A Study of the SVM Tool Life Monitoring Model

• Main Authors: Te-Wei Chang, 張德韋
• Other Authors: Po-Tsang Huang
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/8nwm5d

碩士 === 中原大學 === 工業與系統工程研究所 === 106 === As the market demand shifts to a small number and variety, and the life cycle is short, and the quality requirements of the products in the process are extremely strict. The wear of the tool will cause the workpiece surface to become rougher, and the excessively worn tool will cause the tool to exceed the tool life and to make the surface roughness beyond the tolerance limit. In order to obtain an accurate tool life. Many scholars hope to use predictive methods to monitor the variation of the process on the one hand and to reduce the additional cost on the other hand. In the different processing environments and settings, there are many uncontrollable factors that are beyond human control. Therefore, the development of sensing technology can monitor the variation generated in the process, and then analyze the impact of the process due to external factors, not only can effectively reduce the bad rate, but also can improve the accuracy of the prediction. This study will construct the predictive models. Use support vector machines to quickly identify tools and predict tool life. The traditional predictive models require large amounts of data to modeling, and this study will invest in a small number of models and achieve Accurate prediction results. In order to verify the accuracy and feasibility of the proposed method, two sets of different processing parameters were set up in the experiment, and a small amount of data was put into the prediction system to predict the number of tool processing. The prediction accuracy of the SVM tool discriminant model experimental group is 97.78% and the SVM tool discriminant model verification group results the prediction accuracy rate of 98.11%, which confirms the accuracy and feasibility of the prediction system proposed in this study.