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Improving operational performance of legacy manufacturing machines through reliability management
Thesis   Open access

Improving operational performance of legacy manufacturing machines through reliability management

Phathutshedzo Victor Nekhwalivhe
M.Eng., University of Johannesburg
2026
Handle:
https://hdl.handle.net/10210/520805

Abstract

The reliability of manufacturing machinery is a critical factor influencing operational efficiency, cost management, and overall productivity in industrial settings. However, many manufacturing industries face challenges in maintaining aging or legacy machinery, often lacking modern reliability features. This study examines the impact of reliability management on manufacturing industries, particularly Company X, focusing on its role in improving maintenance quality, reducing downtime, and optimizing asset utilization and operational efficiency. Company X is a steel manufacturing firm in Johannesburg, South Africa. For this study, its name is withheld to protect its identity. This study adds to already existing knowledge on plant dependability and maintenance by highlighting how structured reliability practices can strengthen operational performance and extend the useful life of legacy equipment. This study follows a mixed method research approach, a blend of quantitative and qualitative study. When it comes to Data collection, literature review, observations, a questionnaire, a survey, and maintenance records and documentation will be used for that purpose. A questionnaire to be completed by Company X’s workers within the chosen population was set and distributed to 28 participants to perform gap analysis and assess the maintenance activities. A survey was used to benchmark. This was achieved through an online platform and targeted 50 replies from workers in other manufacturing industries in South Africa. However, 35 replies satisfied the criteria after data cleaning. The findings from this research aim to support organizations in developing a structured reliability management framework to enhance the longevity and operational efficiency of legacy manufacturing machinery.
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