Abstract: Ford's Safety organization performs crash tests on prototype vehicles at multiple planning phases of each new vehicle program. These tests ensure the vehicles meet all government and company requirements by the time the vehicles reach the production phase. However, crash tests are quite expensive to perform due to the high cost of prototype vehicles compared with that of production vehicles. Accordingly, improvements in scheduling that reduce the number of prototypes crashed yield a significant cost savings. This scheduling problem has many sources of complexity: varying deadlines, precedence relationships between tests, incompatibilities in vehicle specs required, etc. Currently, engineers spend weeks of time manually planning the crash schedule for each new vehicle program and coordinating with all the other prototype vehicle users. We are developing an automated system for crash test planning that both minimizes the resources needed and significantly reduces the time engineers spend planning. Co-Authors: University of Michigan - Yuhui Shi, Amy Cohn, Marina Epelman Ford Motor Company - Erica Klampfl Bio: Daniel Reich joined Ford Motor Company, Research & Advanced Engineering, as an Operations Research Analyst in 2011. He received his Bachelor of Science from Columbia University's School of Engineering and Applied Science in 2004 and his PhD in Applied Mathematics from the University of Arizona in 2009. Before joining Ford, Daniel spent two years as a Postdoctoral Research Fellow at the Universidad Adolfo Ibanez School of Business in Santiago, Chile. During his graduate studies and postdoctoral work, Daniel authored several papers on computationally tractable heuristic approaches for optimization under uncertainty. Daniel continues to retain strong ties to the academic community through the Ford-University of Michigan Alliance and Ford-MIT Alliance programs. Early work from his collaboration with MIT on electric vehicle routing was selected as a semi-finalist for the 2013 INFORMS Innovative Applications in Analytics Award. Daniel's current projects at Ford include developing optimization models for scheduling, sales and other applications. He co-developed Ford's Fleet Purchase Planner, which has been featured in Wards Auto, Green Car Reports, Automotive Fleet Magazine and other publications. This work also received the Best Paper Award at the 2013 International Conference on Operations Research and Enterprise Systems and is a finalist for this year's INFORMS Innovative Applications in Analytics Award.