CN114912814A - Jobshop intelligent scheduling system based on digital twin technology - Google Patents
Jobshop intelligent scheduling system based on digital twin technology Download PDFInfo
- Publication number
- CN114912814A CN114912814A CN202210567884.3A CN202210567884A CN114912814A CN 114912814 A CN114912814 A CN 114912814A CN 202210567884 A CN202210567884 A CN 202210567884A CN 114912814 A CN114912814 A CN 114912814A
- Authority
- CN
- China
- Prior art keywords
- scheduling
- production
- jobshop
- strategy
- layer
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000005516 engineering process Methods 0.000 title claims abstract description 29
- 238000000034 method Methods 0.000 claims abstract description 121
- 238000004519 manufacturing process Methods 0.000 claims abstract description 114
- 230000008569 process Effects 0.000 claims abstract description 38
- 238000004088 simulation Methods 0.000 claims abstract description 10
- 238000012545 processing Methods 0.000 claims description 45
- 239000000047 product Substances 0.000 claims description 19
- 239000002994 raw material Substances 0.000 claims description 17
- 230000007306 turnover Effects 0.000 claims description 10
- 239000011265 semifinished product Substances 0.000 claims description 6
- 238000009826 distribution Methods 0.000 claims description 2
- 238000000605 extraction Methods 0.000 claims description 2
- 238000013404 process transfer Methods 0.000 claims description 2
- 238000003860 storage Methods 0.000 claims description 2
- 238000012544 monitoring process Methods 0.000 abstract description 6
- 230000002452 interceptive effect Effects 0.000 abstract description 2
- 238000003754 machining Methods 0.000 description 4
- 230000002159 abnormal effect Effects 0.000 description 3
- 230000015556 catabolic process Effects 0.000 description 3
- 230000010485 coping Effects 0.000 description 3
- 238000006731 degradation reaction Methods 0.000 description 3
- 230000003993 interaction Effects 0.000 description 3
- 230000002411 adverse Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000002360 preparation method Methods 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005215 recombination Methods 0.000 description 1
- 230000006798 recombination Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06316—Sequencing of tasks or work
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/04—Manufacturing
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Primary Health Care (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Manufacturing & Machinery (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- General Factory Administration (AREA)
Abstract
The invention discloses a jobshop intelligent scheduling system based on a digital twin technology, which comprises a jobshop digital twin model and a jobshop interactive with the same, wherein the jobshop digital twin model generates a scheduling strategy and transmits the scheduling strategy to the jobshop; the job shop receives the scheduling strategy in real time and finishes the production process according to the scheduling strategy, and the job shop digital twin model monitors the production process of the job shop in real time, if disturbance factors are monitored in the production process, the original scheduling strategy is checked whether to meet the production scheduling standard based on the discrete event simulation technology, and if not, the original scheduling strategy is updated. The invention utilizes the digital twin technology to not only reproduce the production process of the workshop in real time and improve the monitoring capability of the production process, but also improve the capability of the dispatching system to cope with disturbance in the operation process.
Description
Technical Field
The invention belongs to the technical field of intelligent manufacturing technology and industrial engineering, and particularly relates to a jobshop intelligent scheduling system based on a digital twin technology.
Background
Under the market environment with individual requirements of products, higher requirements are provided for the flexibility, robustness, processing efficiency and the like of the jobshop scheduling system, and the intelligent scheduling system is constructed into a new method and a new mode for meeting the requirements. With the development and application of automation equipment and informatization technology, digital and networked jobshop has fallen on the ground widely, and an important basis is provided for constructing an intelligent scheduling system and improving the intellectualization level of the jobshop.
Disturbance in the actual production process in the jobshop is frequent and various, external disturbance such as order change, product random release, delivery change and the like, internal disturbance such as machine fault, machine degradation, operation rework and the like, and the disturbance provides a great test for the adaptability of production scheduling, and if the disturbance cannot be found in time and is processed at a reasonable moment, the phenomena of production efficiency reduction, serious resource waste and the like are probably caused.
In the face of the disturbance problem, the performance of a scheduling method used under one or more scheduling standards is emphasized on multiple sides of the conventional jobshop scheduling system, and the pertinence is strong. However, under one or more scheduling standards, due to the limitation of a single scheduling method, the adaptability to a plurality of heterogeneous disturbance factors and the diversity of jobs is weak; in the dynamic scheduling process, the influence of real-time monitoring disturbance factors on the scheduling strategy is lacked, and the scheduling strategy cannot be updated in time when being degraded.
Disclosure of Invention
In order to solve the problems of the conventional jobshop scheduling system, the invention provides a jobshop intelligent scheduling system based on a digital twin technology, aiming at monitoring the occurrence of production disturbance and the moment of influence on a scheduling strategy in real time under different scheduling standards, combining priority scheduling rules to form a new scheduling method so as to update the scheduling strategy, efficiently coping with the occurring disturbance factors, and improving the robustness and the production efficiency of a production system to a certain extent.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a jobshop intelligent scheduling system based on digital twin technology comprises a jobshop digital twin model and a jobshop interactive with the same;
the jobshop digital twin model collects production information in the production process of the jobshop in real time, generates a scheduling strategy according to the production tasks issued to the jobshop and the collected production information, and issues the scheduling strategy to the jobshop;
the job shop receives the scheduling strategy in real time and completes the production process according to the scheduling strategy, the job shop digital twin model monitors the production process of the job shop in real time, if disturbance factors are monitored in the production process, whether the original scheduling strategy meets the production scheduling standard is checked based on a discrete event simulation technology, and if the original scheduling strategy does not meet the production scheduling standard, the original scheduling strategy is updated.
The jobshop intelligent scheduling system based on the digital twin technology has the beneficial effects that:
according to the invention, by applying the digital twin technology to the jobshop, the production process of the jobshop is reproduced in real time, the monitoring capability of the production process is improved, the process of obtaining a scheduling method and a generated scheduling strategy is integrated, and the capability of a scheduling system for coping with disturbance in the operation process is improved; a plurality of priority scheduling rules are preferably selected from the established priority scheduling rule base, and the scheduling method formed by flexibly combining the priority scheduling rules overcomes the limitation that the adaptability of a single scheduling method is insufficient under one or more scheduling standards; the new scheduling method is used each time the scheduling strategy needs to be updated under the influence of disturbance factors, so that the adverse effect of the original scheduling strategy is avoided.
Drawings
FIG. 1 is a flowchart illustrating an overall job shop intelligent scheduling system based on digital twin technology according to an embodiment of the present invention;
FIG. 2 is an architecture diagram of a jobshop digital twin model;
FIG. 3 is a flow chart of the generation, execution and update of scheduling policies;
FIG. 4 is a flow chart of the production operation of the job shop.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In one embodiment, as shown in fig. 1, the invention provides a jobshop intelligent scheduling system based on a data twin technology, which comprises a jobshop digital twin model and a jobshop workshop interacting with the same.
The jobshop digital twin model collects production information in the production process of a jobshop in real time, wherein the production information comprises production process information, information of production elements in the shop and operation parameters of the production elements in the shop, the production process information comprises an operation process flow, an operation carrying flow, a raw material extracting flow and a finished product storing flow, the information of the production elements in the shop comprises processing machine information, carrying tool information, stacker information, clamping tool information and processing machine processing operation information, and the operation parameters of the production elements in the shop comprise processing machine operation parameters, carrying tool transportation parameters, stacker operation parameters and clamping tool operation parameters. And then generating a scheduling strategy according to the production tasks issued to the job shop and the collected production information, and issuing the scheduling strategy to the job shop.
The job shop receives the scheduling strategy in real time and finishes the production process according to the scheduling strategy, and the job shop digital twin model monitors the production process of the job shop in real time, if disturbance factors are monitored in the production process, the original scheduling strategy is checked whether to meet the production scheduling standard based on the discrete event simulation technology, and if not, the original scheduling strategy is updated.
When the jobshop digital twin model is constructed, data generated in the workshop production process, workshop element parameters and the like are collected in real time, processed and analyzed, and the jobshop production process and workshop elements are reproduced in real time in high fidelity in a virtual space. In order to meet the high efficiency of the production process, a production scheduling method and a production scheduling strategy are embedded in the constructed virtual model, and finally a jobshop digital twin model comprising a method layer, a strategy layer and an execution layer is constructed, wherein the three layers are mutually fed back and supplement each other as shown in fig. 2. The powerful capabilities of the digital twin technology such as virtual-real interaction, comprehensive measurement, comprehensive analysis and prediction can overcome the limitations of the traditional jobshop scheduling system to a certain extent.
The method layer is responsible for generating an integral scheduling strategy according to resource constraints in the production task and the job shop, and in the production process, when the method layer receives information which is sent by the strategy layer and needs to update the scheduling strategy, the method layer selects and generates a new more suitable scheduling method based on the current production task and shop resources and updates the original scheduling strategy by the scheduling strategy generated by the new scheduling method.
After a production task is issued, counting available production resources of a workshop, selecting a priority scheduling rule PDR from a priority scheduling rule base PDR _ set by taking a procedure as a unit based on a discrete event simulation technology m p The machine that processed each job and the order in which the jobs were processed before each machine are determined. All selected priority scheduling rules are combined into a scheduling method PDR _ set m The scheduling method is a job shop scheduling method in the current production scene. Priority scheduling rule PDR assigned to each process m p Generating a sub-scheduling strategy, and combining all the sub-scheduling strategies into a wholeScheduling policy of the body. Each sub-scheduling strategy is responsible for scheduling the production process on each process. Because a core purpose of the scheduling is to select machines for processing jobs in the production system and order jobs before the machines, and the priority scheduling rule has the advantages of universality, diversity, simplicity and the like, the scheduling method formed by flexibly combining the priority scheduling rule can overcome the limitation of insufficient adaptability of a single scheduling method.
The strategy layer is responsible for transmitting the scheduling strategy generated by the method layer into the execution layer and supervising the production process of the execution layer. In the supervision process, according to external disturbance factors from the outside and/or abnormal phenomena (namely, internal disturbance factors of a job shop) fed back by an execution layer, a strategy layer self-realizes self-inspection of the performance adaptability of the original scheduling strategy, namely, whether the original scheduling strategy meets the production scheduling standard is inspected based on a discrete event simulation technology, and if the original scheduling strategy does not meet the production scheduling standard, namely, the scheduling strategy is not suitable for the current production environment any more, information of the scheduling strategy needing to be updated is fed back to a method layer.
The execution layer is directly connected with the real job shop, and is responsible for receiving the scheduling strategy issued by the strategy layer and applying the scheduling strategy to the production process of the job shop. Meanwhile, the execution layer can map the real production workshop in a real-time high-fidelity manner by collecting data which can represent the states of the production process and the workshop elements of the real production workshop, such as the operation parameters of the machine, the actual processing time of the machine, the use condition of raw materials, the completion condition of finished products, the geometric information of the workshop production elements, the operation parameters of the workshop production elements and the like, analyze the state of the production process of the production workshop and feed back the information (disturbance factors) of abnormal states to the strategy layer.
The scheduling policy generation process from the method layer to the policy layer and the scheduling application process from the policy layer to the execution layer are one task flow delivery process.
Feedback from the enforcement layer, external perturbations to the policy layer, and from the policy layer to the method layer is a process of information flow passing.
The interaction between the layers of the jobshop digital twin model is facilitated by the transfer process of the task flow and the information flow, and disturbance factors which should occur to the production process can be found out in time.
The reasonable selection and use of the production scheduling method are efficient and orderly guarantees in the whole production process and are responsible for generating scheduling strategies. A method layer in the jobshop digital twin model is based on a heuristic algorithm, namely a priority scheduling rule PDR, which is widely available in quantity and variety, firstly, a priority scheduling rule base PDR _ set is constructed, the priority scheduling rule PDR contained in the priority scheduling rule base PDR is selected according to parameter data para1 collected in the production process and parameter data para2 required for solving the scheduling standard, and para1 and para2 are combined into parameter para, wherein the parameters of the production process such as the processing time of machine processing jobs, the transportation time of jobs among processes and the like, and the parameters required for solving the scheduling standard such as the delivery period of jobs under the maximum delay time scheduling standard, the weight coefficient of jobs under the total weighted completion time scheduling standard and the like.
Next, a discrete event simulation technology is utilized to preferably select P superior priority scheduling rules PDR combination forming scheduling method PDR _ set from the priority scheduling rule base PDR _ set by taking a process as a unit m Wherein P is the number of working procedures in the job shop workshop, and the priority scheduling rule PDR assigned to the P working procedure is the P sub-scheduling method PDR m p ，PDR_set、PDR_set m And PDR m p The relationship (c) is shown in the formula (1). PDR m p The process of generating the sub-scheduling policy at the p-th procedure comprises setting a selection policy for selecting a machine to be processed by the job and a priority policy for waiting for the processed job before the machine. The procedure for setting the selection policy for job selection of the machine to be processed is shown in equation (2), where para ijp Values of parameters, f, representing the machine j in process p for operation i d (para ijp ) Shows solving for the parameter value para using the d-th PDR ijp J represents the number of machines included in the p-th process, and J, which corresponds to the obtained maximum priority value, is the machine to be processed selected by the job. Similarly, the process of setting the priority policy of the job waiting to be processed before the machine is shown in fig. 3, where I represents the number of jobs waiting to be processed before the machine, and the maximum priority value obtained finally corresponds to the maximum priority valuei is the job that is first processed by the machine. PDR m p And combining the plurality of solved sub-scheduling strategies to form an integral scheduling strategy.
The execution of the scheduling strategy is a guarantee for monitoring the actual production process and collecting the parameter data of production operation and workshop elements in real time, and is responsible for analyzing the data collected from the actual production workshop and discovering and uploading abnormal phenomena (internal disturbance) such as equipment failure, equipment degradation and the like in time. Among them, because the scheduling method (priority scheduling rule combination) for generating the scheduling policy is deployed around the operation and processing machine, the disturbance such as fault, degradation and the like of the auxiliary equipment such as the transportation tool and the stacker indirectly affects the performance of the scheduling policy. In order to directly express the influence of the disturbance factors on the current scheduling strategy and further promote the self-checking of the performance of the scheduling strategy, the time except the machining operation of the machining machine is collectively called non-value-added time, namely the preparation time before the operation is processed, such as transportation time and carrying time, so that the disturbance factors indirectly influencing the scheduling strategy are converted into time parameters directly influencing the performance of the scheduling strategy.
The updating of the scheduling strategy is a guarantee for continuous, efficient and orderly execution of the production process and is responsible for processing disturbance factors encountered in the production process. Referring to fig. 3, when a disturbance factor is encountered and fed back to the policy layer, the scheduling policy generated by the scheduling method has certain robustness. Therefore, the strategy layer can utilize the discrete event simulation technology to check that the current original scheduling strategy of the production state is based on the production tasks and workshop resources after disturbanceIf the production scheduling standard can be met, the original scheduling strategy is continuously executed; if the production scheduling standard can not be met, the information of the scheduling strategy needing to be updated is fed back to the method layer, and the method layer generates a new scheduling method PDR _ set according to the production task and the production resource recombination priority scheduling rule at the updating moment m And then generating a new scheduling strategy, and updating the original scheduling strategy by the new scheduling strategy so as to realize the updating of the scheduling strategy.
The scheduling method connects the scheduling strategies into a whole, and the scheduling strategies also connect the workshop production elements into a whole. The operation process of the processing workshop is carried out under the guidance of a scheduling strategy. The operation process of the whole scheduling system comprises the operation of the jobshop digital twin model, the production process of the actual jobshop and the interaction of the production process of the actual jobshop digital twin model and the actual jobshop digital twin model.
The operation process of the scheduling system takes a processing machine as a core, and the time consumption of the whole production process is divided into two categories according to value-added time and non-value-added time. The non-value-added time is the time for processing the operation by the processing machine, and the non-value-added time is the preparation time of the operation before processing, and comprises the time for carrying the operation by carrying equipment, the finished product storage time and the raw material extraction time of the stacker.
The scheduling policy generated based on the priority scheduling rule is a characteristic for specifying the machine of the machining operation and the order of the machining operation in a certain process. The workshop elements of each sub-scheduling strategy for guiding the production process are processing machines and carrying tools for carrying operation on one process, if the process is an initial process, the workshop elements comprise stackers for extracting raw materials, and if the process is a final process, the workshop elements comprise stackers for storing finished products. Wherein, the processing machine is the core equipment.
Referring to fig. 4, the production operation process of the job shop after receiving the scheduling policy includes:
the raw materials are conveyed to a raw material turnover area from a raw material shelf through a stacker, and are conveyed to a product-in-process turnover area before the first procedure of the operation through a conveying tool according to the process flow of each operation to wait for processing; placing the raw materials in the product turnover area on a processing machine by using a clamping tool, processing the raw materials by the processing machine, placing the raw materials in the semi-finished product turnover area beside a working procedure after the processing is finished, and determining the operation distribution of the working procedure machine and the processed sequence of the previous generation processing operation of each machine by a sub-scheduling strategy;
if the working procedure is the last working procedure, the finished product is processed by the processing machine which finishes the working procedure, and the finished product is transported to a finished product turnover area through a transport trolley and is transported to a finished product shelf through a finished product stacker;
if the working procedure is not the last working procedure, the operation after the processing of the processing machine which can complete the working procedure is a semi-finished product, and the semi-finished product is transported to a product-in-process transfer area of a downstream working procedure through a transport trolley to be prepared for processing by the processing machine in the downstream working procedure, wherein the processing operation flow of the downstream working procedure is the same as that of the first working procedure.
According to the invention, by applying the digital twin technology to the jobshop, the production process of the jobshop is reproduced in real time, the monitoring capability of the production process is improved, the process of obtaining a scheduling method and a generated scheduling strategy is integrated, and the capability of a scheduling system for coping with disturbance in the operation process is improved; a plurality of priority scheduling rules are preferably selected from the established priority scheduling rule base, and the scheduling method formed by flexibly combining the priority scheduling rules overcomes the limitation that the adaptability of a single scheduling method is insufficient under one or more scheduling standards; the new scheduling method is used each time the scheduling strategy needs to be updated under the influence of disturbance factors, so that the adverse effect of the original scheduling strategy is avoided.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (5)
1. A jobshop intelligent scheduling system based on a digital twin technology is characterized by comprising a jobshop digital twin model and a jobshop interacting with the same;
the jobshop digital twin model collects production information in the production process of the jobshop in real time, generates a scheduling strategy according to the production tasks issued to the jobshop and the collected production information, and issues the scheduling strategy to the jobshop;
the job shop receives the scheduling strategy in real time and completes the production process according to the scheduling strategy, the job shop digital twin model monitors the production process of the job shop in real time, if disturbance factors are monitored in the production process, whether the original scheduling strategy meets the production scheduling standard is checked based on a discrete event simulation technology, and if the original scheduling strategy does not meet the production scheduling standard, the original scheduling strategy is updated.
2. The jobshop intelligent scheduling system based on digital twinning technology of claim 1, wherein the jobshop digital twinning model comprises a method layer, a strategy layer and an execution layer;
the method layer is responsible for generating an integral scheduling strategy according to the production task and the resource constraint in the job shop, and in the production process, when the method layer receives the information which is sent by the strategy layer and needs to update the scheduling strategy, the method layer selects and generates a new scheduling method based on the current production task and the workshop resource and updates the original scheduling strategy by the scheduling strategy generated by the new scheduling method;
the strategy layer is responsible for transmitting the scheduling strategy generated by the method layer to the execution layer and supervising the production process of the execution layer, and in the supervision process, according to external disturbance factors from the outside and/or internal disturbance factors of the job shop fed back by the execution layer, whether the original scheduling strategy meets the production scheduling standard is checked based on a discrete event simulation technology, and if not, information of the scheduling strategy needing to be updated is fed back to the method layer;
the execution layer is responsible for receiving a scheduling strategy issued by the strategy layer, applying the scheduling strategy to the production process of the jobshop and feeding back internal disturbance factors of the jobshop to the strategy layer.
3. The jobshop intelligent scheduling system based on digital twin technology as claimed in claim 2, wherein the process of the method layer generating the overall scheduling policy according to the production task and the resource constraint in the jobshop comprises the following steps:
constructing a priority scheduling rule base PDR _ set, wherein the priority scheduling rule PDR contained in the priority scheduling rule base PDR is selected according to parameter data para1 collected in the production process and parameter data para2 required by the scheduling standard;
p priority scheduling rules PDR are preferably selected from a priority scheduling rule base PDR _ set by using a discrete event simulation technology and taking a process as a unit m p Combined scheduling method PDR _ set m Wherein P is the number of working procedures in the job shop;
using scheduling method PDR _ set m An overall scheduling policy is generated that includes a plurality of sub-scheduling policies.
4. The system as claimed in claim 2, wherein the production operation process of the job shop after receiving the scheduling policy comprises:
the raw materials are conveyed to a raw material turnover area from a raw material shelf through a stacker, and are conveyed to a product-in-process turnover area before the first procedure of the operation through a conveying tool according to the process flow of each operation to wait for processing; placing the raw materials in the product turnover area on a processing machine by using a clamping tool, processing the raw materials by the processing machine, placing the raw materials in the semi-finished product turnover area beside a working procedure after the processing is finished, and determining the operation distribution of the working procedure machine and the processed sequence of the previous generation processing operation of each machine by a sub-scheduling strategy;
if the working procedure is the last working procedure, the finished product is processed by the processing machine which finishes the working procedure, and the finished product is transported to a finished product turnover area through a transport trolley and is transported to a finished product shelf through a finished product stacker;
if the working procedure is not the last working procedure, the operation after the processing of the processing machine which can finish the working procedure is a semi-finished product, the semi-finished product is transported to a product-in-process transfer area of a downstream working procedure through a transport trolley to be processed by the processing machine in the downstream working procedure, and the processing operation flow of the downstream working procedure is the same as that of the first working procedure.
5. The jobshop intelligent scheduling system based on digital twin technology according to claim 1, wherein the production information includes production process information, information of production elements in a workshop, and operation parameters of production elements in the workshop, the production process information includes a process flow of work, a carrying flow of work, an extraction flow of raw materials, and a storage flow of finished products, the information of production elements in the workshop includes information of processing machines, carrying tools, stacker information, clamping tools, and processing operations of processing machines, and the operation parameters of production elements in the workshop include operation parameters of processing machines, carrying tools transportation parameters, stacker operation parameters, and clamping tools operation parameters.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210567884.3A CN114912814A (en) | 2022-05-24 | 2022-05-24 | Jobshop intelligent scheduling system based on digital twin technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210567884.3A CN114912814A (en) | 2022-05-24 | 2022-05-24 | Jobshop intelligent scheduling system based on digital twin technology |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114912814A true CN114912814A (en) | 2022-08-16 |
Family
ID=82767882
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210567884.3A Pending CN114912814A (en) | 2022-05-24 | 2022-05-24 | Jobshop intelligent scheduling system based on digital twin technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114912814A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116415803A (en) * | 2023-04-18 | 2023-07-11 | 杰为软件系统(深圳)有限公司 | Discrete manufacturing system integration and scheduling method based on event arrangement |
| WO2024065484A1 (en) * | 2022-09-29 | 2024-04-04 | 西门子股份公司 | Method and apparatus for recognizing event, and device and medium |
-
2022
- 2022-05-24 CN CN202210567884.3A patent/CN114912814A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024065484A1 (en) * | 2022-09-29 | 2024-04-04 | 西门子股份公司 | Method and apparatus for recognizing event, and device and medium |
| CN116415803A (en) * | 2023-04-18 | 2023-07-11 | 杰为软件系统(深圳)有限公司 | Discrete manufacturing system integration and scheduling method based on event arrangement |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114912814A (en) | Jobshop intelligent scheduling system based on digital twin technology | |
| CN108549977B (en) | Multi-Agent-based order-oriented flexible production dynamic scheduling system | |
| Arbel et al. | Performance evaluation of flexible manufacturing systems | |
| CN113177761B (en) | E-commerce storage intelligent scheduling early warning system considering timeliness | |
| CN109946965A (en) | A kind of Discrete Production Workshop scheduled production method based on improved multiple target Jaya algorithm | |
| CN101364108B (en) | Dynamic dispatching method for workshop working based on matter drive in complex large system environment | |
| CN105467953A (en) | Knowledge representation facing industrial big data and automation application method thereof | |
| CN101957954A (en) | Management and control optimizing method of discrete manufacture production | |
| EP3933744A1 (en) | Blockchain-based industrial manufacturing resource sharing method, device and system | |
| CN115600774A (en) | Multi-target production scheduling optimization method for assembly type building component production line | |
| CN115526482A (en) | Workshop scheduling and dynamic scheduling platform based on digital twin | |
| CN109409780B (en) | Change processing method, device, computer equipment and storage medium | |
| CN106327053B (en) | Construction method of weaving process recommendation model based on multi-mode set | |
| CN107330608A (en) | A kind of production scheduling method based on Techniques of Neural Network | |
| CN115098278B (en) | Digital twin workshop multi-scene interaction method based on microservice | |
| CN113052553A (en) | MES system control method and system for automobile synchronizer gear hub production line | |
| Xu et al. | Optimization of multi-stage production scheduling of automated production | |
| Bai et al. | An OEE improvement method based on TOC | |
| Rathinasamy | Sequencing and scheduling of nonuniform flow pattern in parallel hybrid flow shop | |
| Celik et al. | Impact of information sharing in hierarchical decision-making framework in manufacturing supply chains | |
| Seidmann et al. | Throughput maximization in flexible manufacturing systems | |
| CN118229018B (en) | Multi-resource constrained production logistics collaborative decision-making method and device, electronic device and storage medium | |
| Li et al. | A predictive maintenance method of series-parallel system based on condition monitoring | |
| CN118092288A (en) | Multi-workshop linkage system based on Internet of things | |
| CN117389231B (en) | MES/PCS integrated system of digital workshop |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |