On Quantifying Cost-Benefit of ISHM in Aerospace Systems

Integrated systems health management (ISHM) is a desired system engineering capability to detect, assess, and isolate faults in complex aerospace systems to improve safety and reliability. At the conceptual design level, system-level engineers must make decisions regarding the extent of vehicle fault coverage using on-board sensors and the data collection, processing, interpretation, display, and action capabilities for the various subsystems, all considered essential parts of ISHM. In this paper, we propose a Cost-Benefit Analysis approach to initiate the ISHM design process. The key to this analysis is the formulation of an objective function that explicitly quantifies the cost-benefit factors involved with using ISHM technology in various subsystems. In the end, to determine the best ISHM system configuration, an objective is formulated, referred to as Profit, which is expressed as the product of system availability (A) and revenue per unit availability (R), minus the sum of cost of detection (CD) and cost of risk (CR). Cost of detection includes the cost of periodic inspection/maintenance and the cost of including ISHM; Cost of Risk quantifies risk in financial terms as a function of the consequential cost of a fault and the probabilities of occurrence and detection. Increasing the ISHM footprint will generally lower cost of risk while raising cost of detection, while Availability will increase or decrease based upon the balance of the reliability and detectability of the sensors added, versus their ability to reduce total maintenance time. The analysis is conducted at the system functional level, with ISHM allocated to functional blocks in the optimization analysis. The proposed method is demonstrated using a simplified aerospace system design problem resulting in a configuration of sensors which optimizes the cost-benefit of the ISHM system for the given input parameters. In this problem, profit was increased by 11%, inspection interval increased by a factor of 1.5, and cost of risk reduced by a factor of 2.4.