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Equipment resource configuration optimization method based on knowledge graph driving

A technology of knowledge graph and resource allocation, applied in the field of optimal allocation of manufacturing resources, can solve the problems of insufficient and effective application, insufficient improvement of the efficiency of allocation of manufacturing resources, etc., to improve equipment utilization, enhance data processing capabilities, and reduce optimal allocation. cost effect

Active Publication Date: 2020-05-22
DONGHUA UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] The technical problem to be solved by the present invention is: due to the insufficient and effective application of knowledge-oriented production, the improvement of the efficiency of manufacturing resource allocation is insufficient

Method used

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  • Equipment resource configuration optimization method based on knowledge graph driving
  • Equipment resource configuration optimization method based on knowledge graph driving
  • Equipment resource configuration optimization method based on knowledge graph driving

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Embodiment Construction

[0035] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0036] refer to figure 1 and figure 2 The schematic diagram and detailed illustration of the knowledge map-driven optimal allocation of manufacturing resources shown in the diagram include the organization and generation of knowledge maps of manufacturing resources, involving knowledge modeling in the processing process and modeling of workshop processing equipment; The resource prediction matching method further expresses and...

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Abstract

The invention discloses an equipment resource configuration optimization method based on knowledge graph driving. The method comprises the steps that a knowledge graph of manufacturing resources is organized and generated, and machining process knowledge modeling and workshop machining equipment modeling are involved; the formed knowledge graph is subjected to a distributed representation learningand resource prediction matching method, and the relation between the knowledge graph and mining manufacturing resource implicit knowledge is further represented; when a processing order is issued, acandidate equipment set is constructed in combination with a fuzzy hierarchy method based on knowledge graph driving, and further the candidate equipment set is evaluated and screened through a community load model to complete reconstruction of the manufacturing unit; and finally, configuration optimization of an order task is completed by utilizing an optimization algorithm of the resource configuration mathematical model, an available processing equipment set link is formed, and a production process is guided. According to the method provided by the invention, the data processing capabilityis enhanced to a great extent, the equipment utilization rate and the equipment processing flexibility are improved, and meanwhile, the optimal configuration cost of manufacturing resources requiredby a processing task is also reduced through integrated knowledge reuse.

Description

technical field [0001] The invention relates to the field of optimal configuration of manufacturing resources, in particular to a method for optimizing configuration of equipment resources driven by knowledge graphs. Background technique [0002] Order insertion tasks and customized production have high requirements for quick response of resource allocation. The rational allocation of discrete manufacturing resources plays an important role in improving production efficiency. Among them, equipment configuration optimization (reasonable use of equipment, flexible combination of equipment) is one of the key research issues in a dynamic production environment. At present, in the current new product trial production process, the problems of discrete manufacturing resource allocation conflicts and response delays caused by order insertion are mainly solved by optimizing the processing resource model and algorithm. However, in the machining workshop, due to the variety of data t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/04G06F16/28G06F16/36
CPCG06Q10/04G06Q10/06393G06Q50/04G06F16/288G06F16/367Y02P90/30
Inventor 周彬鲍劲松张启万刘天元刘亚辉
Owner DONGHUA UNIV
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