Study On Prediction Of Cutting Tool Life And Parallel Machine Scheduling With Constraints Of Cutting Tool Life

Manufacturing industry is the principle status in the national economy and intelligent manufacturing has become the most important objective in the development of manufacturing automation where the artificial intelligent technology has become more and more popular.Parallel machine scheduling problems with constraints of cutting tool life have attracted attention from both academia and industry,which seriously affect the efficiency and cost of manufacturing.Jobshop Scheduling Problems(JSP)considering operation assignment and operation consequences without constraints of cutting tool life may increase machine idle time and cause damage of workpiece surface.Therefore,cutting tool life should be restricted in parallel machine scheduling problems.The cutting tool life could be predicted based on the monitoring of cutting tool wear and its prediction may reduce the machine idle time and avoid the damage of workpiece surface caused by the cutting tool resource competition.Furthermore,a parallel machine scheduling plan without cutting tool life constraints is unreasonable during practical manufacturing process.The cutting tool life prediction must be combined in parallel machine scheduling model due to its high effects on processing efficiency and quality.This paper proposes a Manufacturing Execution System(MES)combining cutting tool life prediction and parallel machine scheduling problems to improve bad effects presented above,and the main research topic are as following:(1)Analyze cutting parameters related on cutting tool wear and use GRNN model,with IFOA optimizing its transmission parameters by increasing step size and setting escape parameter,to predict the cutting tool wear.Propose the cutting tool monitoring model based on a method combining GRNN and IFOA to predict the cutting tool life automatically according to different kinds of cutting parameters received,such as features of cutting speed,feed speed,cutting depth,cutting force,average cutting temperature,amplitude and cutting length.(2)Study on parallel machine scheduling problems with more constraints of cutting tool,including cutting tool life and cutting tool numbers,and propose one MIP mathematic model to solve this parallel machine scheduling problem with constraints of cutting tool life.This model can solve the multiple objective optimization problem,including minimum completion time,high utilization rate of remainder cutting tool life and least cutting tool number,and feasible solutions can be gained in small batch data.Meanwhile,propose a Tabu-Genetic Search(TGS)method combining advantages of Tabu Search(TS)and Genetic Algorithm(GA)to gain feasible solutions with acceptable deviations in reasonable calculating time when solving big bath data.(3)According to relevant parameters about the whole cutting tool life cycle,including static features,dynamic features and characteristic features,in the cutting tool life prediction and parallel machine scheduling with constraints of cutting tool life modules,the database structure,tables and fields of production scheduling are designed with corresponding associations form according to the function of modules.These two modules are achieved and integrated into one MES.