Advanced Techniques for Maintenance Modeling and Reliability Analysis of Repairable Systems E-Book
Garima Sharma
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
ADVANCED TECHNIQUES FOR MAINTENANCE MODELING AND RELIABILITY ANALYSIS OF REPAIRABLE SYSTEMS This book covers advanced models and methodologies for reliability analysis of large, complex, and critical repairable systems that undergo imperfect maintenance actions in industries having MRO facilities and also covers real-life examples from the field of aviation. The content presented in this book is inspired by the existing limitations of the generalized renewal process (GRP) model and the problems confronted by the maintenance, repair, and operations (MRO) facilities in industries dealing with large and complex repairable systems. Through this book, the authors have attempted to equip the MRO facilities with more advanced scientific tools and techniques by addressing various limitations related to the reliability analysis of repairable systems. The book is dedicated to various imperfect maintenance-based virtual age models and methodologies to bridge various research gaps present in the available literature. A summary of deliverables is as follows: * Presents the basic concepts of maintenance and provides a virtual age model that can accommodate all maintenance; * Provides the basic concepts of censoring in repairable systems along with the concept of black box and failure modes. Also highlighted is how the proposed work will be useful for industries conducting failure modes and effect analysis (FMEA) and estimating the mean residual life (MRL) of repairable systems; * Presents methodology that applies risk-based threshold on intensity function and provides a threshold to declare the system/component as high failure rate components (HFRCs); * Identifying a system as HFRCs is an important task, but for an industry dealing with critical systems, preventing the system from being HFRC is more important, since the risk involved in such systems would be very high. Thus, the book presents a progressive maintenance policy (PMP) for repairable systems; * Focusses on qualitative analysis of repair quality. Assuming repair quality as a subjective variable, the authors have presented various factors that affect the repair quality most and modeled their interdependency using Bayesian networks (BN). Audience Professional reliability engineers, reliability administrators, consultants, managers, and post-graduate students in engineering schools. The book belongs to any engineering, technical, and academic institution concerned with manufacturing, production, aviation, defense, and software industries.
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Veröffentlichungsjahr: 2023
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Table of Contents
Cover
Table of Contents
Series Page
Title Page
Copyright Page
List of Figures
List of Tables
Preface
1 Maintenance, Repair, and Overhaul
1.1 Introduction
1.2 Maintenance
1.3 Repair
1.4 Overhaul
1.5 Chapter Summary
References
2 Repairable Systems
2.1 Introduction to Repairable Systems and Its Terminologies
2.2 Maintenance Actions on Repairable Systems
2.3 Classifications of Maintenance Categories
2.4 Concept of Censoring
2.5 Problems Faced by the Industries: Present Scenario
2.6 Chapter Summary
References
3 Imperfect Overhaul Virtual Age Model
3.1 Introduction
3.2 Need for an Imperfect Overhaul
3.3 Imperfect Overhaul Virtual Age Model (IOVAM)
3.4 Chapter Summary
References
4 Techniques for Modeling and Analysis of Censored Data Considering the FM Approach
4.1 Introduction
4.2 Problem Background
4.3 Basic Terminologies
4.4 Representation and Analysis of Cases
4.5 Models for FM-Wise Censored Data Analysis for Repairable Systems
4.6 An Industrial Perspective of Technique
4.7 Chapter Summary
References
5 Methodology for Identifying HFRCs Considering Risk-Based Threshold on Intensity Function
5.1 Introduction
5.2 Methodology for Risk-Based Threshold on Intensity Function for HFRC Designation
5.3 Chapter Summary
References
6 Progressive Maintenance Policy
6.1 Introduction
6.2 Progressive Maintenance Policy (PMP)
6.3 PMP Methodology
6.4 Chapter Summary
References
7 Age-Based Maintenance Policies for Repairable Systems
7.1 Introduction
7.2 Age-Based Policies for Repairable Systems
7.3 Chapter Summary
References
8 Study and Modeling of Factors Affecting the REI of Repairable Systems
8.1 Introduction
8.2 Limitations of the Quantitative Assessment of RE
8.3 Investigation of Factor/Subfactors Affecting RE
8.4 Tool Chosen for the Analysis
8.5 Chapter Summary
References
Appendix A
Appendix B
Appendix C
Appendix D
Appendix E
Index
Also of Interest
End User License Agreement
List of Tables
Chapter 1
Table 1.1 Key areas of maintenance and replacement decisions (Jardine and Ts...
Table 1.2 Correlation of the industrial revolution and maintenance (Coleman,...
Chapter 3
Table 3.1 Data description of the turbo starter and plunger pump.
Table 3.2 Virtual age estimation using IOVAM with imperfect SPM, CM, and ove...
Table 3.3 Reliability parameters estimation using different models for turbo...
Table 3.4 Reliability parameters estimation using different models for plung...
Table 3.5 Aero engine failure times in hours.
Chapter 4
Table 4.1 Representation of censored data for case I.
Table 4.2 Representation of censored data for case II: the black box approac...
Table 4.3 Representation of censored data for case II: the failure mode appr...
Table 4.4 Representation of censored data for case III.
Table 4.5 Virtual age estimation for model I.
Table 4.6 Virtual age estimation for model II.
Table 4.7 Conversion of FM-wise censored models into existing ones.
Table 4.8 Comparison matrix for existing and FM-wise censored models.
Table 4.9 Data description of the three identical aero engines.
Table 4.10 Data description of the three identical aero engines.
Table 4.11 Model parameters estimated from the models for the considered dat...
Table 4.12 Time to failures of air conditioning unit.
Chapter 5
Table 5.1 Time of Intervention (TOI) data since new for series 1 aero engine...
Table 5.2 Time Of Intervention (TOI) data since new for series 2 aero engine...
Table 5.3 Estimated parameters.
Table 5.4 Threshold parameters considering constant
Z
in series 1.
Table 5.5 Threshold parameters considering constant
X
in series 1.
Table 5.6 Threshold parameters considering constant
Z
in series 2.
Table 5.7 Threshold parameters considering constant
X
in series 2.
Table 5.8 Failure data (flight hours) for jet engine.
Chapter 6
Table 6.1 Progressive maintenance plan for series 1 aero engines.
Table 6.2 Progressive maintenance plan for series 2 aero engines.
Table 6.3 Comparative results for series 1 aero engines.
Table 6.4 Comparative results for series 2 aero engines.
Table 6.5 Comparative study between classic and progressive maintenance poli...
Chapter 7
Table 7.1 Time to failure data.
Table 7.2 Estimated reliability parameters for policies I and II.
Table 7.3 Estimated optimal overhaul time for policies I and II.
Table 7.4 Estimated spare parts for policies I and II.
Table 7.5 Time to failures of aero engine.
Chapter 8
Table 8.1 Estimated parameters of the two failure modes of aero engine.
Table 8.2 Expected RE values to decrease failure probability.
Table 8.3 Defined states of each factor/subfactor.
Table 8.4 Normalized weights obtained from pairwise comparison.
Table 8.5 Results using the BN model.
Table 8.6 List of evidence.
List of Illustrations
Chapter 1
Figure 1.1 Activities in maintenance management function.
Figure 1.2 Example of a functionability profile in a series system.
Figure 1.3 The maintainability design process.
Figure 1.4 Flowchart of the FMEA/CA.
Figure 1.5 The pillars of TPM.
Figure 1.6 The RCM process (Jardine and Tsand, 2005).
Figure 1.7 Types of maintenance.
Figure 1.8 System failure (Jardine and Tsand, 2005).
Figure 1.9 Basic O&M intervention process to retain or restore technical syste...
Figure 1.10 Types of failure.
Figure 1.11 Minimal and general repair (Jardine and Tsand, 2005).
Figure 1.12 Various techniques for reliability analysis (Rai, Chaturvedi, and ...
Figure 1.13 Optimizing minimal and general repair decisions (Jardine and Tsand...
Figure 1.14 Major overhaul flowchart.
Chapter 2
Figure 2.1 The bathtub curve for repairable systems.
Figure 2.2 Types of maintenance actions.
Figure 2.3 Steps for corrective maintenance.
Figure 2.4 Conditional probability density function for NHPP (Yanez, Joglar, a...
Figure 2.5 Conversion of GRP into other models.
Chapter 3
Figure 3.1 Imperfect CM, SPM, and overhaul in the IOVAM model.
Figure 3.2 Modifications of the IOVAM.
Figure 3.3 Incorporation of other models in the IOVAM.
Figure 3.4 Intensity function graph of the turbo starter considering perfect (...
Figure 3.5 Intensity function graph of the plunger pump considering perfect (N...
Figure 3.6 Availability graph of the turbo starter considering perfect (Nasr
e
...
Figure 3.7 Availability graph of the plunger pump considering perfect (Nasr
et
...
Figure 3.8 The turbo starter virtual age sensitivity graphs considering differ...
Figure 3.9 The plunger pump virtual age sensitivity graphs considering differe...
Figure 3.10 The turbo starter intensity function sensitivity graphs considerin...
Figure 3.11 The plunger pump intensity function sensitivity graphs considering...
Chapter 4
Figure 4.1 The black box approach for censored data.
Figure 4.2 (a) The failure mode approach for repairable systems; (b) the failu...
Figure 4.3 Notations for various intervention times.
Figure 4.4 Representation of case I: (a) black box approach and (b) failure mo...
Figure 4.5 Representation of case II: the black box approach.
Figure 4.6 Representation of case II: the failure mode approach (a) considerin...
Figure 4.7 Representation of case III: (a) the black box approach and (b) the ...
Figure 4.8 (a) Model I and (b) model II.
Figure 4.9 Intensity function graphs of the system considering dominant FMs.
Chapter 5
Figure 5.1 Classic PM policy.
Figure 5.2 Representation of threshold parameters.
Figure 5.3 Variation threshold parameters keeping
Z
constant in series 1.
Figure 5.4 Variation in threshold parameters keeping
X
constant in series 1.
Figure 5.5 Variation in threshold parameters keeping
Z
constant in series 2.
Figure 5.6 Variation in threshold parameters keeping
X
constant in series 2.
Chapter 6
Figure 6.1 PMP for (a) series 1 aero engines and (b) series 2 aero engines.
Figure 6.2 Availability trend for series 1 aero engines: (a) classic PM policy...
Figure 6.3 Availability trend for series 2 aero engines: (a) classic PM policy...
Chapter 7
Figure 7.1 (a) Single repairable system and (b) multiple repairable systems.
Figure 7.2 Age-based overhaul period estimation with imperfect CM (policy I).
Figure 7.3 Age-based overhaul period estimation with imperfect CM and SPM (pol...
Figure 7.4 Present maintenance policy.
Chapter 8
Figure 8.1 The BN model for factors affecting RE.
Figure 8.2 The Bayesian network model.
Figure 8.3 Analysis of the results obtained from the BN model.
Guide
Cover
Series Page
Title Page
Copyright Page
List of Figures
List of Tables
Preface
Table of Contents
Begin Reading
Appendix A
Appendix B
Appendix C
Appendix D
Appendix E
Index
Also of Interest
Wiley End User License Agreement
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Scrivener Publishing100 Cummings Center, Suite 541JBeverly, MA 01915-6106
Publishers at ScrivenerMartin Scrivener ([email protected])Phillip Carmical ([email protected])
Advanced Techniques for Maintenance Modeling and Reliability Analysis of Repairable Systems
Garima Sharma
Senior Reliability Engineer, Valeo India Pvt. Ltd., Chennai, India
and
Rajiv Nandan Rai
Subir Chowdhury School of Quality and Reliability, Indian Institute of Technology, Kharagpur, India
This edition first published 2023 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA© 2023 Scrivener Publishing LLCFor more information about Scrivener publications please visit www.scrivenerpublishing.com.
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Library of Congress Cataloging-in-Publication Data
ISBN 978-1-394-17443-0
Cover image: Pixabay.ComCover design by Russell Richardson
List of Figures
Figure 1.1
Activities in maintenance management function.
Figure 1.2
Example of a functionability profile in a series system.
Figure 1.3
The maintainability design process.
Figure 1.4
Flowchart of the FMEA/CA.
Figure 1.5
The pillars of TPM.
Figure 1.6
The RCM process (Jardine and Tsand, 2005).
Figure 1.7
Types of maintenance.
Figure 1.8
System failure (Jardine and Tsand, 2005).
Figure 1.9
Basic O&M intervention process to retain or restore technical systems and equipment of an industrial asset in an acceptable technical condition.
Figure 1.10
Types of failure.
Figure 1.11
Minimal and general repair (Jardine and Tsand, 2005).
Figure 1.12
Various techniques for reliability analysis (Rai, Chaturvedi, and Bolia, 2020).
Figure 1.13
Optimizing minimal and general repair decisions (Jardine and Tsand, 2005).
Figure 1.14
Major overhaul flowchart.
Figure 2.1
The bathtub curve for repairable systems.
Figure 2.2
Types of maintenance actions.
Figure 2.3
Steps for corrective maintenance.
Figure 2.4
Conditional probability density function for NHPP (Yanez, Joglar, and Modarres, 2002).
Figure 2.5
Conversion of GRP into other models.
Figure 3.1
Imperfect CM, SPM, and overhaul in the IOVAM model.
Figure 3.2
Modifications of the IOVAM.
Figure 3.3
Incorporation of other models in the IOVAM.
Figure 3.4
Intensity function graph of the turbo starter considering perfect (Nasr
et al
. model), imperfect (IOVAM), and minimal (NHPP) overhaul.
Figure 3.5
Intensity function graph of the plunger pump considering perfect (Nasr
et al
. model), imperfect (IOVAM), and minimal (NHPP) overhaul.
Figure 3.6
Availability graph of the turbo starter considering perfect (Nasr
et al
. model), imperfect (IOVAM), and minimal (NHPP) overhaul.
Figure 3.7
Availability graph of the plunger pump considering perfect (Nasr
et al
. model), imperfect (IOVAM), and minimal (NHPP) overhaul.
Figure 3.8
The turbo starter virtual age sensitivity graphs considering different values of q
0
.
Figure 3.9
The plunger pump virtual age sensitivity graphs considering different values of q
0
.
Figure 3.10
The turbo starter intensity function sensitivity graphs considering different values of q
0
.
Figure 3.11
The plunger pump intensity function sensitivity graphs considering different values of q
0
.
Figure 4.1
The black box approach for censored data.
Figure 4.2
(a) The failure mode approach for repairable systems; (b) the failure mode approach for repairable systems with an imperfect SPM.
Figure 4.3
Notations for various intervention times.
Figure 4.4
Representation of case I: (a) black box approach and (b) failure mode approach.
Figure 4.5
Representation of case II: the black box approach.
Figure 4.6
Representation of case II: the failure mode approach (a) considering any three failures of any FM and (b) considering three failures of interested FM only.
Figure 4.7
Representation of case III: (a) the black box approach and (b) failure mode approach.
Figure 4.8
(a) Model I and (b) model II.
Figure 4.9
Intensity function graphs of the system considering dominant FMs.
Figure 5.1
Classic PM policy.
Figure 5.2
Representation of threshold parameters.
Figure 5.3
Variation threshold parameters keeping
Z
constant in series 1.
Figure 5.4
Variation in threshold parameters keeping
X
constant in series 1.
Figure 5.5
Variation in threshold parameters keeping
Z
constant in series 2.
Figure 5.6
Variation in threshold parameters keeping
X
constant in series 2.
Figure 6.1
PMP for (a) series 1 aero engines and (b) series 2 aero engines.
Figure 6.2
A vailability trend for series 1 aero engines: (a) classic PM policy and (b) PMP.
Figure 6.3
A vailability trend for series 2 aero engines: (a) classic PM policy and (b) PMP.
Figure 7.1
(a) Single repairable system and (b) multiple repairable systems.
Figure 7.2
Age-based overhaul period estimation with imperfect CM (policy I).
Figure 7.3
Age-based overhaul period estimation with imperfect CM and SPM (policy II).
Figure 7.4
Present maintenance policy.
Figure 8.1
The BN model for factors affecting RE.
Figure 8.2
The Bayesian network model.
Figure 8.3
Analysis of the results obtained from the BN model.
List of Tables
Table 1.1
Key areas of maintenance and replacement decisions (Jardine and Tsand, 2005).
Table 1.2
Correlation of the industrial revolution and maintenance (Coleman, 1956).
Table 3.1
Data description of the turbo starter and plunger pump.
Table 3.2
Virtual age estimation using IOVAM with imperfect SPM, CM, and overhaul.
Table 3.3
Reliability parameters estimation using different models for turbo starter (three overhaul cycle data).
Table 3.4
Reliability parameters estimation using different models for plunger pump (three overhaul cycle data).
Table 3.5
Aero engine failure times in hours.
Table 4.1
Representation of censored data for case I.
Table 4.2
Representation of censored data for case II: the black box approach.
Table 4.3
Representation of censored data for case II: the failure mode approach.
Table 4.4
Representation of censored data for case III.
Table 4.5
Virtual age estimation for model I.
Table 4.6
Virtual age estimation for model II.
Table 4.7
Conversion of FM-wise censored models into existing ones.
Table 4.8
Comparison matrix for existing and FM-wise censored models.
Table 4.9
Data description of the three identical aero engines.
Table 4.10
Data description of the three identical aero engines.
Table 4.11
Model parameters estimated from models for the considered data set.
Table 4.12
Time to failures of air conditioning unit.
Table 5.1
Time of Intervention (TOI) data since new for series 1 aero engines.
Table 5.2
Time of Intervention (TOI) data since new for series 2 aero engines.
Table 5.3
Estimated parameters.
Table 5.4
Threshold parameters considering constant
Z
in series 1.
Table 5.5
Threshold parameters considering constant
X
in series 1.
Table 5.6
Threshold parameters considering constant
Z
in series 2.
Table 5.7
Threshold parameters considering constant
X
in series 2.
Table 5.8
Failure data (flight hours) for jet engine.
Table 6.1
Progressive maintenance plan for series 1 aero engines.
Table 6.2
Progressive maintenance plan for series 2 aero engines.
Table 6.3
Comparative results for series 1 aero engines.
Table 6.4
Comparative results for series 2 aero engines.
Table 6.5
Comparative study between classic and progressive maintenance policies.
Table 7.1
Time to failure data.
Table 7.2
Estimated reliability parameters for policies I and II.
Table 7.3
Estimated optimal overhaul time for policies I and II.
Table 7.4
Estimated spare parts for policies I and II.
Table 7.5
Time to failures of aero engine.
Table 8.1
Estimated parameters of the two failure modes of aero engine.
Table 8.2
Expected RE values to decrease failure probability.
Table 8.3
Defined states of each factor/subfactor.
Table 8.4
Normalized weights obtained from pairwise comparison.
Table 8.5
Results using the BN model.
Table 8.6
List of evidence.
Preface
The necessity of reliability and maintenance modeling and analysis of repairable systems has been showing an increasing trend due to the complexity of such systems. Repairable systems are the systems that can be restored to an operating condition after failure by any method other than the replacement of whole system. Moreover, they undergo various preventive maintenances (PM) and are often subjected to imperfect maintenance. To undertake the reliability analysis of repairable systems, most of the industries establish their own set up of maintenance, repair, and overhaul (MRO) facilities.
Before laying hands on this book, the authors realized that though various models and maintenance policies are available for the repairable systems, they still lack in providing the solutions to the real-time industrial problems. The models and maintenance policies that can be directly implemented are to be developed. The authors then undertook the task of developing such reliability models and maintenance policies that could be very much useful and beneficial for conducting advanced reliability analysis of repairable systems.
This book provides a framework for the modeling and analysis of repairable systems considering parametric estimation of the failure data. The book provides due exposure to the advanced generalized renewal process (GRP) based models and maintenance policies along with its applications to repairable systems data from aviation industry. The book also covers the dependency modeling of various factors that affect the repair effectiveness of the system. This text is intended to be useful for senior undergraduate, graduate and post graduate students in engineering schools and also for professional engineers, reliability administrators and managers.
This text has primarily emerged from the industrial and research experience of the authors. A number of illustrations have been included to make the subject pellucid and vivid especially to the readers who are new to this area. Various examples have been provided to showcase the applicability of presented models and methodologies to assist the reader in applying the concepts presented in this book.
The basic concepts of reliability analysis of repairable systems and generalized renewal process (GRP) can readily be seen in various available texts that deal with reliability analysis of repairable systems. The reliability literature is plentiful covering such aspects in reliability data analysis where the failure times are modeled by appropriate life distributions. Hence, the reader is advised to refer to any such textbook on repairable systems reliability analysis for a better comprehension of this book.
Chapter 1 introduces the reader to the basics of maintenance, repair and overhaul (MRO). by providing a preview of the fundamental understanding of MRO, so that it will be easier to integrate the knowledge of the advanced reliability techniques in dealing with reliability analysis of repairable systems, which forms the main theme of this book.
Chapter 2 provides an overview of basic concepts and the terminologies used in repairable system reliability analysis, types of maintenance along with the GRP based imperfect maintenance models available in the literature.
Chapter 3 presents a virtual age model considering scheduled preventive maintenance (SPM), corrective maintenance (CM) and overhaul as imperfect. The chapter also describes the activities done during SPM and overhaul along with the need for imperfect overhaul assumption. The model is demonstrated with the help of field failure data of aero engines.
Chapter 4 explains a technique and virtual age models to deal with failure modes (FM) wise censored data of repairable systems. The chapter also highlights the need for this particular technique in industries.
Chapter 5 presents a methodology for risk-based threshold on intensity function for the identification of high failure rate components (HFRCs). The chapter brings out the limitations of the present methods of HFRC designation.
Chapter 6 provides a maintenance policy called progressive maintenance policy (PMP) for large and critical repairable systems. The policy is demonstrated using the same data set as utilized in chapter 5. The superiority of the policy is discussed by comparing it with the conventional maintenance policies followed by the aviation industries in the Indian context.
Chapter 7 presents an age-based maintenance policy to obtain the optimal overhaul time for repairable systems considering CM and SPM and imperfect. The chapter also provides the spare parts estimation model based on virtual age concept.
Chapter 8 brings out the limitations of quantitative assessment over the qualitative assessment of repair effectiveness index (REI) and presents various subjective factors which can affect REI the most. As an example, a dependency model with the help of the Bayesian network (BN) is developed to model their inter-dependency with each other and REI.
The book makes an comprehensive attempt to provide a coverage to various models and methodologies that can be used for advanced modeling and analysis of repairable systems reliability analysis. However, there is always a scope for improvement and we are looking forward to receiving critical reviews and/or comments of the book from students, teachers, and practitioners. We hope readers will all gain as much knowledge, understanding and pleasure from reading this book as we have from writing it.
Garima SharmaRajiv Nandan Rai
1Maintenance, Repair, and Overhaul: A Preview
1.1 Introduction
To undertake the reliability analysis of repairable systems, most of the industries establish their own setup of maintenance, repair, and overhaul (MRO) facilities. Before we embark upon the remaining contents of the book, the authors thought it imperative to introduce the readers to the basics of maintenance, repair, and overhaul. This chapter provides a preview of the fundamental understanding of MRO so that it will be easier to assimilate the comprehension of the advanced reliability techniques to deal with repairable systems, which has been endeavored in this book.
Maintenance, repair, and overhaul, or MRO, provides life cycle maintenance through routine preventive maintenance, planned out-of-service maintenance, or (corrective) repairs, overhaul, or rebuilds for damaged equipment. Even though industries account for the majority of them, a product or piece of equipment with high costs and a long lifespan is definitely a candidate for MRO services. Examples include massive manufacturing machinery, electric power generation, marine boats and infrastructure, mass transit vehicles, military vehicles, and systems.
Industrial systems generally deteriorate over time due to use and exposure to environmental factors. This deterioration eventually results in system failure, which in turn causes safety problems, equipment damage, quality problems, and unplanned machine downtime. A few decades ago, maintenance was mainly thought of as something challenging to manage and had to be done after a failure. Maintenance is widely acknowledged as a crucial component of asset management and a crucial commercial function. Organizations are becoming more aware of how maintenance intervention planning may increase their productivity and reliability. Preventive maintenance activities increase as a result and better fit with other business processes like production scheduling and spare parts management. For instance, companies in the process and chemical sectors can significantly boost profitability by preventing unscheduled stoppages. The continuous automation of production processes and an intensifying level of competition in the market have increased awareness of the need for good maintenance planning.
Keeping facility equipment, tools, and infrastructure in good condition and operating them efficiently is the objective of anybody who works in maintenance. This helps to prevent unanticipated downtime or equipment failure. This is what repair and maintenance allow us to do. Although the terms repair and maintenance are sometimes used interchangeably, they have various meanings in the asset management industry. When an asset breaks, is damaged, or ceases to function, repairs are restorative work that must be done. Routine tasks and/or corrective or preventive repairs performed on assets to avoid damage and extend life expectancy are referred to as maintenance. Examples include routinely cleaning grease traps, and air conditioning units, painting, and inspections.
