Replacement interval optimization for aircraft maintenance

This paper deals with optimization of maintenance strategy of complex Aircraft systems, although the methodology can be applied to any industry. The paper considers two approaches to Preventive Maintenance (PM) interval optimization, shows their advantages and disadvantages, and proposes improvements to both: 1. Traditional approach based on reliability distribution characteristics of the entire population of items (systems) 2. Innovative approach, a Prognostic Health Management (PHM) using the Remaining Useful Life (RUL) of each individual item. For the traditional approach, a unique universal algorithm of "random search" is proposed. The main advantage of this algorithm is its versatility. In contrast to the classical optimization algorithms this methodology does not require complex analytical formulas. As a result, one gets an ability to analyze all possible experimental data types: exact failure times, interval data, suspended times, grouped data, etc. Optimal selection of Inspection/Replacement Interval value then can be made using parameters found as a result of data analysis. The optimization is demonstrated for a loss function of a special type of asymmetry of losses due to premature and late replacement, non-linearity of the Target Function, etc. As for an innovative PHM-based approach, an advanced Prognostic Methodology and unique Model have been developed. This Model implements Critical Zone Recognition (instead of classical Regression method) to verify whether Remaining Useful Life (RUL) of a particular (individual) item exceeds a predefined critical value. Reaching this critical value serves as a trigger for item's PM performance.