Collaborative navigation optimization method for fixed type assembling processes

Abstract

The invention brings forward a collaborative navigation optimization method for fixed type assembling processes. Internet-of-Things technologies are applied to all assembling resources on a base layer, an Internet-of-Things sensing network is built in an assembling workshop, all assembling units and assembling workers are interconnected via a local area network, and real time sharing of manufacture resource information can be realized. Modeling of assembling processes is conducted via hierarchy colored Petri net technologies, the assembling processes are subjected to dynamic priority ranking based on combination of an analytic hierarchy process and a grey correlation matrix, and an optimal matching solution for high priority processes and the assembling workers can be calculated. The collaborative navigation optimization method is based on Internet-of-Things manufacture technologies, optimization is conducted from an angle of the assembling workers, and a strategy for collaborative optimization among the workers can be sought. A defect that real time information is hard to share among all assembling units and a dynamic optimization dispatching solution is hard to carry out via useof a conventional fixed type assembling optimization method can be prevented. Via real time optimal matching, influence exerted on a whole assembling system by local exceptions in assembling processescan be reduced fundamentally.

Description

technical field [0001] The invention relates to the technical field of optimization of assembly systems in manufacturing workshops, in particular to a collaborative navigation optimization method for fixed assembly processes. Background technique [0002] As the competition in the global market continues to intensify, manufacturing companies need to respond quickly to various changes in the market. Reducing planning time in the assembly process is a key factor enabling manufacturing companies to remain competitive. However, in the traditional workshop assembly process, due to the lack of real-time information sharing between assembly units and assembly workers, and the frequent changes in production plans, these factors will lead to low efficiency of the assembly execution system and poor assembly process turnover. Occurrence of serious abnormal problems. [0003] The existing assembly optimization system mainly optimizes the allocation from the perspective of the process,...

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Problems solved by technology

[0007] The above research and inventions have greatly promoted the research and development of collaborative optimization methods for fixed assembly processes. However, when faced with the assembly of large and complex products with fixed layouts, it is necessary to improve the real-time optimization of manufacturing enterprises in the assembly process. In terms of level, there are still the following problems: 1) The complex product assembly process consists of dozens or even more processes. Due to the many tasks and assembly workers involved in the product assembly process, it is difficult to optimize from the perspective of the assembly process. Long time and other issues are not conducive to the implementation of dynamic optimization results; 2) The traditional fixed assembly system lacks a mechanism that can respond quickly to abnormalities and guide the assembly workers in real time; 3) Considering that each assembly worker has There are multiple assembly process execution capabilities. In the assembly process, there is a lack of a task optimization and push model to provide real-time task guidance to assembly workers.

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