Companies use process control to detect and prevent defectrcts in production. One of the most commonly
used technique is control charts. To control multiple dimensions of quality on
one control chart, multivariable control charts, control charts for attributes
and demerit control charts are widely used. In this study, we use demerit
control charts to monitor multiple defect types and propose to employ fuzzy
c-means method to cluster the defect types based on pre-specified criteria. The
criteria are chosen to represent the severity of defect types and specified as:
(i) number of scraps, (ii) number of reworks and (iii) time of rework. In order
to test the proposed method, u and c attribute control charts and demerit
control charts for six instances in a textile company are used and compared. It
is observed that both the scrap and the repair rates are decreased when the
proposed method of demerit control chart is used.
Attribute control charts Demerit control charts Fuzzy clustering Fuzzy demerit control charts Process control
Primary Language | English |
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Subjects | Wearable Materials |
Journal Section | Articles |
Authors | |
Publication Date | June 28, 2020 |
Submission Date | July 30, 2019 |
Acceptance Date | May 22, 2020 |
Published in Issue | Year 2020 Volume: 30 Issue: 2 |