Method And Application Of Job Shop Energy-saving Scheduling Based On Flexible Process Planning

Production scheduling plays a vital role in the manufacturing process and has a direct impact on production efficiency and production costs,which in turn affects the improvement of the core competitiveness of manufacturing enterprises.The development of green energy saving is considered to be the focus of advanced manufacturing.How to reduce the energy consumption of the production system during the manufacturing process has become an urgent problem to be solved.Therefore,the green production scheduling system considering energy saving and consumption reduction has been extensively studied.The process planning system and dispatching system are two inseparable important subsystems in the production system,which is generally carried out separately in the traditional production process,resulting in conflicting objectives and limited plant resource allocation.The research on energy consumption optimization of production system should not be limited to a certain subsystem,coordinate the optimization index of process planning and shop scheduling,rationally allocate workshop resources,and break the bottleneck of traditional scheduling is the purpose of joint optimization of the two,more realistic The need for production and processing.Therefore,it is of great theoretical and practical significance to study the energy-saving scheduling of job shop based on flexible process planning.This paper studies the process planning and workshop scheduling issues.First,the process planning system is taken as the research object.The flexible characteristics of flexible process planning are considered.The influence of different process route designs on production energy consumption is analyzed.A flexible process planning model is proposed,and an improved hybrid genetic simulated annealing algorithm is proposed to solve the model.The output process route is used as the input for subsequent scheduling.Secondly,based on the research of flexible process planning,in order to further reduce the energy consumption in the production process,better coordinate the optimization goals set by the process planning and scheduling,based on the nonlinear optimization method,and the maximum completion time of the traditional optimization goals On the basis of the total production cost,a job shop energy-saving scheduling model based on flexible process planning is proposed.At the same time,an improved hybrid genetic variable neighborhood search algorithm is proposed to solve the model,and the purpose of joint optimization of the process planning system and the scheduling system is achieved.Finally,taking the production of diesel engine parts and components at the 3rd factory of QSY Company as an example,the production process and production scheduling status of several parts are analyzed,and related data such as process information of the parts and processing information of the machine are collected.Based on this,the two models constructed are used as examples,and Python is used as a tool to solve the improved algorithm.The analysis of the example’s calculation process and results proves the validity of the model.Compared with other intelligent optimization algorithms,the superiority of the proposed improved algorithm is proved.