Research On Multi-objective Integrated Process Planning And Scheduling Problems For Low-carbon Manufacturin

The manufacturing industry is the foundation of the country and the foundation of the strong country.The stable and positive situation of the Chinese economy cannot be achieved without the development of the manufacturing industry.However,while the Chinese manufacturing industry has made great contributions to the economy,it also consumes a lot of energy and produces huge carbon emissions.From industrial civilization to ecological civilization is the inevitable trend of social development,and it is imperative for manufacturing industry to realize green manufacturing.As an important part of manufacturing system,process planning and shop scheduling are often carried out step by step in the production process,so the integrated optimization can tap the potential of energy saving and emission reduction.Aiming at the integrated process planning and scheduling problem,this paper will study the multi-objective green IPPS problem by taking carbon emission as the evaluation index.The main research contents are as follows:Firstly,the three main process planning and scheduling integration methods are described and analyzed,the nonlinear process planning integrated scheduling model is selected as the research method for solving the IPPS problem in this paper,and the solution algorithm is summarized and improved accordingly,the basic theory of standard particle swarm optimization is introduced,and a hybrid discrete particle swarm optimization(HDPSO)is designed The algorithm retains the core idea of particle swarm algorithm,optimizes the flight formula of particles,and adds a simulated annealing mechanism to prevent particle swarms from falling into the local optimal solution during flight.Secondly,the low-carbon flexible process planning problem is solved,and the influencing factors of carbon emissions and processing time in the processing process are analyzed,and the carbon emissions in the processing process are divided into machine tool carbon emissions,carbon emissions generated by cutting fluid and transfer carbon emissions,and the processing time is divided into the processing time of the workpiece and the transfer time of the machine,and a low-carbon process planning optimization model is established by minimizing the total carbon emission and minimizing the total processing time as the objective function.The NSGA-II algorithm based on fast nondominated ordering is used to solve the model,and the case of the front brake adjustment arm of the automobile is designed,which verifies the effectiveness of the model.Solve the shop floor scheduling stage of the IPPS problem.In this paper,the influencing factors of carbon emissions in the process of workshop scheduling are quantitatively analyzed,and a low-carbon scheduling optimization model is established with the objective function of minimizing the maximum completion time,minimizing the total delay time and minimizing the total carbon emissions.Based on the solution of the optimal solution of the process planning stage of the multi-objective IPPS problem obtained by the previous method,the hybrid discrete particle swarm algorithm proposed in this paper is used to solve the workshop scheduling stage,and the two are integrated and optimized according to the nonlinear process planning integrated scheduling model.Finally,taking the pipe clamp as a case,including four component parts and seven processing machine tools,the low-carbon process planning and scheduling integration problem is solved,the effectiveness of the model and the improved algorithm is verified,and the TOPSIS method based on the entropy weight method is used to sort and decide the optimal solution for the solved solution set,which provides a basis for the decision-making of the IPPS scheme in actual production.