Mahesh Kumbhar

Predictive maintenance is one of the major thrust areas for many global manufacturing companies. Artificial intelligence, big data analytics and industrial internet of things (IoT) have already shown great potential in the area of maintenance. However, as more companies adopt these technologies, several key challenges have emerged hindering the progress towards complete digitalization of maintenance operations.

With all the data acquired during a day of production, the possibilities for improvement are endless. All you need to do is find a way of interpreting the data. TOPAZ aims to investigate how a combination of data mining, machine learning and optimization can aid manufacturing companies. This will be done by transforming heterogeneous data derived from multiple sources, and potentially from different part of the value chain, into prescriptive actions that support long-term goals of profitability, sustainability and stability.