Based on the results of research in physical asset management, Maintenance, Replacement, and Reliability: Theory and Applications introduces students to the tools for making data-driven decisions and how to use them. The book offers a solid theoretical foundation for these tools, demonstrating applications through various case studies. Firmly rooted in reality, the applications covered relate to areas such as food processing, the military, mining, transportation, steel, and petrochemical and pharmaceutical industries. Ideal for classroom use, this text features supplementary software that can be downloaded from the CRC Web site. The downloadable educational versions of software packages include: OREST, SMS, EXAKT for CBM optimization, PERDEC, Workshop Simulator, Crew Size Optimizer, and WiebullSoft.
This book can be used as a textbook for a one-semester senior undergraduate or postgraduate course on maintenance decision analysis. It provides problem sets with answers at the end of each chapter, an extensive set of PowerPoint slides covering the various chapters and appendices, a solutions manual for the problems in the book, and a bank of more than 100 examination questions. Instructors who adopt the book can obtain these resources at www.crcpress.com.
The authors approach the topic with the ideology that mathematical modeling is not a spectator sport. Their examination of the underpinning theories for formulating models and exploration of real-world applications make the book both informative and practical. It provides professors with the tools they need to easily teach their students how to transform data into information.
Introduction
From Maintenance Management to Physical Asset Management
The Challenges of Physical Asset Management
Improving Physical Asset Management
Reliability through the Operator: Total Productive Maintenance
Reliability by Design: Reliability-Centered Maintenance
Optimizing Maintenance and Replacement Decisions
The Quantitative Approach
References
Component Replacement Decisions
Introduction
Optimal Replacement Times for Equipment Whose Operating Cost Increases with Use
Stochastic Preventive Replacement: Some Introductory Comments
Optimal Preventive Replacement Interval of Items Subject to Breakdown (Also Known as the Group or Block Policy
Optimal Preventive Replacement Age of an Item Subject to Breakdown
Optimal Preventive Replacement Age of an Item Subject to Breakdown, Taking Account of the Times Required to Effect Failure and Preventive Replacements
Optimal Preventive Replacement Interval or Age of an Item Subject to Breakdown: Minimization of Downtime
Group Replacement: Optimal Interval between Group Replacements of Items that Are Subject to Failure: The Lamp Replacement Problem
Further Replacement Models
Spare Parts Provisioning: Preventive Replacement Spares
Spare Parts Provisioning: Insurance Spares
Solving the Constant-Interval and Age-Based Models Graphically: Use of Glasser’s Graphs
Solving the Constant-Interval and Age-Based Models Using the OREST Software
References
Problems
Inspection Decisions
Introduction
Optimal Inspection Frequency: Maximization of Profit
Optimal Inspection Frequency: Minimization of Downtime
Optimal Inspection Interval to Maximize the Availability of Equipment Used in Emergency Conditions, Such as a Protective Device
Optimizing Condition-Based Maintenance (CBM) Decisions References
Problems
Capital Equipment Replacement Decisions
Introduction
Optimal Replacement Interval for Capital Equipment: Minimization of Total Cost
Optimal Replacement Interval for Capital Equipment: Maximization of Discounted Benefits
Optimal Replacement Interval for Capital Equipment Whose Planned Utilization Pattern Is Variable: Minimization of Total Cost
Optimal Replacement Policy for Capital Equipment Taking into Account Technological Improvement: Finite Planning Horizon
Optimal Replacement Policy for Capital Equipment Taking into Account Technological Improvement: Infinite Planning Horizon
Software for Economic Life Optimization
References
Problems
Maintenance Resource Requirements
Introduction
Queuing Theory Preliminaries
Optimal Number of Workshop Machines to Meet a Fluctuating Workload
Optimal Mix of Two Classes of Similar Equipment (such as Medium/Large Lathes) to Meet a Fluctuating Workload
Rightsizing a Fleet of Equipment: An Application
Optimal Size of a Maintenance Workforce to Meet a Fluctuating Workload, Taking Account of Subcontracting Opportunities
The Lease or Buy Decision
References
Problem
Appendix 1: Statistics Primer Appendix 2: Weibull Analysis Appendix 3: Time Value of Money: Discounted Cash Flow Analysis Appendix 4: List of Applications of Maintenance Decision Optimization Models Appendix 5: Ordinates of the Standard Normal Distribution Appendix 6: Areas in the Tail of the Standard Normal Distribution Appendix 7: Values of Gamma Function Appendix 8: Median Ranks Table Appendix 9: Five Percent Ranks Table Appendix 10: Ninety-Five Percent Ranks Table Appendix 11: Critical Values for the Kolmogorov–Smirnov Statistic (d) Appendix 12: Answers to Problems Index
