TY  - BOOK
AU  - Nakagawa,Toshio
ED  - SpringerLink (Online service)
TI  - Random Maintenance Policies
T2  - Springer Series in Reliability Engineering,
SN  - 9781447165750
AV  - T55.4-60.8 
U1  - 670 23
PY  - 2014///
CY  - London
PB  - Springer London, Imprint: Springer
KW  - engineering
KW  - Mechanical engineering
KW  - System safety
KW  - Structural control (Engineering)
KW  - Engineering
KW  - Operating Procedures, Materials Treatment
KW  - Quality Control, Reliability, Safety and Risk
KW  - Facility Management
KW  - Mechanical Engineering
N1  - Ch 1 Introduction -- Ch 2 Random Age Replacement Policies -- Ch 3 Random Periodic Replacement Policies -- Ch 4 Random Preventive Maintenance Policies -- Ch 5 Random Inspection Policies -- Ch 6 Random Redundant Systems -- Ch 7 Random Backup Policies -- Ch 8 Random Scheduling -- Ch 9 Cumulative Damage Models -- Ch 10 Random Models
N2  - Exploring random maintenance models, this book provides an introduction to the implementation of random maintenance, and it is one of the first books to be written on this subject.  It aims to help readers learn new techniques for applying random policies to actual reliability models, and it provides new theoretical analyses of various models including classical replacement, preventive maintenance and inspection policies. These policies are applied to scheduling problems, backup policies of database systems, maintenance policies of cumulative damage models, and reliability of random redundant systems. Reliability theory is a major concern for engineers and managers, and in light of Japan’s recent earthquake, the reliability of large-scale systems has increased in importance. This also highlights the need for a new notion of maintenance and reliability theory, and how this can practically be applied to systems. Providing an essential guide for engineers and managers specializing in reliability maintenance and quality control, this book provides a useful resource for those with doubts carrying out maintenance of new and large systems. It is also intended for graduate students and researchers interested in operations research, statistics, industrial engineering and management science
UR  - http://dx.doi.org/10.1007/978-1-4471-6575-0
ER  -