Complexity as a Measure of the Difficulty of System Diagnosis in Next Generation Aircraft Health Monitoring System

To develop the Next Generation Aircraft Health Monitoring System (NGAHMS), complexity as a measure of the difficulty of diagnosis, or troubleshooting, of a system is explored in this paper. The results presented can be applied to significantly improve safety and human factor design as an important as aspect of risk engineering and management. This is accomplished in system architecture design by quantifying the system structure’s effect on system complexity as well as the number of components which make up the system. For developing the NGAHMS to make flying even safer, more fuel efficient, and more predictable, model-based safety assessment methods such as Fault Tree Analysis (FTA) and Dependency Diagram (DD) with updated descriptions in SAE ARP4761A and ARP4754B can be used to minimize the average number of airborne inspections to find the Minimal Cut Set (MCS) causing an aircraft failure. Since, based on previous research, this average number of airborne inspections is proven to be lower-bounded by the entropy of cut set importance, the system complexity measure can be used to efficiently estimate how difficult it is to find the actual MCS. This state-of-art safety technique facilitates diagnosing faults effectively, and thus obtain full flight envelope protection for the Next Generation of Air Transport. As a measure for system complexity, this entropy function presents an intrinsic feature of the system, providing the basis of establishing rigorous design principles to diagnose safety-critical faults and thus to cancel their effects systematically through NGAHMS.