Development and Evaluation of Overall Equipment Effectiveness of Knitting Machines Using Statistical Tools
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41310%2F22%3A96661" target="_blank" >RIV/60460709:41310/22:96661 - isvavai.cz</a>
Alternative codes found
RIV/60460709:41310/23:94747
Result on the web
<a href="https://doi.org/10.1177/21582440221091249" target="_blank" >https://doi.org/10.1177/21582440221091249</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1177/21582440221091249" target="_blank" >10.1177/21582440221091249</a>
Alternative languages
Result language
angličtina
Original language name
Development and Evaluation of Overall Equipment Effectiveness of Knitting Machines Using Statistical Tools
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20501 - Materials engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
SAGE Open
ISSN
2158-2440
e-ISSN
2158-2440
Volume of the periodical
12
Issue of the periodical within the volume
APR 2022
Country of publishing house
US - UNITED STATES
Number of pages
18
Pages from-to
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UT code for WoS article
000786322700001
EID of the result in the Scopus database
2-s2.0-85128750318