Modeling and Simulation of Repairable Systems for Depot Maintenance and Warranty Forecasting using an Effective Age Approach

Principal Investigators: Zissimos P. Mourelatos, Oakland University, mourelat@oakland.edu
Vijitashwa Pandey, Oakland University, pandey2@oakland.edu
Student: Themistoklis Koutsellis, Oakland University
Government: Matthew Castanier, Amandeep Singh, U.S. Army TARDEC
Clifton Ellis, PEO CS&CSS
Industry: Mohammad Hijawi, Chrysler

Project begins 2016.

Overview of GRP Model for ReliabilityMost engineering systems are repairable. Their components can be repaired or renewed, if system failure occurs, so that the system can be put back into service. The classical reliability theory however, captures only limited aspects of the performance of these systems. The commonly used metrics of Mean-Time-Between-Failures (MTBF) and availability do not provide complete statistical information. MTBF is a widely used concept but only captures the mean. Availability may be misleading because a system that needs constant repair but takes only a short time to repair has a very high availability. Such a system however, has a very small practical use. Over time, many components in a system get old and the frequency of system breakdown increases. Component repairs or replacements are performed within a planning horizon (system useful life) and the system is then retired.

The goal of this project is to develop methods for reliability and long-term operation of repairable systems including "reset" and depot maintenance strategies, and spare-part inventory management, and simultaneously enhance TARDEC’s Fleet Maintenance Simulation (FMS) software tool with all new developments. The research allows us to estimate the effective age of a vehicle, which is a metric we could not calculate before. The estimation of effective age is of high interest to the Army in general and the PEO CS & CSS in particular. We will also develop state-of-the-art capabilities in warranty prediction and forecasting for the automotive and military industries. Currently the FMS tool can predict the reliability, availability, and maintainability of a vehicle fleet using the classicall Non-Homogeneous Poisson Process (NHPP) approach. It can also carry out tradeoff studies, sensitivity analyses, and design optimization of repairable systems.

Most ground vehicle fleets continue to be used for decades. The Army needs therefore, tools to assist in making fleet planning decisions and in developing depot maintenance strategies that will help reduce O&S costs while ensuring that the vehicle fleets maintain their required performance levels. Reliability prediction considering different repair assumptions and technical obsolescence are essential for depot maintenance, "reset", and long-term operation strategies of repairable systems. Repair assumptions are also essential in warranty prediction and forecasting - a critical challenge for the automotive industry which spends billions every year on warranty and spare-parts availability and storage

Publications from closely related prior work:

  • A. Skowronska, D. Gorsich, V. Pandey and Z.P. Mourelatos, "Optimizing the Reliability and Performance of Remote Vehicle-to-Grid Systems Using a Minimal Set of Metrics," ASME Journal of Energy Resources Technology, 137(4), 041204 (7 pages), 2015
  • V. Pandey, Z.P. Mourelatos and M. Castanier, "Decision Topology Assessment in Engineering Design under Uncertainty," Proceedings ASME 2014 Design Engineering Technical Conferences, Paper DETC2014-34244, Buffalo, NY, August 2014.
  • V. Pandey, Z.P. Mourelatos, E. Nikolaidis, M. Castanier and D. Lamb, "System Failure Identification using Linear Algebra: Application to Cost-Reliability Tradeoffs under Uncertain Preferences," Proceedings of SAE International, World Congress, Detroit, MI, April 2012, Paper 2012-01-0914.