| Reliability Theory: With Applications to Preventive Maintenance 2000. Corr. 2nd Edition Contributor(s): Gertsbakh, Ilya (Author) |
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ISBN: 3540672753 ISBN-13: 9783540672753 Publisher: Springer OUR PRICE: $52.24 Product Type: Hardcover - Other Formats Published: September 2000 Annotation: This textbook on Reliability Theory focusses on Applications in Preventive Maintenance (PM). All models are presented in connection with the relevant statistical material. Short and simply written the book is almost self-contained. The reader needs not more than basic knowledge of calculus, probability and statistics. Each chapter is concluded by a series of exercices with detailed solutions. Numerical solutions are elaborated with Mathematica software. Novel topics are discussed, like PM with learning, choice of the best time-scale for PM, handling multidimensional state description, dealing with uncertainty in data. The book is meant for graduate students, researchers and engineers specializing in Quality Control, Logistics, Reliability and Maintenance Engineering. |
| Additional Information |
| BISAC Categories: - Technology & Engineering | Industrial Engineering - Mathematics | Probability & Statistics - General - Technology & Engineering | Quality Control |
| Dewey: 519.2 |
| LCCN: 00045713 |
| Physical Information: 0.56" H x 6.14" W x 9.21" (1.12 lbs) 219 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |
