Risk-based maintenance for electricity network organizations /
By: Mehairjan, Ravish Preshant Yashraj
Publisher: Cham : Springer, c2017.Description: xxi, 155 p. : col. ill. ; 25 cm.ISBN: 9783319492346Subject(s): Electric power systems | Energy policy | Energy security | Quality control | Industrial safety | ReliabilityDDC classification: 333.79320 PR RI Online resources: Location MapItem type | Home library | Call number | Status | Date due | Barcode | Item holds |
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REGULAR | University of Wollongong in Dubai Main Collection | 333.79320 ME RI (Browse shelf) | Available | T0055804 |
, Shelving location: Main Collection Close shelf browser
333.7932 GH DI Distributed generation systems : | 333.7932 KE DI Distribution system modeling and analysis | 333.7932 KE DI Distribution system modeling and analysis | 333.79320 ME RI Risk-based maintenance for electricity network organizations / | 333.7932 PR EN Energy revolution : | 333.793213015195 SO EL Electrical load forecasting : | 333.79323 LI EL Electricity markets |
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, aging processes to select amongst condition monitoring regimes.