Application of Multivariate Data Analysis to machine power measurements as a means of tool life Predictive Maintenance for reducing product waste
Modern manufacturing industries are increasingly looking to predictive analytics to gain decision making information from process data. This is driven by high levels of competition and a need to reduce operating costs. The presented work takes data in the form of a power measurement recorded during a medical device manufacturing process and uses multivariate data analysis (MVDA) to extract information leading to the proposal of a predictive maintenance scheduling algorithm. The proposed MVDA model was able to predict with 100 % accuracy the condition of a grinding tool.