A Use Case to Implement Machine Learning for Life Time Prediction of Manufacturing Tools

Abstract

Current machine learning techniques show a high degree of maturity and can be implemented for applications in manufacturing. In this context, using machine learning to investigate the relationship between process parameters and process performance allows an optimization of production systems. Conventional methods to analyze the life time of a manufacturing tool provide only a vague estimation of tool life. Therefore, this paper introduces an industrial use case for using machine learning to predict individual cutting tool life times. Hence, the life time of every individual manufacturing tool can be realized more accurately and its operation time can be maximized.