Availability Optimization and Maintenance Priorities of a Ramjet Engine Using Genetic Algorithm

The objective of this research is to improve the accessibility of ramjet engines to the aerospace industry by identifying critical elements of the system and to improve operational efficiency across the industry by optimizing endurance and performance. The compressor, gearbox, combustor, turbine, ram burner, and fuel injector are all essential components of an engine. Redundancy in compressor and turbine units is used to improve the overall performance of the system. This problem requires the use of an advanced genetic algorithm optimizer-driven design technique. This optimizer integrates system performance prediction methods to create an integrated design strategy. This study employs arbitrary repair rates, availability, and failure rates that follow an exponential distribution to establish a novel mathematical model. This model employs Markov processes and the Chapman–Kolmogorov equations to achieve generalization. Evaluating component performance involves a thorough examination of the availability values failure rates and repair rates of various subsystems in the decision matrix. It ensures continuous care of the system by making maintenance recommendations for all subsystems. Potential future research avenues may include incorporating real-time data and sophisticated machine-learning algorithms to enhance predictive maintenance processes. This study presents its findings for engine management. Innovations increase the efficiency of engines, making them applicable in real-world situations.