Development and Evaluation of Overall Equipment Effectiveness of Knitting Machines Using Statistical Tools

Abstract

In manufacturing industries, well-maintained machines ensure their maximum utilization with good product quality, efficient time, and minimum cost. The objective of this study is to investigate a socks manufacturing line to propose an advanced maintenance plan based on Overall Equipment Effectiveness (OEE) to improve the overall maintenance along with better machine performance and product quality. Firstly, a socks manufacturing unit was selected and its maintenance-related problems were identified. It was observed that, among the six big losses, three losses have the major contribution in reducing the world-class value of OEE. Then a framework was designed based on the OEE model with the amalgamation of problem-solving tools to overcome the identified problems and reduce the contribution of three big losses. After the successful implementation of the proposed model, a significant reduction in the value of three big losses was observed that ultimately improve the value of OEE factors for the socks knitting machines by 2.18%. The statistical analysis is also conducted using three types of statistical tests, the Normality test, Wilcoxon signed-rank test, and Paired samples t-test. Kolmogorov–Smirnov (KS) test by Statistical Analysis Software (SAS). This paper points out a new proposed model of advanced OEE, which can improve machine maintenance, productivity, and quality in a better way as compared to the conventional OEE model.

Optimizing Auto Manufacturing: A Holistic Approach Integrating Overall Equipment Effectiveness for Enhanced Efficiency and Sustainability

“…The authors discovered that the methods are appropriate for manual assembly lines, workstations, or job shops that frequently combine manual and mechanical technology [38].…”