Reliability Measures Evaluation of Some Multi state Engineering Systems

Abstract

In an era where industrial systems are required to be reliable and efficient, this thesis offers an extensive study on reliability engineering, with a focus on the assessment and improvement of system performance across a variety of engineering applications. The study delves deeply into reliability theory, system modeling methodologies, and practical applications, with the goal of addressing identified gaps in the existing literature. The first chapter gives a basic introduction to reliability theory, emphasizing key performance measurements and reliability evaluation metrics. The primary emphasis is on mathematical models and the crucial significance of Markov processes in modeling system behavior, which serves as a foundation for further investigations. The review of literature highlights critical gaps in areas such as multi-state systems, failure analysis, and maintenance techniques, which helps to determine the research objectives. The thesis assesses an automobile s reliability utilizing a 4-out-of-5:G system and integrated analytical methods. It also evaluates the performance of a paper mill plant using the Markov birth-death process, finding critical components using RAMD. Further analysis explores system sensitivity to component failure with varied repair rates, employing the Gumbel-Hougaard copula approach. Reliability measures of engineering systems like water treatment plant and HVAC system, considering cost and warranty implications were evaluated. Also, the performance enhancement of an aircraft avionics system was examined focusing on the impact of maintenance practices on system reliability. The analysis of these systems uses Markov processes, supplementary variable techniques, and Laplace transformation. Overall, the study shows how to assess and improve system reliability through integrated methods like Laplace transformations, Markov processes, and supplementary variable techniques. It offers an adequate basis for further reliability evaluations by illuminating important aspects of system behavi