AIAC14 Fourteenth Australian International Aerospace Congress

Optimization of PHM System for Electronic Assemblies Using Maintenance Aware Design Environment Software

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.

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