Vasiliy Krivtsov

Senior Staff Technical Specialist
Ford Motor Company

Vasiliy Krivtsov is a practitioner and consultant in Reliability Engineering, Risk Analysis and Applied Statistics employed by Ford Motor Company as a Sr. Staff Technical Specialist. He also holds the position of Adjunct Associate Professor of Reliability Engineering at the University of Maryland, where he teaches a graduate course on advanced reliability data analysis.

Krivtsov has earned a PhD degree in Electrical Engineering from Kharkov Polytechnic Institute (Ukraine) and a PhD in Reliability Engineering from the University of Maryland (USA). He is the author of over 60 professional publications, including 2 books on Reliability Engineering and Risk Analysis, 9 patented inventions and 6 trade secret inventions on statistical algorithms for Ford. He sits on the editorial board of Elsveir's international journal on Reliability Engineering and System Safety, is a Vice Chair of the International Reliability Symposium (RAMS®) Tutorials Committee and a Senior Member of IEEE. Prior to Ford, Krivtsov held the position of Associate Professor of Electrical Engineering in Ukraine, and that of Graduate Research Scientist at the University of Maryland Center for Reliability Engineering. Further information on Dr. Krivtsov's professional activity is available at www.krivtsov.net

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Main Day Two

Sunday, March 4th, 2018

15:40 Optimizing Field Maintenance Schedules

Complex technical systems, over their design life, are subject to preventive maintenance. Viewed as a field service activity, preventive maintenance is necessary to meet a system's reliability and availability (readiness) requirements. The question is what should be the optimal schedule of such preventive maintenance actions? Optimal in the sense that high frequency of these actions increases the cost of maintaining the system's operation but reduces the cost due to the system's downtime, while low frequency – decreases the cost system's operation but increases the cost of downtime. This presentation reviews mathematical (statistical) models that are used for preventive maintenance optimization and illustrated by case studies from the Vasiliy’s corporate experience.