Sandeep Menon1, Chris Stecki2, Jiaqi Song3 and Michael Pecht1,3
1Center for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD 20742, United States, 2PHM Technology Pty Ltd. 1/15 Pickering Rd, Mulgrave VIC 3170 and 3Prognostics and Health Management Center City University of Hong Kong
Prognostics and health monitoring for electronic systems has been a field of interest of many researchers in the past decades. Traditionally, implementation of in-situ health monitoring for electronic systems has not been feasible due to time and cost considerations. However, recent research has led to improved sensing techniques and a better understanding of the manifestations and mechanisms of failures in electronic components. This paper outlines a software-based Failure Mode Mechanism and Effect Analysis approach to identifying the critical factors that lead to failure. A system-level model was created to map the interactions between subsystems at a functional level using a standardized taxonomy available in the software package. Also, the associated possible failures modes and mechanisms at every level were defined while modeling the system. This provided a better understanding of the impact of sub-system failure at a system level and enabled the effective interpretation of the Failure Modes, Mechanisms, and Effects Analysis. A model-based simulation of failure propagation was utilized by the software to generate a system-level database of failure modes and effects. This database allowed us to implement prognostics and health monitoring by identifying monitoring needs and reducing redundancy for a specified level of failure coverage. Also, inconsistencies introduced by a difference in interpretation of the standards were eliminated by using a standardized taxonomy. A case study was conducted to demonstrate the application of this approach for sensor set design optimization.Complete article available to CALCE Consortium Members.