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Risk-Based Maintenance for Electricity Network Organizations
(Englisch)
Ravish Preshant Yashraj Mehairjan

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Risk-Based Maintenance for Electricity Network Organizations

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  • Springer Basel AG
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    +41 61 2050707
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  • 274546479

Produktbeschreibung

Discusses theory as necessary, but either in parallel with extremely pragmatic examples or with reference to real industry experiences

Offers an unusual mix of research and practical application, with international context, written for easy access by a wide audience

Describes a view of maintenance management from Electricity & Gas Distribution Network Operators (DNO) not available elsewhere


Ravish P. Y. Mehairjan is an asset, risk and Lean Six Sigma change management senior professional, based in Rotterdam, the Netherlands. Dr. Mehairjan had experience in various roles as asset management specialist, advisor and project change manager in different business units. He is member and secretary of international working groups of  CIGRE and has published a number international papers and book chapter in the area of risk based maintenance management. Dr. Mehairjan earned his B.Sc (Cum Laude) from the University of Suriname in Paramaribo, Suriname and his M.Sc (Cum Laude) and Ph.D from Delft University of Technology in Delft, the Netherlands. He is a IASSC certified Lean Six Sigma Blackbelt.


This book focuses on the introduction of new and modern maintenance management frameworks of assets in the electricity & gas network sector and more specifically, on electricity networks for distribution. The author describes methodologies for developing and implementing maintenance management maturity models, using case studies to show how these have been applied. These maturity models are discussed as part of an overarching, multi-disciplinary organizational maintenance management professionalization framework. This book adds a new dimension to the well-known Reliability Centered Maintenance (RCM) method, by incorporating failure modes via multiple scenarios into business values, by means of statistical risk calculation methods. The author demonstrates a method called Utility Risk Linked RCM, which uses a statistical tool to develop failure models which can be used to predict future failure behavior of assets in relation to corporate business values. This new method is a practical, structured and comprehensive framework for assessing risk based maintenance policies. The book also proposes a condition monitoring framework that can be used as a guide to assist asset managers in identifying the relationship between failure modes, ageing processes to select amongst condition monitoring regimes.


Introduction.- Asset, Risk & Maintenance Management.- Organisation-Wide Maintenance Improvement Framework.- Risk Linked Reliability Centered Maintenance Management Model.- Statistical-Based Computational Tools for Maintenance Management.- Condition Monitoring Framework for Maintenance Management.- Conclusions & Recommendations.- Appendices.



This book focuses on the introduction of new and modern maintenance management frameworks of assets in the electricity & gas network sector and more specifically, on electricity networks for distribution. The author describes methodologies for developing and implementing maintenance management maturity models,using case studies to show how these have been applied. These maturity models are discussed as part of an overarching, multi-disciplinary organizational maintenance management professionalization framework. This book adds a new dimension to the well-known Reliability Centered Maintenance (RCM) method, by incorporating failure modes via multiple scenarios into business values, by means of statistical risk calculation methods. The author demonstrates a method called Utility Risk Linked RCM, which uses a statistical tool to develop failure models which can be used to predict future failure behavior of assets in relation to corporate business values. This new method is a practical, structured and comprehensive framework for assessing risk based maintenance policies. The book also proposes a condition monitoring framework that can be used as a guide to assist asset managers in identifying the relationship between failure modes, ageing processes to select amongst condition monitoring regimes.


Introduction.- Asset, Risk & Maintenance Management.- Organisation-Wide Maintenance Improvement Framework.- Risk Linked Reliability Centered Maintenance Management Model.- Statistical-Based Computational Tools for Maintenance Management.- Condition Monitoring Framework for Maintenance Management.- Conclusions & Recommendations.- Appendices.


Ravish P. Y. Mehairjan is an asset, risk and Lean Six Sigma change management senior professional, based in Rotterdam, the Netherlands. Dr. Mehairjan had experience in various roles as asset management specialist, advisor and project change manager in different business units. He is member and secretary of international working groups of CIGRE and has published a number international papers and book chapter in the area of risk based maintenance management. Dr. Mehairjan earned his B.Sc (Cum Laude) from the University of Suriname in Paramaribo, Suriname and his M.Sc (Cum Laude) and Ph.D from Delft University of Technology in Delft, the Netherlands. He is a IASSC certified Lean Six Sigma Blackbelt.



Über den Autor

Ravish P. Y. Mehairjan is an asset, risk and Lean Six Sigma change management senior professional, based in Rotterdam, the Netherlands. Dr. Mehairjan had experience in various roles as asset management specialist, advisor and project change manager in different business units. He is member and secretary of international working groups of  CIGRE and has published a number international papers and book chapter in the area of risk based maintenance management. Dr. Mehairjan earned his B.Sc (Cum Laude) from the University of Suriname in Paramaribo, Suriname and his M.Sc (Cum Laude) and Ph.D from Delft University of Technology in Delft, the Netherlands. He is a IASSC certified Lean Six Sigma Blackbelt.

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Inhaltsverzeichnis



Introduction.- Asset, Risk & Maintenance Management.- Organisation-Wide Maintenance Improvement Framework.- Risk Linked Reliability Centered Maintenance Management Model.- Statistical-Based Computational Tools for Maintenance Management.- Condition Monitoring Framework for Maintenance Management.- Conclusions & Recommendations.- Appendices.


Klappentext



This book focuses on the introduction of new and modern maintenance management frameworks of assets in the electricity & gas network sector and more specifically, on electricity networks for distribution. The author describes methodologies for developing and implementing maintenance management maturity models,using case studies to show how these have been applied. These maturity models are discussed as part of an overarching, multi-disciplinary organizational maintenance management professionalization framework. This book adds a new dimension to the well-known Reliability Centered Maintenance (RCM) method, by incorporating failure modes via multiple scenarios into business values, by means of statistical risk calculation methods. The author demonstrates a method called Utility Risk Linked RCM, which uses a statistical tool to develop failure models which can be used to predict future failure behavior of assets in relation to corporate business values. This new method is a practical, structured and comprehensive framework for assessing risk based maintenance policies. The book also proposes a condition monitoring framework that can be used as a guide to assist asset managers in identifying the relationship between failure modes, ageing processes to select amongst condition monitoring regimes.


Discusses theory as necessary, but either in parallel with extremely pragmatic examples or with reference to real industry experiences

n

Offers an unusual mix of research and practical application, with international context, written for easy access by a wide audience

n

Describes a view of maintenance management from Electricity & Gas Distribution Network Operators (DNO) not available elsewhere

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Includes supplementary material: sn.pub/extras

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