Asset operational readiness assessment of new build power plant equipment

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dc.contributor.advisor Wannenburg, Johann
dc.contributor.postgraduate Nkosi, Thokozani Michael
dc.date.accessioned 2020-08-28T10:50:04Z
dc.date.available 2020-08-28T10:50:04Z
dc.date.created 2020-08
dc.date.issued 2019
dc.description Dissertation (MEng)--University of Pretoria, 2019. en_ZA
dc.description.abstract The delivery of medium and mega project has been a challenge for a number of decades, with attempts made to reduce the associated issues around engineering projects implementation. Project delivery before 1950 mainly relates to cost, time, and scope, with a lack of documentation pertaining to methods, as well as inadequate techniques to achieve a quality final product. The concept of Asset Operational Readiness (AOR) emanates in the 1950s from the military as means of providing the “developmental state of weapons systems”. The concept gained momentum as it was associated with “system safety” in the 1980s for decision-making. AOR can be defined as an establishment of a state or configuration which, after completion of the project, “places the right people in the right places at a right time working with the right hardware according to the right procedures and management controls”. The research work covered in this thesis, aims to propose a best-practice AOR framework for mega-projects in the power generation industry. A thorough Literature Review provides an overview of best practices on the AOR requirements for various industrial fields. The survey shows that AOR implementation follows the Project Life Cycle Management (PLCM) principles, from conceptual and pre-feasibility phases to commissioning and operation phases. In addition, the survey considers methodologies and techniques, which aids to enhance AOR framework development such as Root Cause Analysis (RCA) exercises. The study has provided an opportunity to develop an AOR theoretical framework refinement methodology, inclusive of RCA, AOR assessment tools, qualitative survey tool, and scoring systems. The AOR best practice framework and refinement methodology application to a real mega project case study, with historical data, enables a stage wise assessment of each component for individualized performance rating. This provides an identification of the areas that require refinement to have an improved AOR framework as outcome. The research outcome shows that there are implications for inadequate development and implementation of items in the proposed framework. The implications range from rework during manufacturing and construction, poor product quality delivery, poor performance post commissioning, and overall cost overruns. In addition, the study provides evidence that implementation of the AOR framework aids a project to realize its potential and yield positive results, which ultimately benefits an organization in terms of quality product delivery, cost reduction, and optimal Operations and Maintenance of the established asset. en_ZA
dc.description.availability Unrestricted en_ZA
dc.description.degree MEng en_ZA
dc.description.department Civil Engineering en_ZA
dc.identifier.citation Nkosi, TM 2019, Asset operational readiness assessment of new build power plant equipment, MEng Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/75949> en_ZA
dc.identifier.other S2020 en_ZA
dc.identifier.uri http://hdl.handle.net/2263/75949
dc.language.iso en en_ZA
dc.publisher University of Pretoria
dc.rights © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
dc.subject UCTD en_ZA
dc.subject Asset Operational Readiness (AOR) en_ZA
dc.subject.other Engineering, built environment and information technology theses SDG-09
dc.subject.other SDG-09: Industry, innovation and infrastructure
dc.title Asset operational readiness assessment of new build power plant equipment en_ZA
dc.type Dissertation en_ZA


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