Open AccessQuality Variation Minimizer: A New Approach for Quality Improvement in Textile Industry
Author(s) -
Muhammad Amin,
M. Mohamed Amanullah,
Atif Akbar
Publication year - 2016
Publication title -
pakistan journal of scientific and industrial research. series a: physical sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 4
eISSN - 2223-2559
pISSN - 2221-6413
DOI - 10.52763/pjsir.phys.sci.59.2.2016.109.113
Subject(s) - yarn , spinning , quality (philosophy) , variation (astronomy) , product (mathematics) , textile industry , textile , mathematics , sample (material) , six sigma , quality management , coefficient of variation , statistics , computer science , manufacturing engineering , process engineering , engineering , mechanical engineering , materials science , operations management , composite material , geography , geometry , physics , management system , archaeology , quantum mechanics , lean manufacturing , astrophysics , thermodynamics
The main theme of this research is to introduce a new technique for quality improvement in industries and services environment. The technique is called as quality variation minimizer (QVM), which is used to test and compare product quali ty among multiple data groups, i.e. machines, operators, and material etc. For the significant application, QVM is applied at Card department in spinning industry to determine yarn grains quality by different machines. Then comparison of QVM is made with other already developed techniques, i.e., coefficient variation (CV), sigma level etc. to determine yarn grains quality. From the results determined by t-test and chi square test, it has been found that QVM is an effective method to determine yarn grains quality with sample average near the target/demanded value as well as minimum variation.