Shop Scheduling Optimization And Simulation Of Production Line In Machine Tool Component

In recent years,in order to meet the diversified and individualized demands of the market,there are more and more types of products about production line in machine tool component,and the production process is more complicated.Shop scheduling is an important part of the manufacturing system.Through the rational allocation of workshop resources,production efficiency,cost and energy consumption can be improved.Therefore,as to the shop scheduling optimization problem of production line in machine tool component,the following research work is carried out:(1)A high-dimensional many-objective optimization method is studied.In this paper,a genetic algorithm based on similarity of intuitionistic fuzzy sets(SIFS?GA)is proposed to solve the problem of high-dimensional many-objective optimization.The similarity of the intuitionistic fuzzy set is used as the fitness of the evolutionary algorithm to guide the evolution of the algorithm.The Pareto solutions are mapped to the intuitionistic fuzzy set,and the intuitionistic fuzzy set of reference solution are constructed.The similarity degree between the intuitionistic fuzzy sets of Pareto solutions and the reference solutions are calculated,and it is used to judge the merits of the Pareto solutions.Finally,the algorithm is tested by CEC standard test examples,and the results verify that the performance of the algorithm is better than the commonly used multi-objective optimization algorithm.(2)According to the flexible processing characteristics of production line in machine tool component,a many-objective flexible job shop scheduling model and its solving method for green production are established.Firstly,the related theories of flexible job shop scheduling problem and manufacturing system energy consumption are expounded.Based on this,an energy-saving scheduling model of flexible job shop with maximum completion time,idle time,processing quality and energy consumption is established.Secondly,in order to make the algorithm suitable for flexible job shop scheduling problems,the SIFS?GA is discretized and improved.Finally,the performance of the algorithm is evaluated by MK test examples,the result shows that discrete SIFS?GA can effectively solve the energy-saving scheduling problem of high-dimensional many-objective flexible job shop.(3)A multi-objective flexible job shop scheduling model considering transportation time is established for the actual production characteristics of machine tool components.In most studies,the transport time is usually neglected,however the weight of the machine components is large,which will lead to a huge gap between theoretical research and practical applications.Therefore,on the basis of the original,this paper introduces the transport time.The transportation energy consumption generated by the transport process is added in the objective function of energy consumption while the other objective functions are unchanged.Finally,this paper combines with the production examples of actual production workshop's machine tool components.The proposed method and NSGAII are used to complete the solution design of flexible job shop scheduling scheme for production line of machine tool components,the result shows that the discrete SIFS?GA algorithm is an effective method to solve the many-objective flexible job shop scheduling problem considering transit time.(4)In order to verify the above research results more intuitively,the discrete simulation software QUEST is used to simulate and analyze the production system and scheduling scheme.The simulation process by QUEST software is introduced in this case,and the physical modeling and logical link of the production line of machine tool parts processing workshop can be built.Finally,the device utilization,equipment idle time and job completion time and other data parameters is output by QUEST software.The comparative analysis of simulation data proves the effectiveness and superiority of the algorithm.