CN112633769A - Advanced plan scheduling system - Google Patents
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- 238000013439 planning Methods 0.000 claims abstract description 16
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- G06Q10/06311—Scheduling, planning or task assignment for a person or group
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Abstract
The invention discloses a high-level plan scheduling system, which comprises a data management analysis module, an intelligent plan scheduling module and a human-computer interaction module, wherein the data management analysis module is used for managing the data; the man-machine interaction module receives external MES system information, data management analysis module information and manually input information, stores the external MES system information and the manually input information into the data management analysis module, and the intelligent planning and scheduling module reads the information from the data management analysis module to make a scheduling scheme; and the intelligent plan scheduling module sends the formulated scheduling scheme to the human-computer interaction module and the data management analysis module to perform interface display and storage management of results. The invention quickly responds various production disturbance events in a dynamic production environment and efficiently finishes optimized scheduling by combining an automatic and manual adjustment mechanism and a bottleneck resource identification technology, thereby forming organic and ordered unified scheduling management on an electronic equipment digital workshop.
Description
Technical Field
The invention relates to the field of intelligent manufacturing, in particular to a high-level plan scheduling system.
Background
In the face of increasingly intense market competition environments, enterprises should be able to quickly respond to changes in production requirements, improve timeliness and efficiency of production planning under limited resource conditions, and enhance core competitiveness of the enterprises. The military electronic equipment digital industry belongs to the typical discrete manufacturing industry, a production workshop of the military electronic equipment digital industry has the characteristics of multiple varieties, small batch, mixed line production, more disturbance of production plan and the like, and the planning and scheduling of production operation are the core for coordinating resources and tasks of the workshop. The efficient planning and scheduling system is a technology for effectively planning production plans based on current resource constraints of enterprises and taking the minimum order delay amount, the highest equipment utilization rate and the like as optimization targets, and has important significance for meeting the flexible and customized production requirements of the enterprises, helping the enterprises plan, analyze, optimize and make decisions on resources, improving the informatization and intelligentization degree of enterprise operation and enhancing the market competitiveness of the enterprises.
The quick response manufacturing execution environment oriented to the multi-variety variable batch production mode has the characteristics of complexity and dynamics, and production disturbance from multiple aspects such as production plans, turnover processes, equipment materials and the like exists in the manufacturing execution. The operation plan generated by the mixed-line production operation scheduling algorithm is optimized, and the reasonability of the plan level is only ensured, because of the dynamic property of the manufacturing execution process, a large number of disturbance factors such as production time/sequence change, equipment failure, production preparation, order change and the like exist, and the operation plan cannot truly reflect the actual production field situation due to the production disturbance. If these disturbance events are left alone, the operation plan will be disconnected from the production and manufacturing execution site, so that the guiding meaning of the operation plan is greatly lost. Therefore, the job plan solution must be updated in response to the disturbance event.
Meanwhile, the bottleneck resource is a key factor restricting the manufacturing execution process, which means that the actual production capacity of the bottleneck resource cannot meet the requirement, and may be high-precision equipment, professional technicians or even specialized tools, the bottleneck resource is one of important factors causing overstock of the products in production and even stopping of the production process, the bottleneck resource must be identified in order to improve the overall output of the system, and the utilization rate of the bottleneck resource is improved through a reasonable optimization algorithm.
Therefore, it is an urgent need in the art to develop a high-level planning and scheduling system for discrete manufacturing industry, which takes timely response of dynamic disturbance events and diagnosis of bottleneck resources as key technologies.
Disclosure of Invention
In order to solve the problems, the invention provides a high-level plan scheduling system, which comprises a data management analysis module, an intelligent plan scheduling module and a human-computer interaction module; the man-machine interaction module receives external MES system information, data management analysis module information and manually input information, stores the external MES system information and the manually input information into the data management analysis module, and the intelligent planning and scheduling module reads the information from the data management analysis module to make a scheduling scheme; and the intelligent plan scheduling module sends the formulated scheduling scheme to the human-computer interaction module and the data management analysis module to perform interface display and storage management of results.
The preparation of the scheduling scheme comprises the following steps:
manufacturing resource information, order information and process route information are obtained from the data management analysis module through the man-machine interaction module;
acquiring historical operating data from a data management and analysis module through a human-computer interaction module, wherein the historical operating data comprises personnel resources, equipment resources, material resources, environmental resources and measurement information, establishing a time sequence model among the personnel resources, the equipment resources, the material resources, the environmental resources and the measurement information, analyzing the utilization rate and the problem occurrence rate of various resources changing along with time, and judging the occurrence mode of bottleneck resources by using a cluster analysis method, wherein the occurrence mode of the bottleneck resources comprises insufficient capacity of specific equipment and high failure rate of key devices;
establishing a mapping relation between process route information and manufacturing resource information on the basis of the generation modes of the manufacturing resource information, the order information, the process route information and the bottleneck resource, determining the priority of an order according to the difference of the order information, forming a coupling associated constraint model by taking the shortest completion time of the order or the maximum utilization rate of the resource as a target, and generating a scheduling scheme;
updating the scheduling scheme by adopting a classification modularization method according to production disturbance information from a human-computer interaction module; the production disturbance events comprise disturbance events generated when a production field executes, disturbance events generated due to order change, disturbance events generated due to equipment state or capacity scheduling adjustment and disturbance events generated when a job is prepared;
and acquiring new order information through the man-machine interaction module, updating the manufacturing resource information according to the new order information, and updating the scheduling scheme.
Further, the data management analysis module carries out statistical analysis on the scheduling result according to the historical operating data and sends the scheduling result to the human-computer interaction module; the information stored by the data management analysis module comprises: historical operating data, production disturbance information.
Furthermore, the human-computer interaction module comprises an information instruction integration interface and a scheduling result display interface, the instruction integration interface completes information interaction between the data management analysis system and the intelligent scheduling system, and the scheduling result display interface displays the scheduling scheme.
Compared with the prior art, the invention has the following beneficial effects:
the invention solves the problem that the production plan scheduling capability is insufficient under the influence of multiple varieties, variable batches, dynamic disturbance and bottleneck resources in the field of discrete manufacturing industry; by combining an automatic and manual adjustment mechanism and a bottleneck resource identification technology, various production disturbance events in a dynamic production environment are quickly responded, and optimized scheduling is efficiently completed, so that organic and ordered unified scheduling management of an electronic equipment digital workshop is formed.
Drawings
Fig. 1 is a schematic diagram of a system configuration in embodiment 1 of the present invention.
Fig. 2 is a schematic diagram of information flow of a system workflow according to embodiment 1 of the present invention.
Detailed Description
The present invention is described in further detail below with reference to the attached drawing figures.
In this disclosure, aspects of the present invention are described with reference to the accompanying drawings, in which a number of illustrative embodiments are shown. It should be appreciated that the various concepts and embodiments described above, as well as those described in greater detail below, may be implemented in any of numerous ways, as the disclosed concepts and embodiments are not limited to any one implementation. In addition, some aspects of the present disclosure may be used alone, or in any suitable combination with other aspects of the present disclosure.
Example 1:
as shown in fig. 1, the advanced planning and scheduling system according to this embodiment includes a data management analysis module, an intelligent planning and scheduling module, and a human-computer interaction module; the man-machine interaction module receives information of an external MES (Manufacturing Execution System), information of the data management analysis module and manually input information, stores the external MES information and the manually input information into the data management analysis module, and the intelligent planning and scheduling module reads the information from the data management analysis module to make a scheduling scheme; and the intelligent plan scheduling module sends the formulated scheduling scheme to the human-computer interaction module and the data management analysis module to perform interface display and storage management of results. The three modules realize flexible interaction, and form the integrated functions of dynamic input, intelligent scheduling and dynamic display.
The data management analysis module carries out statistical analysis on the scheduling result according to the historical operating data and sends the scheduling result to the man-machine interaction module; the information stored by the data management analysis module comprises: historical operating data, production disturbance information.
The human-computer interaction module comprises an information instruction integration interface and a scheduling result display interface, the instruction integration interface completes information interaction between the data management analysis system and the intelligent scheduling system, and the scheduling result display interface displays the scheduling scheme.
As shown in fig. 2, the preparation of the scheduling scheme includes the following steps:
1) for the arrangement of a workshop operation plan, the intelligent plan scheduling module acquires manufacturing resource information, order information and process route information, namely a data interface 1, from the data management analysis module through an instruction integration interface of the human-computer interaction module;
the intelligent planning and scheduling module acquires historical operating data from the data management and analysis module through an instruction integration interface (a data interface '2' in fig. 2) of the human-computer interaction module, the historical operating data comprises personnel resources, equipment resources, material resources, environment resources and measurement information, a time series model among the personnel resources, the equipment resources, the material resources, the environment resources and the measurement information is established, the utilization rate and the problem occurrence rate of various resources changing along with time are analyzed, a cluster analysis method is utilized to judge the occurrence mode of bottleneck resources, and the occurrence mode of the bottleneck resources comprises that the specific equipment has insufficient capacity and the failure rate of key devices is high;
establishing a mapping relation between process route information and manufacturing resource information on the basis of the generation modes of the manufacturing resource information, order information, the process route information and bottleneck resources, determining the priority of an order according to the difference of the order information, forming a coupled and associated constraint model by taking the shortest completion time of the order or the maximum utilization rate of the resources as a target, generating a scheduling scheme, and sending the scheduling scheme to a human-computer interaction module for displaying through a data interface 3 in the figure 2;
updating the scheduling scheme by adopting a classification modularization method according to the production disturbance information from the human-computer interaction module (through a data interface '4' in the figure 2); the production disturbance events comprise disturbance events generated when a production field executes, disturbance events generated due to order change, disturbance events generated due to equipment state or capacity scheduling adjustment and disturbance events generated when a job is prepared;
and acquiring new order information from an external MES system through a human-computer interaction module (a data interface '7' in the figure 2), updating the manufacturing resource information according to the new order information, updating a scheduling scheme (an interface '5' in the figure 2), and feeding back the updated scheduling scheme to the human-computer interaction module through a data interface '6' in the figure 2.
In summary, the invention constructs a high-level planning and scheduling system for a multi-variety and small-batch electronic equipment digital workshop, and solves the problem of insufficient production planning and scheduling capability under the influence of multi-variety, variable-batch, dynamic disturbance and bottleneck resources in the field of discrete manufacturing industry; through a mechanism combining automatic adjustment and manual adjustment and a bottleneck resource identification technology, various production disturbance events in a dynamic production environment are quickly responded, and optimized scheduling is efficiently completed, so that organic and orderly unified scheduling management of an electronic equipment digital workshop is formed.
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 fall within the spirit and principle of the present invention are intended to be included therein.
Claims (3)
1. A high-level plan scheduling system is characterized by comprising a data management analysis module, an intelligent plan scheduling module and a human-computer interaction module; the man-machine interaction module receives external MES system information, data management analysis module information and manually input information, stores the external MES system information and the manually input information into the data management analysis module, and the intelligent planning and scheduling module reads the information from the data management analysis module to make a scheduling scheme; the intelligent plan scheduling module sends the formulated scheduling scheme to the human-computer interaction module and the data management analysis module to perform interface display and storage management of results;
the preparation of the scheduling scheme comprises the following steps:
manufacturing resource information, order information and process route information are obtained from the data management analysis module through the man-machine interaction module;
acquiring historical operating data from a data management and analysis module through a human-computer interaction module, wherein the historical operating data comprises personnel resources, equipment resources, material resources, environmental resources and measurement information, establishing a time sequence model among the personnel resources, the equipment resources, the material resources, the environmental resources and the measurement information, analyzing the utilization rate and the problem occurrence rate of various resources changing along with time, and judging the occurrence mode of bottleneck resources by using a cluster analysis method, wherein the occurrence mode of the bottleneck resources comprises insufficient capacity of specific equipment and high failure rate of key devices;
establishing a mapping relation between process route information and manufacturing resource information on the basis of the generation modes of the manufacturing resource information, the order information, the process route information and the bottleneck resource, determining the priority of an order according to the difference of the order information, forming a coupling associated constraint model by taking the shortest completion time of the order or the maximum utilization rate of the resource as a target, and generating a scheduling scheme;
updating the scheduling scheme by adopting a classification modularization method according to production disturbance information from a human-computer interaction module; the production disturbance events comprise disturbance events generated when a production field executes, disturbance events generated due to order change, disturbance events generated due to equipment state or capacity scheduling adjustment and disturbance events generated when a job is prepared;
and acquiring new order information through the man-machine interaction module, updating the manufacturing resource information according to the new order information, and updating the scheduling scheme.
2. The advanced planning scheduling system of claim 1 wherein the data management analysis module performs statistical analysis on scheduling results according to historical operating data and sends the scheduling results to the human-computer interaction module; the information stored by the data management analysis module comprises: historical operating data, production disturbance information.
3. The advanced planning scheduling system of claim 2 wherein the human-computer interaction module comprises an information instruction integration interface and a scheduling result display interface, the instruction integration interface performs information interaction between the data management analysis system and the intelligent scheduling system, and the scheduling result display interface displays the scheduling plan.
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| CN113298349A (en) * | 2021-04-25 | 2021-08-24 | 阿里巴巴（中国）有限公司 | Order processing method, equipment and storage medium |
| CN113869966A (en) * | 2021-08-25 | 2021-12-31 | 青岛理工大学 | Clothing personalized customization method and system |
| CN114186779A (en) * | 2021-11-03 | 2022-03-15 | 北京科技大学 | Dynamic scheduling method and system for multi-model small-batch production line |
| CN115099656A (en) * | 2022-07-05 | 2022-09-23 | 上海交通大学 | Marine engineering segmented intelligent scheduling system architecture and scheduling algorithm based on simulation optimization |
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