Abstract
This paper evaluates the impact of Total Productive Maintenance (TPM) in a railway and mining
component manufacturing company. Literature suggest that TPM is an approach innovative to
maintenance and its major goals are no defects, no accidents and no breakdowns. Many authors have
argued that TPM improves quality, equipment productivity, prevents unexpected breakdowns and reduces
defects. Reliable manufacturing equipment is considered as a major contributor to the profitability and
performance of manufacturing systems in today’s extremely evolving environment. Most organizations
function effectively today because the equipment is reliable and available thereby maximising production
throughput and profit.
A case study was conducted and it involved a mixed method approach where both quantitative and
qualitative data was gathered and analysed. The company implemented TPM through the following
initiatives; autonomous maintenance, employee improvement, planned maintenance, quality maintenance,
education and training and safety and health. TPM was implemented for eighteen months. This study
made use of the following maintenance improvement tools, TPM, Failure Mode Effects and Critically
Analysis (FMECA) and cause and effect diagram. Maintenance performance factor such as Overall
Equipment Effectiveness (OEE) was analysed before and after TPM implementation.
The results of this study showed that TPM implementation contributes to equipment reliability. There was
an improvement in overall organizational performance. Through FMECA, maintenance tasks were
prioritized and risk priority numbers (RPN) were calculated for particular equipment. Key performance
indicators such as productivity and OEE were on an upward trend while there was a reduction in defect
rates. Communication among workers, workers and management, and among different departments was
improved. Worker motivation was improved through autonomous maintenance. However maintenance
performance in some departments was found to be too low due to unavailability of data and worker
inconsistency. This paper contributes to the theory and practice of TPM implementation.