Dynamic Scheduling Method Of Flexible Job Shop For Intelligent Factory

The manufacturing industry plays a pillar role in economic development.With the rise of intelligent manufacturing and the Internet of things,more and more emerging information technologies are involved in the upgrading and transformation of traditional factories.In the process of transformation to intelligent factories,manufacturing standards such as processing dynamics and accuracy are also improved accordingly,and the traditional flexible workshop scheduling mode seems to be stretched to guide workshop production.Especially when abnormal events such as equipment failure occur in the factory,it is impossible to quickly and dynamically adjust the manufacturing process in the workshop,so the research on the scheduling mode under the intelligent factory is beneficial to the transformation and upgrading of the manufacturing industry.the intelligent factory scheduling mode is to quickly give a scheduling method that meets the processing requirements according to the product processing requirements.Starting with the scheduling requirements of flexible job shop in intelligent factory,this paper analyzes the production scheduling mode and characteristics of flexible job shop in intelligent factory,and presents a dynamic scheduling method for flexible job shop in intelligent factory.First of all,this paper introduces the technical conditions needed for the transformation and upgrading of the traditional job shop scheduling mode to the intelligent factory scheduling mode,and analyzes the requirements of flexible job shop scheduling under the intelligent factory.this paper discusses how to realize the organic unity of information and manufacturing industry under the intelligent factory.Secondly,the optional processing equipment,processing time and processing sequence of transmission shaft parts in manufacturing workshop are recorded and analyzed.Simplified as a flexible job shop scheduling case,in view of the diversity of workshop information,workshop awareness is realized by pasting RFID changes on important materials and equipment in the workshop,and the models of simple events,label events and complex events are defined.Furthermore,a flexible job shop scheduling algorithm for intelligent factory is designed.On the basis of genetic algorithm(Genetic Algorithm,GA),variable neighborhood search(Variable Neighborhood Search,VNS)algorithm is used to establish the mutation interval and mutation rate of adaptive crossover and mutation operators,as well as three neighborhood structures based on VNS critical path.The disadvantage of slow convergence and easy to fall into local optimization in the early iterative stage of the algorithm is improved.GAVNS is used to do single-target and multi-objective tests on benchmark cases in Kacem and Brandimarte,and the performance superiority of GAVNS is verified by comparing with other similar algorithms.Finally,a flexible job shop rescheduling method considering machine failure probability is proposed to solve the problem that uncertain machine failure reduces the enforceability of the initial scheduling scheme.The event and cycle-driven strategy based on failure probability are adopted,a variety of rescheduling modes are comprehensively used,and the maximum completion time deviation,process start time cumulative deviation and process machine change are introduced as evaluation indexes.the scheduling scheme is solved by means of hybrid genetic algorithm with three key neighborhood structures of disjunctive graph transformation.Through the simulation analysis of the processed flexible job shop case,the superiority of the proposed rescheduling method to deal with machine fault disturbance under different conditions is verified..