Prediction Method Researchfor Consumptionof Cutting Tool And System Designintire Mold Manufacturing Enterprises

Tire mold manufacturing is becoming more and more important in modern industry; it promotes the rapid development of the tire mold industry because of the huge demand in the market. The tool is essential for Tire mold manufacturing and its information runs through the whole process from production preparation to completion. It influences the efficiency of the investment and production significantly. Rational use and consumption of the tool is important for the tire mold enterprise production management, as well as the calculation and assessment of the costs. Therefore, doing the prediction research for consumption of tool and guaranteeing reliable tool supply plan is particularly important.The traditional tool consumption calculations are based on consumption quotas. Because of its considerations are often not comprehensive, and the workload is too large for forecasters, so the method is lack of advanced and rationality. It is necessary to find a more scientific and reasonable theory of prediction method. With the tool consumption as the research object, a tool consumption prediction model is established, and then the system of tool consumption prediction is designed. The major research content includes the following aspects.First of all, this paper engaged in the research of characteristics of the tire mold’s production, to identify the main factors affecting the tool consumption. It is analyzed from both technical and managerial aspects, and six factors are obtained. They are machining man-hour, type of process, the work piece material, tool material, the tire tread type, level of workers.Secondly, the data mining technology is used to support the prediction model. The use of cluster analysis is for the classification of tool consumption. Three types of tool consumption are established from using Two-step clustering. Regression analysis is used to propose the regression equations.At the same time, the equations’ statistical significance was proved by significance test and accuracy test.At the end, the tool consumption prediction software is developed. And the SPSS object is combined with the software because of its powerful data analysis capabilities. It promotes the production works of staff for tool consumption; it also has an important role to enhance the level of tool management.