Optimization Of Idle Tool Path In Multi-Feature Machining Of Urban Rail Chassis

In recent years,the fast-growing economy promotes the expansion of urban scale,and the congestion of urban traffic leads to the increasing desire of the public for public transportation,and the most loaded,most frequent,and punctual public transportation in the city is the subway,which corresponds to the increasing orders of subway manufacturing,and its production capacity faces a huge challenge under the condition that the production efficiency of CNR remains unchanged.The subframe of the city rail is one of the important parts of the subway.Its huge area makes each production take a lot of time,which seriously hinders the manufacturing progress of the subway.The rapid rise of the digital economy has led to its penetration and integration into various fields.The digital reform and development of the manufacturing industry have provided a feasible path for the in-depth study of the urban rail underframe processing route problem,therefore,the optimization of the urban rail underframe processing route can effectively improve the production efficiency and reduce the production cost of the enterprise.In this thesis,by reviewing a large amount of literature,comparing the research status of tool selection management problems,workpiece process path problems,and Heterogeneous Fixed Fleet Vehicle Routing Problem(HFFVRP),many factors affecting the optimization of the machining route of urban rail underframe are analyzed.It analyzes the many factors affecting the optimization of the machining route of urban rail underframe,takes the optimization of the machining route of urban rail underframe as the research objective,and analyzes the theory related to the empty tool path and the number of tool changes in depth.The objective function of the model is the shortest tool path and the minimum number of tool changes;the constraints focus on the conservation of the flow of the feature to be machined and tool type restrictions;each feature to be machined uses the candidate toolset preference gray correlation decision as to the tool allocation principle.By analyzing the advantages and disadvantages of different algorithm composition principles and application scenarios,it was determined that the improved NSGA-II algorithm was used to solve the proposed model,firstly,the features and knives were encoded by MSOS(machine selection and operation sequence representation)chromosomes;then,the dynamic Finally,to increase the diversity of the population,it is handled in two ways: single-point or double-point crossover by chromosome similarity judgment,and variation probability according to the number of iterations.Finally,the aluminum alloy city rail underframe case of the China Railway was solved,and a reasonable machining route was solved using the improved NSGA-II algorithm.Compared with the target values obtained by the traditional group planning method,the empty tool path and the number of tool changes obtained by using the improved NSGA-II algorithm were reduced,and the mathematical model and algorithm proposed in this thesis were proved effective by the case results,which improved the productivity of the enterprise.