AbstractsEngineering

With the development of technology the reliability problem has become a greater concern newlinebecause of high tech industrial process with ever increasing level of sophistication comprises most engineering systems Technological developments lead to an increase in the number of complicated systems as well as an increase in the complexity of the system themselves With remarkable advancements made in engineering systems became more and more sophisticated Because of their varied nature these problems have attracted the attention of scientists from various disciplines especially the system engineers Reliability theory deals with the methods and techniques to ensure the maximum effectiveness of the system Depending on the nature of research a stochastic analysis is made based on some good probability models but ultimately the goal is to give a numerical estimate of the reliability characteristics An attempt is made in this thesis to analyze the stochastic models with the aim of improving the accuracy and applicability of reliability predictions for complex repairable systems After an extensive literature review several limitations in the existing research have been identified On the basis of these limitations nine models for various types of systems such as industrialbased engineering systems manufacturing systems incorporating various types of failuresnamely partial failure major failure minor failure common cause failure human failure catastrophic failure etc have been developed newlineChapter one Introduction and Statement of the Problem is introductory in nature and gives a review of the terms and techniques used in the analysis of reliability systems Chapter two newlinedescribes the critical review of literature related to the work Some research gaps identified newlineafter the review have also been given in this chapter Chapter three describes the stochastic newlinebehavior of a complex repairable system having three units in a parallel configuration with newlinemulti state failures Chapter four describes three different models Advisors/Committee Members: Dr. Mangey Ram.