Research On The Optimization Of Key Spare Parts In Engine Manufacturing Process

Energy is the basic source power of social development,and the energy crisis seriously affects the sustainable development of social economy.The safe and low-energy operation of mechanical equipment is an effective measure to mitigate the energy crisis and reduce carbon emissions.It is inevitable that performance degradation and failure will occur in the production process of engine numerical control machine tools.Timely and reasonable maintenance of these equipment is an important way to ensure the safe and low energy consumption operation of engine machine tools.In order to ensure timely maintenance,the reasonable equipment spare parts are required to provide support.Therefore,this paper conducts research on the annual consumption prediction of key spare parts of engine CNC machine tools and optimization of ordering decisions to ensure the safe,efficient and economic operation of engine CNC machine tools.Research on predicting consumption of key spare parts for engine CNC machine tools is conducted.Firstly,this paper uses AHP-ABC model to screen out the key spare parts of CNC machine tools,and rough set theory to sort out the key factors.Secondly,traditional grey theory and Markov chain are combined to calculate the consumption characteristic sequence of key spare parts annual consumption,in order to predict the annual consumption of key spare parts of CNC machine tools.The sequence includes key factor data and spare parts consumption data.Finally,a case study is conducted by a spindle of transmission part and high-pressure pump of cooling system in the numerical control machine tool of an automobile engine factory,which have a great influence on the safety and energy consumption.The equal dimension and new information m-GMM(1,1)model proposed in this paper is used to predict the consumption of spindle and high-pressure pump for four consecutive years.The comparison between the predicted consumption and the actual consumption shows that the accuracy of the prediction model proposed in this paper is higher than that of the traditional prediction model.Research on ordering optimization of key spare parts for engine CNC machine tools based on reliability is conducted.Firstly,this paper combines statistical concepts with individual characteristics to jointly characterize their deterioration trend.Then,the improved Hidden Markov Model is used to predict the reliability trend of the machine tool components.Secondly,in order to achieve the purpose of spare parts ordering decision optimization,this paper establishes a spare parts ordering optimization model based on predictive reliability.Finally,a case study is conducted on an automobile engine factory,focusing on its decisions on ordering spindle bearing of engine CNC machine tool.The reliability of spindle is predicted by SI-D-HMM model and verified with the actual data.The result shows that the reliability prediction results are in good agreement with the actual deterioration.Then,the decision-making optimization model of spare parts ordering based on reliability proposed in this paper is adopted to figure out the timing of ordering spindle bearing with the lowest expected cost of unit operation time of spindle,so as to optimize the decision-making of ordering.