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Optimising corrective maintenance backlog using quality tools and quality principles at a selected power generation plant in South Africa optimising corrective maintenance backlog using quality tools and quality principles at a selected power generation plant in South Africa

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Date

2022-04

Authors

Maseola, Matshidiso Moses

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Abstract

This study is located within a power generation plant based in the Free state province of South Africa. Corrective maintenance is a challenge in the power generation plant which created corrective maintenance backlog. This emerged as a significant challenge for the power generation to address. According to previous studies, there has been minimal improvements in the coal-fired power generation plants in South Africa. This has created an environment where power generation is through aged infrastructure with high maintenance. South Africa, with its current power generation challenges, has a direct negative impact on global investors. It is critical to meet electricity demand to power the current and future economic needs of the country. The aim of the study is to optimise the corrective maintenance backlog at a selected power generation plant. In this study, a combination of qualitative and quantitative research methods were applied. A questionnaire was sent to the power generation plant employees. Top management was interviewed, and secondary data on corrective maintenance and documentation was analysed. This study looked at integrating essential quality tools and ISO 9001:2015 Quality Management Principles to optimise the corrective maintenance backlog. This integration brought about a practical and implementable framework that the power generation plant can apply to improve the execution of maintenance activities and thus reduce the corrective maintenance backlog.

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Submitted in fulfillment of the requirements for the Master of Philosophy in Quality Management, Durban University of Technology Technology, Durban, South Africa, 2022.

Keywords

Corrective maintenance, Quality management, Quality tools, Quality principles, Optimisation

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https://doi.org/10.51415/10321/4287

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