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PERBANDINGAN DIAGRAM KONTROL MEWMA DAN DIAGRAM KONTROL T2 HOTELLING UNTUK PENGENDALIAN KUALITAS PRODUK KAIN POLYESTER (Studi Kasus : PT Daya Manunggal Kota Salatiga)

*Abdiyasti Nurul Arifa  -  Departemen Statistika, FSM, Universitas Diponegoro, Indonesia
Rukun Santoso  -  Departemen Statistika, FSM, Universitas Diponegoro, Indonesia
Tatik Widiharih  -  Departemen Statistika, FSM, Universitas Diponegoro, Indonesia
Open Access Copyright 2020 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

Fabrics is one of the most important needs of human life, so demand for clothing is greatly increased. Polyester fabric is a superior product at PT Daya Manunggal Salatiga because it has good quality. The quality of the fabric is very important because it is very influential in the competition to attract consumer interest. To maintain the consistency of the quality of the products produced in accordance with specifications, it is necessary to control the quality of the production process. The quality characteristics used in the production process of polyester fabric are thick layers, thin layers, two weft threads partially and two weft threads one more interconnected with one another, so multivariate control diagrams are used. Multivariate Exponentially Weighted Moving Average (MEWMA) and T2 Hotelling are control diagrams for monitoring mean process. The results showed that the MEWMA control diagram with lambda 0.7 yielded controlled results with a BKA value of 14.56021. Whereas in the Hotelling T2 control diagram a data reduction of four revisions was made to achieve controlled results with a final BKA value of 10.10928. The controlled production process obtained multivariate process capability values of 0.9672105 <1 which means the process is not capable. Comparison of results from the two methods shows that the MEWMA control diagram is more sensitive than the T2 Hotelling control diagram.

Keywords: Fabric, Multivariate Exponentially Weighted Moving Average (MEWMA), Hotelling T2, Process Capability Analysis

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Keywords: Fabric; Multivariate Exponentially Weighted Moving Average (MEWMA); Hotelling T2; Process Capability Analysis

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