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.