Reliability Analysis of Lifetime Distributions

Abstract

International standards requires huge investments at global level to develop and maintain the quality of products. The main focus of these international standards is to provide variability, reliability and objectivity among the users of these products and therefore, in the present scenario of global competition and liberalization, it is indispensable that world industries become completely responsive of the requirements to produce reliable products and design capable systems to meet international standards. The functionality of the capable system and to maintain the safety of the people using the products, a high reliability must be required as any drawback in the system leads to inconvenience, things can become even bad to worse when any adulteration or miss management in a system causes a huge economic loss. There is an utmost need for reliability of products in order to achieve good outputs with high standards and to design highly accurate systems, the dependence of reliability theory has been increasing rapidly with the recent technological exploration. The application of this theory is not restricted only to fewer areas but it is applicable to entire fields of mechanical, industrial, electronic and communication engineering, computer sciences, information, disaster management, aerospace engineering, earthquake, weather forecasting, transportation control, navigations, volcano forecasting, healthcare and defense technology and so on. newlineThe thesis has been divided into seven chapters and a comprehensive bibliography at the end newlineChapter I is devoted to the introduction of reliability theory and some lifetime distributions pre-requisite in the development of subsequent chapters. newlineChapter II discusses a new modified generalized linear failure rate distribution that generalizes various existing distributions for specific parameter setting. Some mathematical properties have been derived and the flexibility of the new distribution in the shapes of cumulative distribution function, probability density function and .....