Most companies have a lot of data and it is critical for them to know how to use it. My work is on developing mathematical models to integrate real-world data with operational decision making.
Alp Akcay is an assistant professor in the Operations, Planning, Accounting and Control (OPAC) group at Eindhoven University of Technology. His research interests include statistical decision making under uncertainty, simulation design and analysis, and approximate dynamic programming with applications in manufacturing, maintenance, and supply chain management. He is a core-team member of the smart maintenance and manufacturing research program at Data Science Center Eindhoven.
Alp Akcay received his PhD in Operations Management from the Tepper School of Business at Carnegie Mellon University (2013). The title of his PhD dissertation is “Statistical Estimation Problems in Inventory Control.” Dr. Akcay holds an MSc in Industrial Engineering from Sabanci University (2008) and a BSc in Mechanical Engineering from Boğaziçi University (2006). Prior to joining TU Eindhoven, dr. Akcay has worked as an assistant professor at Bilkent University (2013-2015).
Simulation-based production planning for engineer-to-order systems with random yield2017 Winter Simulation Conference (WSC 2017) (2018)
Simulation of inventory systems with unknown input models: a data-driven approachInternational Journal of Production Research (2017)
Stochastic simulation under input uncertainty for contract manufacturer selection in pharmaceutical industry2016 Winter Simulation Conference (WSC 2016) (2016)
A simulation-based support tool for data-driven decision making : operational testing for dependence modellingProceedings of the 2014 Winter Simulation Conference, 7-10 December 2014, Savanah, Georgia (2014)
Quantifying input uncertainty in an assemble-to-order system simulation with correlated input variables of mixed typesProceedings of the 2014 Winter Simulation Conference, 7-10 September 2014, Savanah, Georgia (2014)
- Maintenance and service logistics
- Manufacturing Technology
No ancillary activities