Multi-Objective Optimization Method And Application For Low Carbon And Efficient Machining Process Planning

In recent years,the problem of global warming has become increasingly serious,and in order to actively respond to climate change,the manufacturing industry,which is one of the main sources of greenhouse gases,urgently needs to reduce energy consumption and carbon emissions.From the perspective of process planning,which is the key link of mechanical manufacturing process,this paper has carried out an in-depth study on the characteristics and quantitative model of carbon emission in the machining process of mechanical products,with low carbon emission as the optimization target while not reducing the machining efficiency.The main research contents are as follows:Firstly,taking machining process as the research object,the research boundary of carbon emission system,the carbon emission sources and the quantification coefficients of each carbon emission source are determined from the aspects of energy and materials.The influence of key factors in process planning on carbon emission of machining process is explored from several aspects,such as cutting amount,machining machine tool,machining tool,cutting fluid and machining sequence respectively.The basic knowledge related to carbon emission from the previous paper is integrated,and each carbon emission sources are converted in terms of machining stages of parts,and a quantitative model of carbon emission is constructed by considering several typical machining methods of turning,milling and drilling;on this basis,the main tasks of process planning are analyzed,the optimization of continuous process parameters and discrete process routes are carried out in stages,and corresponding optimization strategies are proposed respectively.Secondly,the time period characteristics of single machining element are analyzed and the machining time model is established based on it,integrate the carbon emission model and constraints,and take milling machining as an example,with milling speed,feed per tooth and milling depth as optimization variables,and construct a low-carbon efficient multi-objective optimization model for cutting parameters with constraints.In order to improve the search speed and accuracy of the PSO algorithm,dynamic inertia weight factor and penalty function were incorporated to improve the algorithm.The feasibility and effectiveness of the proposed cutting parameter optimisation model and the improved algorithm are verified by an example of milling a plane.Thirdly,the flexible characteristics of the process route are analyzed,and the constraint matrix is used to describe the machining order constraint relationship of machining elements;a multi-objective optimization model is established with the selection of machining machine and tools for each machining element and the sequence of machining as optimization variables,the minimum carbon emission and the shortest completion time of the whole process chain as optimization objectives;a three-stage coding method is used to describe the flexible process route,and the NSGA-II algorithm is improved with simulated annealing operation and constraint checking and correction methods to improve its optimization-seeking efficiency and ensure the feasibility of the solution;the proposed model and optimization method are proved to provide some reference for the low-carbon-efficient multi-objective optimization problem of the process route through machining examples.Finally,in order to improve the use value of machining-related data and the intelligence and digitalization of low-carbon optimization of machining process planning,a low-carbon-efficient machining process planning system is designed and developed based on the proposed model and method,and the structural framework and workflow of the system are analyzed,and the usage methods and pages of the system management,process parameter optimization,process route optimization and data management functional modules are introduced and demonstrated in detail.