# Decision-Making Framework for Aviation Safety in Predictive Maintenance Strategies
## 2 Materials and Methods  
### Predictive Maintenance in Aviation  
The aviation industry is a highly complex and safety-critical domain where maintenance plays a pivotal role in ensuring operational efficiency and passenger safety. Traditional maintenance practices such as reactive and preventive maintenance have been effective but often result in unplanned downtimes or excessive maintenance costs. Predictive maintenance, on the other hand, uses advanced technologies to monitor the condition of components and systems, enabling timely interventions before failures occur. This approach not only enhances safety but also optimizes resource utilization, making it increasingly vital in modern aviation.  
PM is a CBM strategy that uses real-time data from sensors and advanced analytics to predict when a component or system will likely fail. By identifying potential failures early, maintenance can be scheduled during non-critical times, reducing unexpected downtimes and associated costs. In aviation, this involves the integration of tools like vibration analysis, thermography, and acoustic emission testing with advanced analytics platforms to assess the health of aircraft components.  
The potential-failure (P-F) curve is a fundamental tool used to understand the degradation process of components and systems [35]. It illustrates the timeline from the detection of a potential failure in point P to the point F of functional failure (Figure 1).  
In aviation, where safety is paramount, detecting point P as early as possible is crucial. The P-F Curve is divided into several zones:  
1. Proactive maintenance zone occurs before any detectable degradation, focusing on eliminating root causes through design improvements and best practices.
2. Preventive maintenance zone refers to scheduled interventions based on estimated component lifespans, often occurring near point P.
3. Predictive maintenance zone is the critical window between point P and point F, where condition-monitoring tools detect issues and trigger timely interventions.
4. Reactive maintenance zone refers to post-failure interventions when the system has already ceased to function.  
In aviation, predictive maintenance thrives in the P-F interval, where it utilizes advanced monitoring and predictive analytics to address issues before they lead to functional failure. Modern aviation employs different predictive maintenance technologies (Table 1).  
The applicability of the curve for defining the maintenance strategy largely depends on whether the component experiences gradual degradation that can be monitored, such as mechanical bearings or hydraulic systems. For components with measurable conditions, like engine vibrations or structural fatigue, the curve is highly relevant. Conversely, components that fail unpredictably, such as electronic chips or systems prone to sudden catastrophic failure, are less suited to this model. Some examples of applied predictive maintenance across various components and systems in aviation are shown in Table 2.  
Figure 1: The degradation process of systems with possible strategies of maintenance.  
Predictive maintenance offers several advantages in aviation. It enhances safety by detecting potential failures early, reducing the risk of in-flight incidents. It optimizes costs by minimizing over-maintenance and avoiding costly reactive repairs. Increased aircraft availability is achieved by enabling scheduled maintenance during off-peak hours, reducing downtime. Data-driven decision-making improves the accuracy of maintenance planning through real-time data and predictive analytics.  
Despite its advantages, implementing predictive maintenance in aviation is not without challenges. Integrating data from multiple systems and ensuring interoperability can be complex. Maintenance personnel require training to interpret data and operate advanced tools. Additionally, predictive maintenance practices must adhere to stringent aviation safety regulations.