Maintenance
performance is critical for ensuring operational efficiency and reliability in
power generation facilities. At a South African coal-fired power generation
plant (PGP), various factors influence maintenance effectiveness, including the
integration of quality tools, management principles, and the role of external
service providers. This study investigates these factors to identify
opportunities for improvement and enhanced performance.
The study employed a quantitative cross-sectional
research approach to collect empirical data through surveys at the selected
PGP. Participants were selected using a stratified sampling technique to
capture diverse perspectives across different roles and responsibilities. Data analysis included both descriptive and
inferential statistics.
The findings reveal significant gaps in the
application of quality tools, contributing to increased downtime and reduced
system reliability. Although the plant demonstrates a strong commitment to
quality objectives, continuous improvement initiatives are not sufficiently
embedded in daily operations. Key challenges include inefficient workforce
management, substandard workmanship, inadequate spare parts inventory
practices, and communication gaps with external service providers.
To address these challenges, this study proposes an
Operational Quality Maintenance Framework, integrating quality tools and
principles with best practices in supplier management, waste reduction, and
improved documentation. A notable feature of the framework is the introduction
of a “Hit Squad” approach, that deploys specialized teams to critical areas,
enabling them to promptly address urgent maintenance issues and normalize
operations. This strategy enhances collaboration between departments and ultimately
leads to improved maintenance performance.
The proposed framework offers a practical model for
integrating quality management into maintenance processes, providing a pathway
for improved reliability and efficiency in coal-fired power generation. The
insights from this study contribute to the broader understanding of maintenance
optimization and offer scalable solutions applicable to similar industrial
contexts, emphasizing the importance of structured quality management for
sustainable operations.
