Description
The traditional business model for providing condition monitoring and predictive maintenance services is under pressure from the proliferation of new technologies such as predictive analytics, cloud and digital automation. There are currently many initiatives whereby companies try to collect real-time asset data, train statistical models on this data and apply them continuously to predict equipment failures before they occur in a fully automated process. Given all the recent buzz on Big Data, Industry 4.0 and the Industrial Internet of Things, it might come as a surprise that this new, digitized way of working is only gradually being implemented. Currently, quite a few predictive analytics projects do not deliver the expected outcomes within the expected timeframe, for a variety of reasons.
In this presentation, some practical insights are presented on predictive analytics programs, how they can be managed successfully and how some common pitfalls can be avoided. An overview is given of the distinct types of predictive techniques that can be applied, their pros and cons, and the typical setup and stages of a predictive analytics project. Some practical lessons learned are elaborated, both for companies already actively exploring predictive analytics as well as for those who are only thinking about whether or how to get started.
Bio
Joris Van Ostaeyen is an expert on service business models and predictive analytics. He helps companies to create and capture value from services and data. Dr. Van Ostaeyen holds a Master of Science in Electromechanical Engineering (2003) and a PhD in Industrial Management (2014) from KU Leuven University, Belgium. Early in his career, he gained 5 years of experience in Belgium and China as process engineer and manufacturing project leader for Atlas Copco, the world’s largest manufacturer of air compressors. After his return from China, he became Research Associate at the Center for Industrial Management of KU Leuven and did research into service business models for industrial manufacturers. He has authored various articles in international scientific journals and is a regular speaker at national and international conferences. In parallel to his academic work, he started his activities as independent consultant in 2013. Dr. Van Ostaeyen helps companies to create new business models and to implement digital transformation projects. His clients include Barco, SAS Institute and Allied Reliability Group. Over the last years, he has managed projects related to advanced analytics in various industries, such as technology, chemical processing and metalworking.
