Maintenance has an essential role in ensuring that engineering systems perform at expected levels of reliability, availability and safety in a cost effective manner and in keeping with the corporate demands.
A review of extensive research in the field of maintenance indicates that most models either have over-simplified assumptions or are analytically and computationally too intensive for practical application. Optimal Maintenance of Large Engineering System endeavors to address this anomaly for the maintenance decision maker and researcher.
The book brings under one roof, a critical discussion on the classical and contemporary analysis of maintenance models, presentation of maintenance decision as a multi-objective optimization problem using genetic algorithms and use for fuzzy logic for handling uncertainty and expert opinion or domain knowledge with particular reference to maintenance of large engineering systems.
There are also necessary inputs to equip the readers with the necessary skills, such as genetic algorithms, fuzzy sets, bayesian statistics, etc., as well as a detailed exposure to tools and techniques for maintenance planning and management, CMMS and expert systems.
Table of Contents
• Foreword
•
• Preface
• Introduction
• Modeling for Maintenance Decisions
• Maintenance of Large Engineering Systems: A Multi-Criteria Decision Problem
• Multi-Objective Maintenance Optimization using Genetic Algorithms
• Uncertainties in Maintenance Decisions
• Fuzzy Maintenance Decision Making
• Spare Parts Inventory Decisions
• Maintenance Costing
• Maintenance Planning Tools and Strategies.
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A. Srividya.: Professor, Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai Ajit K. Verma.: Professor, University College, Haugesund, Norway P. G. Ramesh.: PhD (Reliability Engineering), Indian Institute of Technology Bombay, Mumbai
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