Failure Identification for Mission Analysis for Complex Systems

Abstract

This paper presents a new method for complex system failure analysis that provides both an overall failure analysis on a system’s functionality as well as a mission-based failure analysis. The Failure Identification for Complex Mission Analysis (FICMA) method presented here uses physics-based governing equations to identify the system’s overall behavior during both nominal and faulty conditions. The FICMA method is unique in that it first identifies a specific failure, or combination of failures, within a system and determines how each failure scenario will affect the system’s overall functional capabilities. Then, FICMA uses this failure information to assess and optimize various mission plans that the system may be asked to perform. The FICMA method is designed to identify all potential functional failures of a given system, and then, depending on the types of failures that have occurred, to identify the optimal functional approach needed to successfully complete its current mission. First, the FICMA method employs MATLAB/Simulink software along with multiple unique metrics to simulate various potential failure scenarios. Then, based on how these failure scenarios affect the functionality of the system components, the mission plans are automatically optimized. This optimization is based on finding the mission plan that experiences the fewest total effects from a given failure scenario, i.e. the most robust mission plans. Also, by using the FICMA method, each component of a system can be simulated anywhere from 0–100% of its original functionality without the specific failure mechanisms being required, which allows for this method to be implemented early in the design process while still providing valuable and unique failure information. To demonstrate this new method, a theoretical case study of a 3-linkage robot arm was chosen. Through simulations of multiple failure scenarios and mission plans, the FICMA method’s unique assessment and optimization techniques will demonstrate how to determine the optimal plan for completing a mission after a failure scenario has occurred.