CN113159593A - Intelligent scheduling system based on big data calculation and analysis - Google Patents
Intelligent scheduling system based on big data calculation and analysis Download PDFInfo
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- CN113159593A CN113159593A CN202110462679.6A CN202110462679A CN113159593A CN 113159593 A CN113159593 A CN 113159593A CN 202110462679 A CN202110462679 A CN 202110462679A CN 113159593 A CN113159593 A CN 113159593A
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- 238000004364 calculation method Methods 0.000 title claims abstract description 16
- 238000004519 manufacturing process Methods 0.000 claims abstract description 93
- 230000003993 interaction Effects 0.000 claims abstract description 18
- 238000013439 planning Methods 0.000 claims abstract description 16
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- 230000008569 process Effects 0.000 claims abstract description 6
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
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- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06316—Sequencing of tasks or work
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- G—PHYSICS
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- 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
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Abstract
The invention discloses an intelligent scheduling system based on big data calculation and analysis, in particular to the field of intelligent scheduling of production and processing processes, which comprises an interaction module, a scheduling module and a scheduling module, wherein the interaction module is used for providing an interaction platform for a user, displaying the running state of the system and receiving the operation instruction of the user; the APS module is used for receiving the order and realizing the planned scheduling of the order execution process according to the operation instruction and the data of the planned execution module; the database module is used for storing unfinished order information and finished order information; and the scheduling planning module is used for planning and scheduling according to the orders submitted by the APS module. The invention stores unfinished orders through the task pool, intelligently schedules the unfinished orders through the priority decision module, and carries out abnormity early warning on the scheduled production plan, thereby avoiding the production plan from outputting actual production capacity, and simultaneously comparing the construction period and the delivery date of the production plan, avoiding overdue, and further carrying out optimal scheduling on the production plan.
Description
Technical Field
The invention relates to the technical field of intelligent scheduling of production and processing processes, in particular to an intelligent scheduling system based on big data calculation and analysis.
Background
The workshop is a basic unit for the internal organization production of the enterprise and is also a first-level organization for the production administration management of the enterprise. Consisting of several sections or production teams. The system is set according to the professional properties of each stage of product production or each component of the product in an enterprise and the professional properties of each auxiliary production activity, and has a factory building or a field, machine equipment, tools, certain production personnel, technical personnel and management personnel which are necessary for completing production tasks.
The workshop is a place for product production and processing, and under the background of 'Internet + manufacturing', an enterprise production mode gradually develops towards the direction of multi-variety and personalized customization, so that the workshop is more and more intelligent, and the scheduling of a production plan is easily disordered in the production process of a product, so that an order is often overtime and cannot be delivered, and therefore an intelligent scheduling system based on big data calculation and analysis is provided.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide an intelligent scheduling system based on big data calculation and analysis, so as to solve the above-mentioned problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: an intelligent scheduling system based on big data calculation and analysis, comprising:
the interaction module is used for providing an interaction platform for a user, displaying the running state of the system and receiving an operation instruction of the user;
the APS module is used for receiving the order and realizing the planned scheduling of the order execution process according to the operation instruction and the data of the planned execution module;
the database module is used for storing unfinished order information and finished order information;
the scheduling planning module is used for planning and scheduling according to the order submitted by the APS module;
and the plan execution module is used for carrying out production processing according to the plan schedule formulated by the schedule plan module.
Further, the database module comprises a task pool and a resource pool;
the task pool is used for storing unfinished order information;
and the resource pool is used for storing historical data, and the historical data records production related data of completed orders.
Further, the scheduling plan module comprises a production plan generating module, a priority decision module and a production plan updating module;
the production plan generating module is used for acquiring the unfinished order information of the task pool and generating a production plan and various elements in the production plan according to the unfinished order information;
the priority decision module is used for acquiring the production plan generated by the production plan generation module and various elements in the production plan and arranging an execution sequence for each production plan according to a priority division rule;
and the production plan updating module is used for updating the production plan reordered by the priority decision module.
Furthermore, the scheduling planning module further comprises an anomaly early warning module, which is arranged between the priority decision module and the production plan updating module and is used for carrying out anomaly early warning on the scheduling plan given by the priority decision module and resending the scheduling plan giving out early warning to the priority decision module for carrying out scheduling again.
Further, the abnormity early warning module comprises an overrun early warning module and an overrun early warning module;
the overrun early warning module is used for calculating the plan scheduling given by the priority decision module by combining the actual production capacity of the plan execution module, and sending an early warning instruction to related personnel when the production capacity of the plan execution module required by the plan scheduling is greater than the actual production capacity of the plan execution module;
and the overdue early warning module is used for calculating according to the scheduling and delivery time in the order information given by the priority decision module, and sending an early warning instruction to related personnel when the scheduling is overdue.
The system further comprises a pushing module, which is used for transmitting the production progress information such as order completion prompt information, order pause production information, order recovery production information and the like to related personnel.
Furthermore, the interaction module builds a human-computer interaction interface, and the human-computer interaction interface is a web page and is used for providing an interface program for connecting the mobile phone APP or the special windowing management software with the dynamic planning and scheduling system.
Further, the production plan updating module is further configured to transmit the updated production plan to the priority decision module, so that when the order module receives a new order, the priority decision module rearranges the execution order of each production plan.
The invention has the technical effects and advantages that:
compared with the prior art, the invention stores unfinished orders through the task pool, intelligently schedules the unfinished orders through the priority decision module, performs abnormity early warning on the scheduled production plan, avoids the production plan from producing actual production capacity, and simultaneously compares the construction period and the delivery date of the production plan, avoids overdue, thereby optimally scheduling the production plan.
Drawings
FIG. 1 is an overall system block diagram of the present invention.
FIG. 2 is a system block diagram of the database module of the present invention.
FIG. 3 is a system diagram of a scheduling planning module according to the present invention.
FIG. 4 is a system block diagram of the anomaly early warning module of the present invention.
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.
1-4, an intelligent scheduling system based on big data calculation and analysis, comprising:
the interaction module is used for providing an interaction platform for a user, displaying the running state of the system and receiving an operation instruction of the user;
the APS module is used for receiving the order and realizing the planned scheduling of the order execution process according to the operation instruction and the data of the plan execution module;
the database module is used for storing unfinished order information and finished order information;
the scheduling planning module is used for planning and scheduling according to the order submitted by the APS module;
and the plan execution module is used for carrying out production processing according to the plan schedule formulated by the schedule plan module.
In a preferred embodiment, the database module comprises a task pool and a resource pool;
the task pool is used for storing unfinished order information;
and the resource pool is used for storing historical data, and the historical data records production related data of completed orders.
In a preferred embodiment, the scheduling plan module includes a production plan generating module, a priority decision module, and a production plan updating module;
the production plan generating module is used for acquiring the unfinished order information of the task pool and generating a production plan and various elements in the production plan according to the unfinished order information;
the priority decision module is used for acquiring the production plan generated by the production plan generation module and various elements in the production plan and arranging an execution sequence for each production plan according to a priority division rule;
and the production plan updating module is used for updating the production plan reordered by the priority decision module.
In a preferred embodiment, the scheduling planning module further includes an anomaly early warning module, which is disposed between the priority decision module and the production plan updating module, and is configured to perform anomaly early warning on the scheduling schedule given by the priority decision module, and resend the scheduling schedule giving an early warning to the priority decision module for rerouting the scheduling schedule.
In a preferred embodiment, the abnormity early warning module comprises an overrun early warning module and an overrun early warning module;
the overrun early warning module is used for calculating the plan scheduling given by the priority decision module by combining the actual production capacity of the plan execution module, and sending an early warning instruction to related personnel when the production capacity of the plan execution module required by the plan scheduling is greater than the actual production capacity of the plan execution module;
and the overdue early warning module is used for calculating according to the scheduling and delivery time in the order information given by the priority decision module, and sending an early warning instruction to related personnel when the scheduling is overdue.
In a preferred embodiment, the system further comprises a pushing module, which is used for transmitting production progress information such as order completion prompting information, order production suspension information, order production resumption information and the like to related personnel.
In a preferred embodiment, the interaction module is built with a human-computer interaction interface, and the human-computer interaction interface is a web page and is used for providing an interface program for connecting the mobile phone APP or the special windowing management software with the dynamic planning and scheduling system.
In a preferred embodiment, the production plan updating module is further configured to transmit the updated production plan to the priority decision module, so that when the order module receives a new order, the priority decision module reschedules the execution order of the production plans.
The points to be finally explained are: first, in the description of the present application, it should be noted that, unless otherwise specified and limited, the terms "mounted," "connected," and "connected" should be understood broadly, and may be a mechanical connection or an electrical connection, or a communication between two elements, and may be a direct connection, and "upper," "lower," "left," and "right" are only used to indicate a relative positional relationship, and when the absolute position of the object to be described is changed, the relative positional relationship may be changed;
secondly, the method comprises the following steps: in the drawings of the disclosed embodiments of the invention, only the structures related to the disclosed embodiments are referred to, other structures can refer to common designs, and the same embodiment and different embodiments of the invention can be combined with each other without conflict;
and finally: the above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that are within the spirit and principle of the present invention are intended to be included in the scope of the present invention.
Claims (8)
1. An intelligent scheduling system based on big data calculation and analysis, comprising:
the interaction module is used for providing an interaction platform for a user, displaying the running state of the system and receiving an operation instruction of the user;
the APS module is used for receiving the order and realizing the planned scheduling of the order execution process according to the operation instruction and the data of the planned execution module;
the database module is used for storing unfinished order information and finished order information;
the scheduling planning module is used for planning and scheduling according to the order submitted by the APS module;
and the plan execution module is used for carrying out production processing according to the plan schedule formulated by the schedule plan module.
2. The intelligent scheduling system based on big data calculation and analysis of claim 1, wherein: the database module comprises a task pool and a resource pool;
the task pool is used for storing unfinished order information;
and the resource pool is used for storing historical data, and the historical data records production related data of completed orders.
3. The intelligent scheduling system based on big data calculation and analysis as claimed in claim 2, wherein: the scheduling plan module comprises a production plan generating module, a priority decision module and a production plan updating module;
the production plan generating module is used for acquiring the unfinished order information of the task pool and generating a production plan and various elements in the production plan according to the unfinished order information;
the priority decision module is used for acquiring the production plan generated by the production plan generation module and various elements in the production plan and arranging an execution sequence for each production plan according to a priority division rule;
and the production plan updating module is used for updating the production plan reordered by the priority decision module.
4. The intelligent scheduling system based on big data calculation and analysis of claim 3, wherein: the scheduling planning module also comprises an abnormity early warning module which is arranged between the priority decision module and the production plan updating module and used for carrying out abnormity early warning on the planned scheduling given by the priority decision module and resending the planned scheduling giving out early warning to the priority decision module for carrying out planning scheduling again.
5. The intelligent scheduling system based on big data calculation and analysis of claim 4, wherein: the abnormity early warning module comprises an overrun early warning module and an overrun early warning module;
the overrun early warning module is used for calculating the plan scheduling given by the priority decision module by combining the actual production capacity of the plan execution module, and sending an early warning instruction to related personnel when the production capacity of the plan execution module required by the plan scheduling is greater than the actual production capacity of the plan execution module;
and the overdue early warning module is used for calculating according to the scheduling and delivery time in the order information given by the priority decision module, and sending an early warning instruction to related personnel when the scheduling is overdue.
6. The intelligent scheduling system based on big data calculation and analysis of claim 1, wherein: the system also comprises a pushing module used for transmitting the production progress information such as order completion prompt information, order production suspension information, order production recovery information and the like to related personnel.
7. The intelligent scheduling system based on big data calculation and analysis of claim 1, wherein: and the interaction module is built with a human-computer interaction interface, and the human-computer interaction interface is a web page and is used for providing an interface program for connecting a mobile phone APP or special windowing management software with a dynamic planning and scheduling system.
8. The intelligent scheduling system based on big data calculation and analysis of claim 3, wherein: the production plan updating module is further configured to transmit the updated production plan to the priority decision module, so that when the order module receives a new order, the priority decision module rearranges the execution order of each production plan.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114298528A (en) * | 2021-12-24 | 2022-04-08 | 苏州浪潮智能科技有限公司 | Auxiliary balancing method, system and device for scheduling and delivering period of orders of multiple production lines |
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| CN106251084A (en) * | 2016-08-09 | 2016-12-21 | 武汉益模科技股份有限公司 | A kind of production schedule used based on computer software performs management system and method |
| CN107844892A (en) * | 2017-09-29 | 2018-03-27 | 深圳供电局有限公司 | A kind of equipment O＆M plan Dynamic Scheduling system and optimization method |
| CN108985711A (en) * | 2018-06-29 | 2018-12-11 | 北京仿真中心 | A kind of intelligent plant dynamic planning scheduling system |
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2021
- 2021-04-28 CN CN202110462679.6A patent/CN113159593A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4866628A (en) * | 1987-12-18 | 1989-09-12 | International Business Machines Corp. | Automated production dispatch system with feedback control |
| CN106251084A (en) * | 2016-08-09 | 2016-12-21 | 武汉益模科技股份有限公司 | A kind of production schedule used based on computer software performs management system and method |
| CN107844892A (en) * | 2017-09-29 | 2018-03-27 | 深圳供电局有限公司 | A kind of equipment O＆M plan Dynamic Scheduling system and optimization method |
| CN108985711A (en) * | 2018-06-29 | 2018-12-11 | 北京仿真中心 | A kind of intelligent plant dynamic planning scheduling system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114298528A (en) * | 2021-12-24 | 2022-04-08 | 苏州浪潮智能科技有限公司 | Auxiliary balancing method, system and device for scheduling and delivering period of orders of multiple production lines |
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