Reliability Theory : With Applications to Preventive Maintenance

Ilya Gertsbakh

ISBN 10: 3540672753 / ISBN 13: 9783540672753

Edité par Springer-Verlag GmbH, 2005

A propos de cet article

Zustand: Gut | Sprache: Englisch | Produktart: Bücher.

N° de réf. du vendeur 323597/3

Détails bibliographiques

• Titre: Reliability Theory : With Applications to Preventive Maintenance
• Éditeur: Springer-Verlag GmbH
• Date de parution: 2005
• Langue: anglais
• ISBN à 10 chiffres: 3540672753
• ISBN à 13 chiffres: 9783540672753
• Reliure: Couverture rigide
• Édition: 2ème Édition
• État de l'article: Gut
• Catalogues du vendeur:
  • Bücher

A propos de ce titre

Synopsis

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.