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In today's aircraft the diagnostic and prognostic systems play a crucial part in aircraft safety while reducing the operating and maintenance costs. Aircraft are very complex in their design and require consistent monitoring of systems to establish the overall vehicle health status. Most diagnostic systems utilize advanced algorithms (e.g. Bayesian belief networks or neural networks) which usually operate at system or sub-system level. The sub-system reasoners collect the input from components and sensors to process the data and provide the diagnostic/detection results to the flight advisory unit. Several sources of information must be taken into account when assessing the vehicle health, to accurately identify the health state in real time. These sources of information are independent system-level diagnostics that do not exchange any information/data with the surrounding systems.

UAS (Unmanned aircraft system), widely known to the general public as drones, are comprised of two major system elements: an Unmanned Aircraft (UA) and a Ground Control Station (GCS). UAS have a high mishap rate when compared to manned aircraft. This high mishap rate is one of several barriers to the acceptance of UAS for more widespread usage. Better awareness of the UA real time as well as long term health situation may allow timely condition based maintenance. Vehicle health and usage are two parts of the same solution to improve vehicle safety and lifecycle costs. These can be worked on through the use of two related aircraft management methods, these are: IVHM (Integrated Vehicle Health Management) which combines diagnosis and prognosis methods to help manage aircraft health and maintenance, and FOQA (Flight Operations Quality Assurance) systems which are mainly used to assist in pilot skill quality assurance.

In the past few decades the number of airplanes has increased dramatically and aircraft systems have become increasingly more complex. Under these conditions, the next generation of airplanes will undergo substantial changes and will make significant technical progress to improve operational safety. This vision is entirely consistent with the adoption of Integrated Vehicle Health Management (IVHM) technology which uses merging of interdisciplinary trends to carry out safe and effective vehicle operation. Hitherto, IVHM has made much progress in the realm of maintenance and operation, but little on safety assessment. This paper discusses the issues around how IVHM could be used to aid the operational safety assessment in the aviation industry. Special attention is paid to existing safety assessment methods, and some challenges and promising research directions are highlighted.