The aviation industry is facing growing demands to reduce its environmental impact while ensuring operational safety and economic viability. As aircraft maintenance plays a central role in the lifecycle of aviation components, optimizing these processes is essential for achieving long‐term sustainability. Digitalization as a key enabler offers new ways to plan and execute repair processes more efficiently. A central element is the systematic collection and use of process data. In this research, detailed results from non‐destructive testing such as visual inspections, and other diagnostic methods are captured in structured and standardized databases, organizations can create a digital memory of component conditions, defect histories, and repair outcomes. These databases allow for data‐driven process planning, enabling maintenance teams to identify patterns, anticipate failure modes, and select repair strategies based on evidence rather than experience. Complementing this data‐centric approach, simulation‐based process planning is developed for virtual testing and optimization of repair procedures before carrying them out in practice. Through simulations, various repair scenarios can be evaluated in terms of time, cost, and environmental impact. This supports sustainable decision‐making by minimizing waste, rework, and downtime. The effects of the proposed data‐driven simulation models on sustainability are critically discussed.
Aigner et al. (Mon,) studied this question.