A THESIS SUBMITTED TO THE FACULITY OF MECHANICAL ENGINEERING, INSTITUTE OF TECHNOLOGY, SCHOOL OF GRADUATE STUDIES, ARBAMINCH UNIVERSITY

Abstract

Overall equipment effectiveness is a part of total productive performance regarded as a measurement tool under total productive maintenance and aimed to identify production losses related to equipment that reduces machine effectiveness. Over the years, the inability of Nail Manufacturing Companies to achieve optimum maintenance of their equipment, and enhanced machine availability for better resource and maintenance utilization, has adversely affected their competitive advantage. The need to undertake a unique production method that will curb their several equipment maintenance challenges, and also reposition them for world-class manufacturing not solely decrease their losses, but will additionally increase their throughput and profitability. The general objective of the study is to investigate how to improve overall equipment effectiveness in the Gift Nail Manufacturing factory. Daily maintenance related data were collected and the analyses were performed using the descriptive statistics method with the help of Excel. The results showed that the highest value of 95.6 and 90.975 in the descriptive statistics for the maximum and mean respectively, underscore the importance of quality in the company's products. The percentage of mean for quality, availability, and performance obtained were 90.975, 61.9875 and 58.4125 respectively. This once again showed that quality of products is the greatest overall equipment effectiveness factor that nail manufacturing companies must take seriously in order to reduce the six big losses (Equipment failure, set-up and adjustment, idling and minor stoppages, speed losses, quality defects, and Rework) in their manufacturing processes. The analysis which is the main contribution of the study showed that quality has the greatest value followed by availability and performance. Also, overall equipment effectiveness must be set at 23.4 and 38.9 for both the lower and upper limits respectively, in order to effectively reduce downtime, production cost, the inherent wastes, as well as the six big losses