Dynamic Multi-objective Flexible Job-shop Scheduling In Intelligent Manufacturing Environment

The contribution of manufacturing enterprises to the national economy has been recognized by the country,they are faced with many challenges,such as market globalization,economic changes,shortened product development cycle,changes in consumer demand and intensified competition.Time-to-market is particularly important in industries where manufacturing flexibility and process time determine the success rate of small and medium enterprises.Enterprises are required to carry out intelligent production planning and workshop scheduling to meet the delivery date and make quality decisions.With the development of intelligent manufacturing,the Internet of Things(IoT),cloud computing,big data,artificial intelligence and other new information technologies promote the development of cloud manufacturing,green manufacturing,service-oriented manufacturing and other new manufacturing models,which have greatly improved the production efficiency of the job shop.Intelligent manufacturing based on information physical system(CPS)is the development trend of manufacturing industry.Digital twinning is considered as an implementation of CPS.Considering the complexity and uncertainty of discrete manufacturing job shop,the intelligent decision and real-time scheduling of dynamic multi-objective job shop scheduling are two major challenges.By introducing digital twinning(DT),the physical workshop can be compared with the constantly updated digital workshop in real time,the dynamic event interference can be detected,and the rescheduling scheme can be triggered in time.Based on this,this paper studies the optimal scheduling problem of flexible job shop under the intelligent manufacturing environment,and establishes the study on the timely rescheduling of the twin shop to dynamic disturbance events,mainly including the following aspects:(1)Multi-objective Flexible Job-shop Scheduling Problem(MO-FJSP)was considered.First,the paper introduces the two subproblems of flexible shop scheduling:determine product each working procedure processing machine to choose and determine the machining sequence of machines working procedure and start processing time,considering the three typical optimization objectives and makespan,equipment and key equipment load energy consumption,building mathematical model for the flexible job shop scheduling and network disjunctive graph model.Aiming at this problem,combined with the strong global search ability of NSGA-Ⅲ and the ability of neighborhood search to search the solution space of the problem,a hybrid K-NSGA-zero algorithm based on the critical process and critical path neighborhood search was designed.Compared with the results of other intelligent algorithms,its efficiency and performance were outstanding in solving large and medium-sized problems through benchmark examples.Among all the tested methods,the Pareto solution occupies the largest proportion,and the Pareto solution has better spatial distribution.(2)Multi-objective Dynamic Flexible Job-shop Scheduling Problem(MO-DFJSP)was considered.First introduces intelligent manufacture environment of the new connotation of jobshop scheduling dynamic interference,interference issues affecting heavy workshop scheduling level can be divided into three categories to study(machining time extension,machine failure,emergency order insert),digital twin body dynamic scheduling model is constructed,set up shop scheduling method based on digital twin technology system,It includes intelligent realtime acquisition of scheduling data,rescheduling driving mechanism,intelligent scheduling decision and rescheduling scheme generation.Through the case study,the response ability of this method to dynamic events is greatly improved,and its contribution to delivery delay and energy consumption reduction is outstanding.This method can solve the problem that the scheduling time point is difficult to determine and reduce the scheduling cost by optimizing the rescheduling frequency.(3)Research on potential applications.In the production line of the manufacturing enterprise HN company as the background,establish intelligent digital twin job-shop manufacturing environment prototype system,carrying plant simulation twin body model,the simulation software to build digital to HN company production line processing eight parts and machine scheduling,for example,to verify the effectiveness of the proposed three kinds of dynamic interference event scheduling scheme is effective,The digital twin scheduling decision mechanism proposed in this paper is superior to the conventional scheduling rules in the three indexes of maximum completion time,total delay and total machine load.A 10 percent increase in machine utilization and a 1.5 unit reduction in average product delay time.