Research On Flexible Job Shop Scheduling Optimization Of R Company For Energy Saving

The increasingly severe environmental crisis and energy problems have prompted the traditional manufacturing industry to transform its production processes in the direction of high efficiency and low energy consumption.On the other hand,the fast-changing market demand forces manufacturing enterprises to develop towards a multi-variety,small-lot production model.This customer demand-centered production model places higher demands on the production flexibility of manufacturing enterprises.Process planning and workshop scheduling are key aspects of the manufacturing process and are two important ways to improve the efficiency of manufacturing systems and reduce energy consumption.In traditional manufacturing industries,process planning and workshop scheduling are carried out separately and sequentially,i.e.workshop scheduling optimization is carried out only after process planning is completed,ignoring the intrinsic connection between process planning and workshop scheduling,which easily causes resource conflicts and inefficiencies in the workshop scheduling process.Therefore,this paper takes the flexible job shop scheduling problem of R’s machining workshop as the research object,and enhances the ability of optimal scheduling of machining shop from the perspective of integrating process planning and shop scheduling,to achieve the purpose of improving production efficiency and reducing machining energy consumption.The main research work of this paper is as follows.(1)After analyzing the current situation of machining workshop scheduling in Company R,an integrated optimization model of process planning and workshop scheduling is constructed with the optimization objectives of minimizing the maximum completion time and total energy consumption of the machining process,and the process route and machining sequence of the workpiece,as well as the machine allocation and machining gear selection of each process,are comprehensively optimized.(2)Based on the standard grey wolf algorithm,an improved multi-objective grey wolf algorithm is designed to solve the optimization problem of process planning and workshop scheduling integration,including improving the coding method,population-level determination method,and population update method of the grey wolf algorithm,and designing three different scale cases to verify the effectiveness of the improved multiobjective grey wolf algorithm.(3)The improved multi-objective grey wolf algorithm is used to solve the scheduling example of the machining workshop of company R.The Pareto non-dominated solution set is obtained and the entropy-weight-TOPSIS method is used to evaluate the Pareto nondominated solution set to obtain the best scheduling solution.A detailed comparison between the current scheduling solution and the best scheduling solution is then carried out in terms of maximum completion time and total energy consumption of the process to demonstrate the superiority of the best scheduling solution.