Multi-Equipment Work Centers For Intelligent Manufacturing And MTO Requirements Scheduling And Optimization Methods

With the increasing market competition and the concept of smart factory,the traditional production scheduling method is gradually developed into multi-equipment work center scheduling for smart manufacturing and MTO requirements.And this type of scheduling can be borrowed from Hybrid Flow Shop Scheduling(HFSP)and optimization method.HFSP is a combination of flow shop scheduling and parallel machine scheduling,which is a typical NP-hard problem and widely exists in the actual production of manufacturing industry.In this paper,the optimization method of HFSP is used as an entry point to study the zeroidle multi-equipment work center scheduling problem,and the solution method is designed based on the framework of genetic algorithm.First,for the single-objective multi-equipment work center scheduling problem,a mathematical model considering setup time and handling time is established,and GA1-VNS based on genetic algorithm and variable neighborhood search algorithm is proposed with the optimization objective of minimizing the maximum completion time;GA1-VNS adopts the encoding method of permutation and global rules,introduces POX and LOX crossover operators,improves the variation strategy,and uses The effectiveness of GA1-VNS in solving the singleobjective multi-equipment work-center scheduling problem is demonstrated by testing the standard set of arithmetic cases,performance improvement experiments and algorithm comparison experiments.Secondly,for the multi-objective multi-equipment work center scheduling problem,a mathematical model considering setup time and handling time is established,and NSGA-II-V based on non-dominated sorting genetic algorithm and variable neighborhood search algorithm is proposed with the optimization objective of minimizing the maximum completion time and the number of handling times;based on multiobjective scheduling theory,fast non-dominated sorting and crowding degree operators are introduced to find the Pareto optimal solution set;the advantages of NSGA-II-V for solving the multi-objective multi-equipment work center scheduling problem are demonstrated through experiments such as algorithm comparison and performance improvement tests.Then,for the multi-objective dynamic multi-equipment work-center scheduling problem,equipment failure and emergency order insertion models are developed with the objectives of production cycle time,handling times,system stability and system robustness;NSGA-II-V is used to solve the multi-objective dynamic multi-equipment work-center scheduling problem,and the proposed model and algorithm are verified by solving the arithmetic cases of random moment failure as well as random moment order insertion in The effectiveness and efficiency of the proposed model and algorithm in handling dynamic events are verified.Finally,a multi-equipment work-center scheduling system for smart manufacturing and MTO requirements is constructed to summarize the whole paper and provide an outlook on future research.