Bøger af Ilya Gertsbakh

The material in this book was first presented as a one-semester course in Relia­ bility Theory and Preventive Maintenance for M.Sc. students of the Industrial Engineering Department of Ben Gurion University in the 1997/98 and 1998/99 academic years. Engineering students are mainly interested in the applied part of this theory. The value of preventive maintenance theory lies in the possibility of its imple­ mentation, which crucially depends on how we handle statistical reliability data. The very nature of the object of reliability theory - system lifetime - makes it extremely difficult to collect large amounts of data. The data available are usu­ ally incomplete, e.g. heavily censored. Thus, the desire to make the course material more applicable led me to include in the course topics such as mod­ eling system lifetime distributions (Chaps. 1,2) and the maximum likelihood techniques for lifetime data processing (Chap. 3). A course in the theory of statistics is aprerequisite for these lectures. Stan­ dard courses usually pay very little attention to the techniques needed for our purpose. A short summary of them is given in Chap. 3, including widely used probability plotting. Chapter 4 describes the most useful and popular models of preventive main­ tenance and replacement. Some practical aspects of applying these models are addressed, such as treating uncertainty in the data, the role of data contamina­ tion and the opportunistic scheduling of maintenance activities.

This introductory book equips the reader to apply the core concepts and methods of network reliability analysis to real-life problems. Based on the lecture notes of eight courses taught by the authors, the book is also self-contained, with no theory needed beyond the lectures.

The increase in the requirements on the reliability of units makes it necessary to analyze the relationship between mathematicalmeth ods of calculating reliability and the physical nature of fail ures.

This book deals with reliability investigations of networks whose components subject to failures can be in three states -up, down and middle (mid), contrary to traditionally considered networks having only binary (up/down) components.

This allows to develop a probabilistic follow-up analysis of the network in the process of its gradual destruction, to identify most important network components and to develop efficient heuristic algorithms for network optimal design.

Well written textbook on industrial applications of Statistical Measurement Theory. Each topic starts with an informal introduction followed by an example, the rigorous problem formulation, solution method, and a detailed numerical solution.