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dc.contributor.advisorWichers, J.H., Profen_US
dc.contributor.authorBudeli, L.en_US
dc.date.accessioned2020-03-17T09:31:39Z
dc.date.available2020-03-17T09:31:39Z
dc.date.issued2019en_US
dc.identifier.urihttps://orcid.org/0000-0002-5947-0731en_US
dc.identifier.urihttp://hdl.handle.net/10394/34392
dc.descriptionPhD (Development and Management), North-West University, Potchefstroom Campus
dc.description.abstractFor power utilities to secure a competitive edge in the energy sector, the efficiency of life cycle management programmes must be improved through successful execution of projects. In today's competitive environment, producing products that are fit for purpose and meet or exceed quality requirements, as well as being cost competitive, are key factors in determining organisational success. Effective project management practices require a project management system that supports management to achieve its organisational project goals, in order to position the organisation strategically for future performance. However, due to projects being inaccurately monitored resulting in improper management, the project success rate is very low, which has a major economic impact on organisations. This study proposes a Project Success Life Cycle Model (PSLCM) that is aimed at ensuring that critical factors are considered when the success of power plant life cycle management projects are measured. This model uses data envelopment analysis (DEA) to measure task, activity, process, product or firm input and output, as well as process efficiency at any stage of project, product or business development. It integrates technical performance and financial performance measures so that projects in different industries can be compared objectively and inefficiencies in areas where resource availability is high, can be easily identified. This paper shows how integrating effective technical and financial performance measures (TFPM), data envelope analysis (DEA) and design of experiments (DOE), as well as the use of standard processes, can dramatically improve plant life cycle management through an integrated life cycle management model. Statistical methods, which include analysis of variance (ANOVA), factorial experiments, T test, relative importance index (RII), and Pearson correlation coefficient where used to evaluate, verify and validate data. The outcome of the model is a success performance measure which incorporates project, product and corporate performance into a single value. This model will make it easy to compare projects, product and organisational performance in different stages of the power plant life cycle. The paper demonstrates how utilities can achieve sustained performance by identifying how the combination of project management best practices and life cycle management methodologies can recognise process improvement opportunities.en_US
dc.language.isoenen_US
dc.publisherNorth-West University (South Africa)en_US
dc.subjectCritical success factorsen_US
dc.subjectlife cycle managementen_US
dc.subjectbenefits realisationen_US
dc.subjectdata envelope analysesen_US
dc.subjectperformance measurementen_US
dc.titleCritical success factor model to optimize power plant life cycle managementen_US
dc.typeThesisen_US
dc.description.thesistypeDoctoralen_US
dc.contributor.researchID10065350 - Wichers, Jacob Harm (Supervisor)en_US


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