This book focuses on the
introduction of new and modern
of assets in the electricity
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
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.
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.
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.