Van Horenbeek's background is in mechanical engineering. As well as holding master's degrees in electromechanical engineering and industrial management, he gained a Ph.D. in maintenance and reliability management with a focus on predictive maintenance at the University of Leuven in Belgium. His doctorate involved cooperation with several industrial companies like Bekaert and Atlas Copco, and here he became interested in combining engineering skills with data analytics.
"With my Ph.D., I did research on predictive maintenance, purely from an engineering point of view. So how to capture vibration data with different equipment, but then also combining it with data analytics, how to make sense out of this data, how to come to predictions on when the components are going to fail for example, and linking it to the business case as well. For me, one of the important pillars is the engineering aspect of the business, which has everything to do with data analytics and combining it with value."
After doing his Ph.D. he worked as an asset management consultant for Dutch company Stork Technical Services at their Antwerp site. Here he performed reliability engineering projects at Umicore, BASF, and VPK among others. "I worked on several projects, but spent most of my time in the chemical industry, implementing Six Sigma Lean Reliability Engineering, always from the point of view of using the engineering knowledge that was already available within these companies, but taking the next step in terms of smarter use of data."
While doing this work he came in contact with SAS, and eventually joined them in 2015 in a customer advisory role dedicated to manufacturing clients. "This combined my biggest interests in engineering with data analytics," he says. In 2019 he was appointed as Manufacturing Lead for Western Europe, overseeing customers in the Netherlands, Belgium Luxembourg, and France.
His background of engineering skills, management skills, and data analytics skills, makes him an ideal partner to his clients, to help them develop and embed analytics within their manufacturing processes.
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