  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.
