Energy-Efficient Scheduling Of Multi-Variety And Small Batch Flexible Job Shop With Complex Processes

As a result of multi-variety,single piece and small batch,as well as the cross-parallelism of multiple models,different parts and processes of aerospace complex components need frequent switching which lead to low efficiency and generates a large amount of energy consumption in the job-shop.Thus,an energy efficient job shop is crucial to reducing the total energy consumption of aerospace enterprises.Furthermore,due to the complex production process,long process processing and processing preparation time,batch properties of workpieces and flexible machine tool selection,unreasonable scheduling plan will definitely lead to a large amount of energy,time,cost and other resources wastage in the aerospace complex components job-shop.Therefore,as an effective way to reduce the energy consumption in the job-shop,job-shop energy-efficient scheduling is a well-motivated research issue for green and high-quality development of aerospace enterprises.Thus,this work focuses on the manufacturing process of some aerospace typical complex components,and conducts an in-depth study on the energy consumption problem existing in the operation of the job-shop.Then,make a system research for energy consumption optimization of the job shop scheduling model construction and model solving method under static and dynamic scheduling environment.The specific research contents are as below:(1)To cope with the problems of high energy consumption,low machine tool utilization caused by the mixed flow of multiple varieties and single parts and small batches,as well as complex process in the aerospace complex components flexible job-shop.A static energy consumption optimization scheduling method based on improved NSGA-II algorithm is proposed.First,a static multi-objective energy-efficient lot-splitting scheduling model for aerospace complex components is formulated.Then,a weighted process tree and NSGA-II hybrid algorithm is introduced to solve the model.In this way,the problems of slow search speed and poor convergence caused by non-directional generation of initial solution are solved and the optimal scheduling scheme is obtained.Finally,an energy-efficient job-shop in static environment is achieved.(2)To address the impact of dynamic events such as emergency order insertion and machine failure in the actual production of the workshop,a dynamic energy consumption optimization scheduling method based on improved ABC algorithm is presented.Firstly,a dynamic multi-objective energy-efficient lot-splitting scheduling model for aerospace complex components is addressed.And an improved ABC algorithm based on differential evolution and cross variation is designed to solve the model.In this way,the global search ability,convergence speed and quality of the solution are improved,and the diversity of the population is guaranteed.Furthermore,the optimal scheduling scheme is obtained and the job-shop energy consumption in dynamic environment is optimized.(3)To verify the practicability of the optimal scheduling scheme,the simulation model of production job-shop of multi-variety and small batch aerospace enterprises based on Plant Simulation is constructed.Sim Talk is used to establish the simulation logic,and the scheduling schemes before and after optimization are analyzed from the aspects of production efficiency,equipment yield and balance rate.Then,the multi-level,comprehensive and scientific verification of the whole production scheduling scheme of aerospace complex components is realized.