repeated scheduling between processes, thereby reducing production efficiency; and traditional systems usually lack the ability to dynamically adjust, which can easily lead to some equipment being idle for a long time while other equipment is overloaded, resulting in waste of resources. Due to the lack of real-time monitoring and automatic scheduling functions, the matching of equipment availability and production tasks is often not optimized; and traditional systems often rely on manual judgment and arrangement, which can be easily affected by the experience and preferences of operators, resulting in inaccurate or unreasonable production plans. The manual scheduling process may also lead to human errors, making it difficult to ensure the optimal arrangement of each link. Summary of the Invention
[0003] The technical problem to be solved by the present invention is to overcome the shortcomings of the above-mentioned prior art and provide an intelligent production scheduling management system and method.
[0004] The technical solution adopted to solve the above technical problems is: an intelligent production scheduling management system, including:
[0005] An information acquisition unit, configured to acquire order data, acquire demand information of all workpieces of the product to be scheduled based on the order data, and acquire production process information of the product to be scheduled based on the demand information of all workpieces;
[0006] a process division unit, the process division unit being configured to determine a constraint matrix based on the production process information of the product to be scheduled, and to divide the production process information of the product to be scheduled into a parallel process group, a serial process group, and an assembly process based on the constraint matrix;
[0007] A status monitoring unit, configured to monitor the production status of all production equipment in real time to obtain an equipment status table, and determine whether the production equipment can execute the serial process group based on the equipment status table;
[0008] The first scheduling unit is used to schedule the serial process group in sequence according to the production equipment if the production equipment can execute the serial process group, so as to obtain first scheduling information, and to build a parallel production scheduling model according to the equipment status table and the parallel process group, and to solve the production scheduling model to obtain second scheduling information.
[0009] Preferably, the system further comprises:
[0010] a second scheduling unit, configured to, if the production equipment cannot execute the serial process group, construct a parallel production scheduling model based on the equipment status table and the parallel process group, solve the production scheduling model to obtain second production scheduling information, and continuously monitor the production status of all production equipment in real time until the production equipment can execute the serial process group to obtain first production scheduling information;
[0011] A production scheduling integration unit is used to obtain production scheduling information of the product to be scheduled based on the first production scheduling information, the second production scheduling information and the third production scheduling information corresponding to the assembly process.
[0012] Preferably, obtaining demand information of all workpieces of the product to be scheduled according to the order data, and obtaining production process information of the product to be scheduled according to the demand information of all workpieces includes:
[0013] Obtain the name of the product to be scheduled according to the order data;
[0014] Matching the product name to be scheduled with a preset product library to obtain a workpiece demand table corresponding to the product name to be scheduled;
[0015] Determine the workpiece names and required quantities of all workpieces of the product to be scheduled according to the workpiece requirement table;
[0016] The workpiece name is matched with the preset workpiece library to obtain the workpiece production process table corresponding to the workpiece, and the above operation is repeated until all workpieces in the workpiece demand table are processed to obtain the production process information of the product to be scheduled.
[0017] Preferably, determining the constraint matrix according to the production process information of the product to be scheduled includes:
[0018] Determining a first production process without sequence requirements for the product to be scheduled according to the production process information of the product to be scheduled;
[0019] Determining a second production process with a priority requirement for the product to be scheduled according to the production process information of the product to be scheduled;
[0020] Determining a third production process with restrictive requirements for the product to be scheduled according to the production process information of the product to be scheduled;
[0021] A constraint matrix is determined according to the first production process, the second production process, and the third production process, wherein the constraint matrix is expressed as follows:
[0022]
[0023] in, Indicates the zth row and the Elements of a column.
[0024] Preferably, the production process information of the product to be scheduled is divided into a parallel process group, a serial process group and an assembly process according to the constraint matrix, including:
[0025] Determine the first production process group, the second production process group, and the third production process group of the product to be scheduled according to each element in the constraint matrix;
[0026] Using the first production process group as the serial process group;
[0027] The second production process group and the third production process group are used as parallel process groups;
[0028] An assembly process is obtained based on the workpieces completed by the serial process group and the parallel process group.
[0029] Preferably, judging whether the production equipment can execute the serial process group according to the equipment status table includes:
[0030] Determining the total equipment state required by the serial process group;
[0031] matching the overall device status with the device status table to determine whether the device status table matches the overall device status;
[0032] If the equipment status table is consistent with the overall equipment status, it is determined that the production equipment can execute the serial process group; otherwise, it is determined that the production equipment cannot execute the serial process group.
[0033] Preferably, constructing a parallel production scheduling model based on the equipment status table and the parallel process group includes:
[0034] The optimization target of all workpieces in the parallel process group is determined according to the equipment status table and the parallel process group, wherein the expression of the optimization target is as follows:
[0035]
[0036] Among them, W i,j represents the net profit of the i-th workpiece, v i represents the value of the i-th workpiece, ω i represents the delay penalty coefficient of the i-th job, T i represents the delay of the i-th job, H j represents the number of initial processable time periods of production equipment j, t represents the index of the initial processable time period of production equipment j, μ jt represents the price of production equipment j during processing time t, represents the first decision variable, and if the i-th workpiece is processed in the processing time t of production equipment j, then Otherwise,
[0037] The constraint conditions of all workpieces in the parallel process group are determined according to the equipment status table and the parallel process group, wherein the constraint conditions are expressed as follows:
[0038]
[0039] Among them, C i represents the completion time of the i-th job, and p i represents the processing time of the i-th workpiece, and It represents the time period when the i-th workpiece is processed on the production equipment j. represents the starting time of processing of the i-th workpiece on production equipment j, x ij represents the second decision variable, and if the i-th workpiece is processed on production equipment j, then x ij =1, otherwise, x ij =0, represents the third decision variable, and if the i-th workpiece is processed at the l-th position on the production equipment j, then Otherwise, t ij It represents the time it takes to transport the i-th workpiece from production equipment j to the designated location, m represents the number of all production equipment, and n represents the number of all workpieces in the parallel process group;
[0040] A parallel production scheduling model is obtained according to the optimization objectives of all workpieces in the parallel process group and the constraint conditions of all workpieces in the parallel process group.
[0041] Preferably, solving the production scheduling model to obtain the second production scheduling information includes:
[0042] Initialize i=1, μjt =μ, where represents the number of unallocated time slots for production equipment j, μ represents the H j The initial price of the period;
[0043] The production equipment of the workpiece is determined according to the preset production scheduling conditions. If there are multiple production equipments that meet the preset production scheduling conditions, they are selected in ascending order of number. i is the length of the scheduling period, so that s i In [1,H j -p i +1] traverse the scheduling time range, and determine the scheduling time of multiple production equipment that meet the preset production scheduling conditions with the lowest bid [s i ,f i ];
[0044] If there is no production equipment that meets the preset production scheduling conditions, i is the length of the scheduling period, so that s i In [1,H j -p i +1] traverse all production equipment within the scheduling time period and determine the scheduling period of each production equipment with the minimum bid [s i ,f i ];
[0045] Calculating the maximum net profit of the workpiece; if the workpiece has the same maximum net profit on different production equipment, scheduling the workpiece according to the production equipment with the highest bid; and determining the second production scheduling information based on the workpiece number, the production equipment number, the scheduling period of the production equipment, and the bid;
[0046] Determine whether all workpieces are production scheduled. If all workpieces are production scheduled, the production scheduling ends. Otherwise, i=i+1 and repeat the above operation.
[0047] Preferably, the expression of the second production scheduling information is as follows:
[0048] <i,j,s i ,f i ,b i >
[0049] Among them, i represents the number of the workpiece, j represents the number of the production equipment, and s i Indicates the starting period of workpiece processing, f i Indicates the end of workpiece processing, b i represents the bid price of the artifact;
[0050] The production scheduling conditions are as follows:
[0051]
[0052] Among them, j * It represents the number of production equipment that meets the production scheduling conditions, and M represents the set of all equipment.
[0053] The technical solution adopted to solve the above technical problems is: an intelligent production scheduling management method, which is applicable to the intelligent production scheduling management system described above, comprising:
[0054] Acquire order data, acquire demand information of all workpieces of the product to be scheduled based on the order data, and acquire production process information of the product to be scheduled based on the demand information of all workpieces;
[0055] Determine a constraint matrix based on the production process information of the product to be scheduled, and divide the production process information of the product to be scheduled into a parallel process group, a serial process group, and an assembly process based on the constraint matrix;
[0056] Monitor the production status of all production equipment in real time to obtain an equipment status table, and determine whether the production equipment can execute the serial process group according to the equipment status table;
[0057] If the production equipment can execute the serial process group, sequentially scheduling the serial process group according to the production equipment to obtain first production scheduling information, building a parallel production scheduling model according to the equipment status table and the parallel process group, and solving the production scheduling model to obtain second production scheduling information;
[0058] If the production equipment cannot execute the serial process group, a parallel production scheduling model is constructed based on the equipment status table and the parallel process group, the production scheduling model is solved to obtain second production scheduling information, and the production status of all production equipment is continuously monitored in real time until the production equipment can execute the serial process group to obtain first production scheduling information;
[0059] Production scheduling information of the product to be scheduled is obtained according to the first scheduling information, the second scheduling information and the third scheduling information corresponding to the assembly process.
[0060] The beneficial effects of the present invention are as follows: (1) The present invention intelligently divides parallel process groups and serial process groups. The system can make reasonable production scheduling arrangements according to actual conditions. Parallel processes can be carried out simultaneously to improve production efficiency, while serial processes can be scheduled sequentially according to the availability of production equipment, avoiding unnecessary waiting and idle time of equipment resources. By monitoring the equipment status in real time, the production scheduling plan can be dynamically adjusted. When the equipment fails or cannot execute a certain process, the production scheduling plan can be adjusted in time to avoid delays in the production plan. By solving the scheduling model of the parallel process group, it can ensure that multiple processes can be processed in parallel, thereby maximizing resource utilization and shortening the production cycle; (2) The present invention determines whether the equipment can execute the serial process group. The system ensures that each device is working at its optimal load. When some equipment is temporarily unable to execute serial processes, parallel scheduling is used to enable other equipment to maintain efficient operation, avoid resource waste, and adjust the production scheduling order according to the real-time status of the equipment. The system can not only effectively reduce the idle time of equipment, but also flexibly respond to emergencies in production (such as equipment failure, emergency orders, etc.), ensure continuous production, and avoid the low efficiency brought by traditional manual scheduling; (3) By acquiring order data, workpiece demand information and production process information, the system can build an accurate production scheduling model, which makes the production plan more accurate and can predict the production cycle of each link, providing a basis for resource allocation and logistics arrangements, and making production scheduling decisions in a data-driven manner, avoiding the unreasonable arrangements and errors that may be brought about by manual scheduling, and improving the accuracy and reliability of scheduling. BRIEF DESCRIPTION OF THE DRAWINGS
[0061] Figure 1 A schematic diagram of the system architecture of the overall system in an embodiment of the present invention;
[0062] Figure 2 The figure is a flowchart of the steps of the overall method in one embodiment of the present invention.
[0063] Figure numerals: 1. Information acquisition unit; 2. Process division unit; 3. Status monitoring unit; 4. First scheduling unit; 5. Second scheduling unit; 6. Production scheduling integration unit. DETAILED DESCRIPTION
[0064] Example 1, as Figure 1 As shown, the present invention proposes an intelligent production scheduling management system, including:
[0065] Information acquisition unit 1, which is used to acquire order data, obtain demand information of all workpieces of the product to be scheduled based on the order data, and obtain production process information of the product to be scheduled based on the demand information of all workpieces;
[0066] Process division unit 2, which is used to determine a constraint matrix based on the production process information of the product to be scheduled, and divide the production process information of the product to be scheduled into parallel process groups, serial process groups and assembly processes according to the constraint matrix;
[0067] The status monitoring unit 3 is used to monitor the production status of all production equipment in real time to obtain an equipment status table, and judge whether the production equipment can execute the serial process group according to the equipment status table;
[0068] The first scheduling unit 4 is used to schedule the serial process group in sequence according to the production equipment if the production equipment can execute the serial process group, so as to obtain the first scheduling information, and to build a parallel production scheduling model according to the equipment status table and the parallel process group, and to solve the production scheduling model to obtain the second scheduling information.
[0069] In the present invention, order data refers to a production order placed by a customer, which contains detailed product demand information, such as product type, quantity, delivery date, etc.; workpiece demand information refers to the demand situation of all product parts or workpieces involved in the order; production process information refers to all production steps (i.e., processes) required to manufacture a certain product, which may involve different production processes such as cutting, welding, processing, and assembly; constraint matrix refers to the constraint matrix used to describe the mutual constraint relationship between different processes in production scheduling, for example, some processes must be started after other processes are completed; parallel process group refers to a process group that can be carried out simultaneously, these processes are not dependent on each other, and can be produced in parallel; serial process group refers to a process group that must be carried out in sequence, there is a dependency relationship between these processes, and the subsequent process must wait for the previous process to be completed before it can start; assembly process refers to the final assembly process in the production process after the workpiece needs to be processed or manufactured; the equipment status table is a table or database that records the status of all production equipment, usually including information such as the equipment's ID, status, and current working content.
[0070] In an optional embodiment, the system further includes:
[0071] The second scheduling unit 5 is used to build a parallel production scheduling model based on the equipment status table and the parallel process group if the production equipment cannot execute the serial process group, solve the production scheduling model to obtain the second production scheduling information, and continuously monitor the production status of all production equipment in real time until the production equipment can execute the serial process group to obtain the first production scheduling information;
[0072] The production scheduling integration unit 6 is used to obtain production scheduling information of the product to be scheduled based on the first production scheduling information, the second production scheduling information and the third production scheduling information corresponding to the assembly process.
[0073] In a second embodiment, an intelligent production scheduling management system proposed by the present invention is provided. Compared with the first embodiment, this embodiment further includes: obtaining demand information of all workpieces of the product to be scheduled based on order data, and obtaining production process information of the product to be scheduled based on the demand information of all workpieces, including:
[0074] Get the name of the product to be scheduled based on the order data;
[0075] Match the product name to be scheduled with the preset product library to obtain the workpiece demand table corresponding to the product name to be scheduled;
[0076] Determine the workpiece names and required quantities of all workpieces of the products to be scheduled according to the workpiece requirement table;
[0077] Match the workpiece name with the preset workpiece library to obtain the workpiece production process table corresponding to the workpiece. Repeat the above operation until all workpieces in the workpiece demand table are processed to obtain the production process information of the product to be scheduled.
[0078] In this embodiment, the preset product library is a database containing information on all possible products that may be produced, including a detailed description, technical requirements, production process, etc. of each product; the workpiece requirement table lists detailed information on all workpieces (such as parts, materials, etc.) required to produce a certain product, including the name, quantity, specifications, etc. of each workpiece; the preset workpiece library is a database containing information on all workpieces (parts, raw materials, etc.), which may include the name, specifications, materials, production process, usage scenarios, etc. of the workpiece. The workpiece library is a reference used by the scheduling system to match workpiece names and obtain detailed process information; matching refers to finding relevant information based on the name of the product to be scheduled or the name of the workpiece by querying the preset library (product library or workpiece library). For example, matching the product to be scheduled with the product library to find all workpiece requirements corresponding to the product; then matching each workpiece with the workpiece library to obtain the corresponding production process table.
[0079] In an optional embodiment, determining a constraint matrix based on production process information of the product to be scheduled includes:
[0080] Determine the first production process without sequence requirement among the products to be scheduled according to the production process information of the products to be scheduled;
[0081] Determine the second production process with priority requirement for the product to be scheduled according to the production process information of the product to be scheduled;
[0082] Determine the third production process with restricted requirements for the product to be scheduled based on the production process information of the product to be scheduled;
[0083] A constraint matrix is determined based on the first production process, the second production process, and the third production process, where the constraint matrix is expressed as follows:
[0084]
[0085] in, Indicates the zth row and the Elements of a column.
[0086] In an optional embodiment, the production process information of the product to be scheduled is divided into a parallel process group, a serial process group, and an assembly process according to the constraint matrix, including:
[0087] Determine the first production process group, the second production process group, and the third production process group of the product to be scheduled according to each element in the constraint matrix;
[0088] The first production process group is used as a serial process group;
[0089] The second production process group and the third production process group are used as parallel process groups;
[0090] The assembly process is obtained based on the workpieces completed by the serial process group and the parallel process group.
[0091] In an optional embodiment, determining whether the production equipment can execute the serial process group according to the equipment status table includes:
[0092] Determine the total equipment status required for the serial process group;
[0093] Matching the total device status with the device status table to determine whether the device status table is consistent with the total device status;
[0094] If the equipment status table is consistent with the overall equipment status, it is determined that the production equipment can execute the serial process group; otherwise, it is determined that the production equipment cannot execute the serial process group.
[0095] It should be noted that the total equipment status refers to the comprehensive operating status of all equipment within a given time. This is determined based on the requirements of the serial process group and the equipment status required by each process. In other words, according to the requirements of each process, the status of each device is integrated to form an overall status description. For example, if a serial process group requires the idle state of specific equipment, the total equipment status should require that these devices are idle at that moment.
[0096] In an optional embodiment, a parallel production scheduling model is constructed based on the equipment status table and the parallel process group, including:
[0097] The optimization targets of all workpieces in the parallel process group are determined based on the equipment status table and the parallel process group. The expression of the optimization target is as follows:
[0098]
[0099] Among them, W i,j represents the net profit of the i-th workpiece, v i represents the value of the i-th workpiece, ω i represents the delay penalty coefficient of the i-th job, T i represents the delay of the i-th job, H j represents the number of initial processable time periods of production equipment j, t represents the index of the initial processable time period of production equipment j, μ jt represents the price of production equipment j during processing time t, represents the first decision variable, and if the i-th workpiece is processed in the processing time t of production equipment j, then Otherwise,
[0100] The constraints of all workpieces in the parallel process group are determined based on the equipment status table and the parallel process group. The constraint expressions are as follows:
[0101]
[0102] Among them, C i represents the completion time of the i-th job, and p i represents the processing time of the i-th workpiece, and It represents the time period when the i-th workpiece is processed on the production equipment j. represents the starting time of processing of the i-th workpiece on production equipment j, x ij represents the second decision variable, and if the i-th workpiece is processed on production equipment j, then x ij =1, otherwise, x ij =0, represents the third decision variable, and if the i-th workpiece is processed at the l-th position on the production equipment j, then Otherwise, t ij It represents the time it takes to transport the i-th workpiece from production equipment j to the designated location, m represents the number of all production equipment, and n represents the number of all workpieces in the parallel process group;
[0103] A parallel production scheduling model is obtained according to the optimization objectives of all workpieces in the parallel process group and the constraint conditions of all workpieces in the parallel process group.
[0104] In an optional embodiment, the production scheduling model is solved to obtain the second production scheduling information, including:
[0105] Initialize i=1, μ jt =μ, where represents the number of unallocated time slots for production equipment j, μ represents the H j The initial price of the period;
[0106] Determine the production equipment of the workpiece according to the preset production scheduling conditions. If there are multiple production equipment that meet the preset production scheduling conditions, select them in ascending order of number. i is the length of the scheduling period, so that s i In [1,H j -p i +1] traverse the scheduling time range, and determine the scheduling time of multiple production equipment that meet the preset production scheduling conditions with the lowest bid [s i ,f i ];
[0107] If there is no production equipment that meets the preset production scheduling conditions, i is the length of the scheduling period, so that s i In [1,H j -p i +1] traverse all production equipment within the scheduling time period and determine the scheduling period of each production equipment with the minimum bid [s i ,f i ];
[0108] Calculate the maximum net profit of the workpiece. If the workpiece has the same maximum net profit on different production equipment, schedule it according to the production equipment with the highest bid. Determine the second production schedule based on the workpiece number, production equipment number, production equipment scheduling period, and bid.
[0109] Determine whether all workpieces are production scheduled. If all workpieces are production scheduled, the production scheduling ends. Otherwise, i=i+1 and repeat the above operation.
[0110] In an optional embodiment, the expression of the second production scheduling information is as follows:
[0111] <i,j,s i ,f i ,b i >
[0112] Among them, i represents the number of the workpiece, j represents the number of the production equipment, and s i Indicates the starting period of workpiece processing, f i Indicates the end of workpiece processing, b i represents the bid price of the artifact;
[0113] The production scheduling conditions are as follows:
[0114]
[0115] Among them, j * It represents the number of production equipment that meets the production scheduling conditions, and M represents the set of all equipment.
[0116] Example 3, as Figure 2 As shown, the present invention proposes an intelligent production scheduling management method, which is applicable to the intelligent production scheduling management system, including:
[0117] S1. Obtain order data, obtain demand information of all workpieces of the product to be scheduled based on the order data, and obtain production process information of the product to be scheduled based on the demand information of all workpieces;
[0118] S2. Determine a constraint matrix based on the production process information of the product to be scheduled, and divide the production process information of the product to be scheduled into a parallel process group, a serial process group, and an assembly process based on the constraint matrix;
[0119] S3. Monitor the production status of all production equipment in real time to obtain an equipment status table, and determine whether the production equipment can execute the serial process group based on the equipment status table;
[0120] S4. If the production equipment can execute the serial process group, sequentially schedule the serial process group according to the production equipment to obtain first production scheduling information, and construct a parallel production scheduling model based on the equipment status table and the parallel process group, and solve the production scheduling model to obtain second production scheduling information;
[0121] S5. If the production equipment cannot execute the serial process group, a parallel production scheduling model is constructed based on the equipment status table and the parallel process group. The production scheduling model is solved to obtain the second production schedule information. The production status of all production equipment is continuously monitored in real time until the production equipment can execute the serial process group to obtain the first production schedule information.
[0122] S6. Obtain production scheduling information of the product to be scheduled according to the first scheduling information, the second scheduling information, and the third scheduling information corresponding to the assembly process.
[0123] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.
Claims
1. An intelligent production scheduling management system, characterized in that: include: An information acquisition unit (1), the information acquisition unit (1) is used to acquire order data, acquire demand information of all workpieces of the product to be scheduled based on the order data, and acquire production process information of the product to be scheduled based on the demand information of all workpieces; A process division unit (2), the process division unit (2) is used to determine a constraint matrix based on the production process information of the product to be scheduled, and divide the production process information of the product to be scheduled into a parallel process group, a serial process group and an assembly process according to the constraint matrix; A status monitoring unit (3), the status monitoring unit (3) is used to monitor the production status of all production equipment in real time to obtain an equipment status table, and to determine whether the production equipment can execute the serial process group according to the equipment status table; The first scheduling unit (4) is used to, if the production equipment can execute the serial process group, sequentially schedule the serial process group according to the production equipment to obtain first scheduling information, and to construct a parallel production scheduling model according to the equipment status table and the parallel process group, and to solve the production scheduling model to obtain second scheduling information.
2. The intelligent production scheduling management system according to claim 1, characterized in that: The system further comprises: The second scheduling unit (5) is configured to, if the production equipment cannot execute the serial process group, construct a parallel production scheduling model based on the equipment status table and the parallel process group, solve the production scheduling model to obtain second production scheduling information, and continuously monitor the production status of all production equipment in real time until the production equipment can execute the serial process group to obtain first production scheduling information; A production scheduling integration unit (6) is used to obtain production scheduling information of the product to be scheduled based on the first production scheduling information, the second production scheduling information and the third production scheduling information corresponding to the assembly process.
3. The intelligent production scheduling management system according to claim 2, characterized in that: Obtaining demand information of all workpieces of the product to be scheduled according to the order data, and obtaining production process information of the product to be scheduled according to the demand information of all workpieces, including: Obtain the name of the product to be scheduled according to the order data; Matching the product name to be scheduled with a preset product library to obtain a workpiece demand table corresponding to the product name to be scheduled; Determine the workpiece names and required quantities of all workpieces of the product to be scheduled according to the workpiece requirement table; The workpiece name is matched with the preset workpiece library to obtain the workpiece production process table corresponding to the workpiece, and the above operation is repeated until all workpieces in the workpiece demand table are processed to obtain the production process information of the product to be scheduled.
4. The intelligent production scheduling management system according to claim 3, characterized in that: Determining a constraint matrix based on the production process information of the product to be scheduled includes: Determining a first production process without sequence requirements for the product to be scheduled according to the production process information of the product to be scheduled; Determining a second production process with a priority requirement for the product to be scheduled according to the production process information of the product to be scheduled; Determining a third production process with restrictive requirements for the product to be scheduled according to the production process information of the product to be scheduled; A constraint matrix is determined according to the first production process, the second production process, and the third production process, wherein the constraint matrix is expressed as follows: in, Indicates the zth row and the Elements of a column.
5. The intelligent production scheduling management system according to claim 4, characterized in that: Dividing the production process information of the product to be scheduled into a parallel process group, a serial process group, and an assembly process according to the constraint matrix, including: Determine the first production process group, the second production process group, and the third production process group of the product to be scheduled according to each element in the constraint matrix; Using the first production process group as the serial process group; The second production process group and the third production process group are used as parallel process groups; An assembly process is obtained based on the workpieces completed by the serial process group and the parallel process group.
6. The intelligent production scheduling management system according to claim 5, characterized in that: Determining whether the production equipment can execute the serial process group according to the equipment status table includes: Determining the total equipment state required by the serial process group; matching the overall device status with the device status table to determine whether the device status table matches the overall device status; If the equipment status table is consistent with the overall equipment status, it is determined that the production equipment can execute the serial process group; otherwise, it is determined that the production equipment cannot execute the serial process group.
7. An intelligent production scheduling management system according to claim 6, characterized in that: Constructing a parallel production scheduling model according to the equipment status table and the parallel process group includes: The optimization target of all workpieces in the parallel process group is determined according to the equipment status table and the parallel process group, wherein the expression of the optimization target is as follows: Among them, W i,j represents the net profit of the i-th workpiece, v i represents the value of the i-th workpiece, ω i represents the delay penalty coefficient of the i-th job, T i represents the delay of the i-th job, H j represents the number of initial processable time periods of production equipment j, t represents the index of the initial processable time period of production equipment j, μ jt represents the price of production equipment j during processing time t, represents the first decision variable, and if the i-th workpiece is processed in the processing time t of production equipment j, then Otherwise, =0; The constraint conditions of all workpieces in the parallel process group are determined according to the equipment status table and the parallel process group, wherein the constraint conditions are expressed as follows: Among them, C i represents the completion time of the i-th job, and p i represents the processing time of the i-th workpiece, and It represents the time period when the i-th workpiece is processed on the production equipment j. represents the starting time of processing of the i-th workpiece on production equipment j, x ij represents the second decision variable, and if the i-th workpiece is processed on production equipment j, then x ij =1, otherwise, x ij =0, represents the third decision variable, and if the i-th workpiece is processed at the l-th position on the production equipment j, then Otherwise, t ij It represents the time it takes to transport the i-th workpiece from production equipment j to the designated location, m represents the number of all production equipment, and n represents the number of all workpieces in the parallel process group; A parallel production scheduling model is obtained according to the optimization objectives of all workpieces in the parallel process group and the constraint conditions of all workpieces in the parallel process group.
8. An intelligent production scheduling management system according to claim 7, characterized in that: Solving the production scheduling model to obtain second production scheduling information includes: Initialize i=1, μ jt =μ, where represents the number of unallocated time slots for production equipment j, μ represents the H j The initial price of the period; The production equipment of the workpiece is determined according to the preset production scheduling conditions. If there are multiple production equipments that meet the preset production scheduling conditions, they are selected in ascending order of number. i is the length of the scheduling period, so that s i In [1,H j -p i +1] traverse the scheduling time range, and determine the scheduling time of multiple production equipment that meet the preset production scheduling conditions with the lowest bid [s i ,f i ]; If there is no production equipment that meets the preset production scheduling conditions, i is the length of the scheduling period, so that s i In [1,H j -p i +1] traverse all production equipment within the scheduling time period and determine the scheduling period of each production equipment with the minimum bid [s i ,f i ]; Calculating the maximum net profit of the workpiece; if the workpiece has the same maximum net profit on different production equipment, scheduling the workpiece according to the production equipment with the highest bid; and determining the second production scheduling information based on the workpiece number, the production equipment number, the scheduling period of the production equipment, and the bid; Determine whether all workpieces are production scheduled. If all workpieces are production scheduled, the production scheduling ends. Otherwise, i=i+1 and repeat the above operation.
9. The intelligent production scheduling management system according to claim 8, characterized in that: The expression of the second production scheduling information is as follows: <i,j,s i ,f i ,b i >; Among them, i represents the number of the workpiece, j represents the number of the production equipment, and s i Indicates the starting period of workpiece processing, f i Indicates the end of workpiece processing, b i represents the bid price of the artifact; The production scheduling conditions are as follows: Among them, j * It represents the number of production equipment that meets the production scheduling conditions, and M represents the set of all equipment.
10. An intelligent production scheduling management method, which is applicable to the intelligent production scheduling management system according to any one of claims 9, characterized in that: include: Acquire order data, acquire demand information of all workpieces of the product to be scheduled based on the order data, and acquire production process information of the product to be scheduled based on the demand information of all workpieces; Determine a constraint matrix based on the production process information of the product to be scheduled, and divide the production process information of the product to be scheduled into a parallel process group, a serial process group, and an assembly process based on the constraint matrix; Monitor the production status of all production equipment in real time to obtain an equipment status table, and determine whether the production equipment can execute the serial process group according to the equipment status table; If the production equipment can execute the serial process group, sequentially scheduling the serial process group according to the production equipment to obtain first production scheduling information, building a parallel production scheduling model according to the equipment status table and the parallel process group, and solving the production scheduling model to obtain second production scheduling information; If the production equipment cannot execute the serial process group, a parallel production scheduling model is constructed based on the equipment status table and the parallel process group, the production scheduling model is solved to obtain second production scheduling information, and the production status of all production equipment is continuously monitored in real time until the production equipment can execute the serial process group to obtain first production scheduling information; Production scheduling information of the product to be scheduled is obtained according to the first scheduling information, the second scheduling information and the third scheduling information corresponding to the assembly process.