Open AccessDevelopment and Evaluation of Overall Equipment Effectiveness of Knitting Machines Using Statistical Tools
Author(s) -
Muhammad Ramzan,
Hafsa Jamshaid,
Ismial Usman,
Rajesh Mishra
Publication year - 2022
Publication title -
sage open
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.357
H-Index - 32
ISSN - 2158-2440
DOI - 10.1177/21582440221091249
Subject(s) - overall equipment effectiveness , wilcoxon signed rank test , reliability engineering , total productive maintenance , socks , statistical hypothesis testing , computer science , remanufacturing , quality (philosophy) , product (mathematics) , productivity , engineering , manufacturing engineering , production (economics) , mathematics , mann–whitney u test , statistics , computer network , philosophy , geometry , epistemology , economics , macroeconomics
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.