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PENGENDAIAN MULTIVARIATE DENGAN DIGRAM KONTROL MEWMA ENGGUNAKAN METODE SIX SIGMA (STUDI KASUS PT FUMIRA SEMARANG TAHUN 2019) | Utami | Jurnal Gaussian skip to main content

PENGENDAIAN MULTIVARIATE DENGAN DIGRAM KONTROL MEWMA ENGGUNAKAN METODE SIX SIGMA (STUDI KASUS PT FUMIRA SEMARANG TAHUN 2019)

*Puspita Ayu Utami  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Mustafid Mustafid  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Tatik Widiharih  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2020 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

As one of the biggest corrugation producing industries, PT Fumira Semarang is always required to fulfill customer needs by continuously improving their quality. Galvanized Steel is the raw material for the production of corrugation at PT Fumira Semarang. There are three important quality characteristics to be controlled in order that the results of galvanized steel production fit the standards to be manufactured as corrugation are waves, rust, and scratches. Six Sigma is a method for controlling quality. Six Sigma has focus on reducing defects, by standard 3,4 defects per one million opportunties. This research aims to identify the galvanized steel production process using Six Sigma method with MEWMA control chart and the capability of the process to fit the standards. Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is a tool used to control multivariate process averages. The result of this research are MEWMA control chart with lambda 0.7 shows that the process is controlled statistically and The Sigma value for waves is 2,33, for rust 2,05, and for scratches 2,64. And the research reveals the galvanized steel production process has not fit to the standard because the process capabilty index is 0,2805.

 

Keywords: Galvanized Steel, Quality Control, Six Sigma, Multivariate Exponentially Weighted Moving Average, Process Capability Analysis

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Keywords: Galvanized Steel; Quality Control; Six Sigma; Multivariate Exponentially Weighted Moving Average; Process Capability Analysis

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  1. Assauri, S. 2010. Manajemen Pemasaran. Jakarta: Raja Grafindo Persada
  2. Evans, J. R., & Lindsay, W. M. 2007. Pengantar Six Sigma: An Intoduction to Six Sigma & Process Improvement. Diterjemahkan oleh: Afia R. Fitriati. Jakarta: Salemba Empat
  3. Fumira. 2010. Material and Process. http://www.fumira.co.id/fumira/index. php?option=com_content&view=article&id=104&Itemid=97. Diakses : 7 Juni 2019
  4. Gaspersz, V. 2002. Pedman Implementasi Program Six Sigma Terintegrasi Degan ISO 9001:2000, MBNQA, dan HACCP. Jakarta: PT Gramedia Pustaka Utama
  5. George, M. L. 2002. Lean Six Sigma: Combining Six Sigma Quality with Lean Production Speed. New York: McGraw-Hill
  6. Haryatmi, S., & Guritno, S. 2008. Metode Statistika Multivariat. Jakarta: Universitas Terbuka
  7. Johnson, R., & Wichern, D. 2007. Applied Multivariate Statistical Analysis 6th Edition . United States of America: Pearson Education
  8. Diterjemahkan oleh: Bob Sabran. Jakarta: Erlangga
  9. Montgomery, D. C. 2009. Introduction to Statistical Quality Control 6th Edition. United States of America: John & Wiley Sons, Inc
  10. Morrison, D. 1990. Multivariate Statistical Methods 3th Edition . New York: Mc Graw Hill Publishing Company
  11. Mustafid. 2017. Statistika Dalam Proyek Six Sigma. Semarang: UNDIP Press
  12. Raissi, S. 2009. Multivariate Process Capability Indices On The Presence Of Priority For Quality Characteristics. Journal of Industrial Engineering International, Vol. 5, No. 9, 27-36

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