Research On Optimization Of Tool Configuration In Machining Center

Tool life is an important limiting factor in machining productivity.Especially in the multivariety and small-batch production environment,the tool magazine capacity of the CNC machine tool is limited,and one tool change cannot complete the processing of all tasks.During the machining process,there will be tools that have run out of life,or the tool type required for the task is not in the tool magazine,and the tool needs to be changed to meet the machining requirements of the task.However,frequent tool changes can increase the number of downtimes,tool changes and new tools used,thereby reducing production efficiency and increasing configuration costs.In order to solve the above problems,this thesis conducts research from the following aspects:First,analyze the production and operation process of the automated machining center in detail,review and classify the modeling methods and solving algorithms related to the tool configuration problem,explain the process of several commonly used algorithms in detail,and analyze the applicability of the algorithms;Secondly,analyze the operation process of the automated production unit,combine the company's daily management methods for tools,understand the tool flow process between the various levels of the tool magazine,and analyze the tool change process between the machine tool magazine and the workshop tool magazine in detail.The tool configuration problem between the two is described,the characteristics of the problem are summarized,the problem hypothesis is proposed,and the mathematical model is established.Then,an accurate solution algorithm is proposed to solve the small-scale tool configuration problem,and the influence of tool life on the continuous processing of the task is analyzed.Here,it is proposed to reduce the state space of the tool configuration process,and use the dynamic programming inverse method to find the optimal solution.Analyze the influencing factors that affect the exact solution,build a heuristic rule algorithm framework,and refine the constraints through the algorithm framework,and propose a variety of heuristic rules to solve.Finally,according to the performance indicators and influencing factors of the established evaluation algorithm,experiments are carried out through experimental design,and the experimental results are analyzed,and the performance of different algorithms is obtained under the influence of different factors.Through the experimental analysis,it is concluded that the heuristic rule can obtain the optimal tool configuration scheme within the effective time,and can effectively reduce the total tool change cost.