Smart Maintenance and Human Factor Modeling for Aircraft Safety

The global pandemic has significantly accelerated the need for remote monitoring and diagnostics of airline operations and assets. As passenger and cargo flights are impacted from all directions, maintenance can be the steady, reliable part of the puzzle that helps get things back on track. This chapter explores the aircraft safety challenges that can be addressed with better maintenance technology and human factor modeling. Aircraft safety relies heavily on maintenance. During the COVID-19 recovery phase, airline operators need to focus on the application of a robust management of change process to implement better maintenance technology, identify new aircraft safety risks, determine effective mitigation measures, and implement strategies for deploying changes accordingly. For years aircraft maintenance routines have been carried out in the same manner without change, now with international travel restrictions, social distancing, reduced staff, and limited maintenance funding, the need for smarter ways of doing maintenance is obvious. In this regard smart technology has an important role to play. For instance, IoT data generates the capacity for predictive aircraft maintenance, AI introduces the capacity for smart, deep-learning machines to make predictive maintenance more accurate, actionable, and automatic. AI-enabled predictive maintenance leverages IoT data to predict and prevent aircraft failures. While smart technology enhances aircraft safety through better maintenance performance on the one hand, there are technical and human factor problems induced by COVID-19 on the other. The Safe Aircraft System (SAS) model, based on the Dirty Dozen and SHELL human factor models, is an initiative proposed to minimize such COVID-19 problems. This work shows through a case illustration that SAS modeling is a useful tool in identifying potential hazards/consequences associated with any major or minor changes in flight operations. Hence the synergistic effect of smart maintenance and the SAS model in enhancing aircraft system safety are demonstrated.