# Decision-Making Framework for Aviation Safety in Predictive Maintenance Strategies
## 3 Results
### MCDA-Based Decision-Making Framework for PM Implementation  
#### 3.3.1 General Approach for Decision-Making Framework Development  
The decision-making framework for implementing PM of aircraft components utilizes a MCDA approach to systematically evaluate and rank components based on their suitability for PM. This approach addresses the complex and multidimensional nature of maintenance decision-making, ensuring that all technical, economic, regulatory, and organizational factors are considered in a transparent, data-driven, and actionable manner.  
The framework aims to identify and prioritize aircraft components that are most suitable for PM, balance diverse considerations, provide a reproducible decision-making process, and align with aviation safety and operational priorities.  
The decision-making process involves five key steps (Figure 11).  
Step 1: Criteria identification and weighting: Criteria are identified through literature reviews, expert consultations, and empirical data analysis. The AHP is used to assign weights to each criterion based on pairwise comparisons, ensuring that the most critical factors receive appropriate emphasis [36].  
Step 2: Scoring and normalization: Quantitative and qualitative data are collected for each criterion and normalized to a common scale (0 to 1) to ensure comparability.  
Step 3: Aggregation of scores: Scores are aggregated at two levels:  
* Criterion-level aggregation: Normalized scores within each thematic category are weighted and summed to produce a category score.
* Category-level aggregation: Category scores are weighted and combined to calculate an overall PM suitability score for each component.  
Step 4: Ranking and prioritization: Components are ranked based on their overall PM suitability scores, which reflect their feasibility for PM. Components are categorized intotiers (e.g., high, moderate, or low suitability), enabling targeted decision-making.  
Step 5: Validation and sensitivity analysis: The framework is validated by comparing results with historical maintenance data and expert opinions. Sensitivity analysis is conducted to test the robustness of results under varying criteria weights and scores, identifying the most influential factors affecting the rankings.  
The framework's outputs include a prioritized list of components suitable for PM, actionable insights into the key factors influencing PM feasibility, and recommendations for addressing challenges such as data sufficiency or cost considerations. For example, a turbofan engine might score highly in technical reliability and economic feasibility, making  
Figure 11: Key steps of decision-making process.  
it an ideal candidate for PM, while hydraulic systems with moderate data sufficiency may require sensor enhancements. FMC with low predictability and cost-effectiveness scores may be deemed unsuitable for PM.  
This MCDA-based framework offers several advantages. It provides a comprehensive evaluation by considering diverse factors, ensures transparency and reproducibility through structured methods like AHP, and adapts to new data or operational changes. By incorporating expert input and feedback, it builds stakeholder consensus and enhances credibility. The framework supports the aviation industry's transition to more efficient, reliable, and cost-effective maintenance strategies while maintaining alignment with safety and regulatory priorities.  
This decision-making framework provides a robust, adaptable, and evidence-based approach for implementing predictive maintenance in aviation. By integrating multiple criteria, expert insights, and a structured evaluation process, it facilitates informed decisions that optimize operational efficiency and safety while addressing economic and organizational constraints.