MONITORING VARIABILITAS PROSES BERDASARKAN STATISTIK WILKS

Suci Barlian Sari, Erna Tri Herdiani, Nasrah Sirajang

Abstract


In a manufacturing industry quality problems often occur. One of the main cause is due to variability process. Variability process is a variation that occurs in the process, both in manufacturing and non-manufacturing processes. One method for monitoring variabiliti process is by using Wilks Statistics. Wilks statistics is a method that is used based on individual observations. This study aims to monitor the variability of the process and apply it to Electric Resistance Welded (ERW) pipes with the Wilks statistical method. In addition, a capability process analysis is also carried out when the Wilks control chart has been controlled. The result showed that all observations carried out individually were in control limit with a capability process of  2.5386, which means the process capability of ERW pipe production using a multivariate Wilks statistical control chart was capable and match  with the specifications limit specified by company.


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References


Djauhari, Maman A. (2011). Geometric Interpretation of Vector Variance. Universiti Teknologi Malaysia. Jurnal Matematika, Volume 27, Nomor 1, 51–57.

Johnson, Richard. Dean Wichern. 2007. Applied Multivariat Statistical Analysis, 5th ed. New Jersey: Prentice Hall.

Khoo, M.B.C., & Quah, S.H. 2003. Multivariate control chart for process dispersion based on individual observations. Quality Engineering.

Montgomery, D.C.(2009). Introduction to statistical quality control (6th ed.) Arizona State University: John Wiley & Sons, Inc.

Morrison, D. F., (1990). Multivariate Statistical Methods Third Edition. USA: Mc Graw Hill Inc.

Noor, A.M dan Djauhari, M.A. 2010. Monotoring the variability of beltline moulding process using Wilks Statistics. Journal of Fundamental science, vol 6, no. 2, pp.116-120,2010

R.L. Mason and A.C. Rencher, Methods of multivariate analysis, 2nd ed. John Wiley & Sons, New York, NY, (2002).

R.L. Mason, Y.M. Chou and J.C. Young, Monitoring variation in a multivariate process when the dimension is large relative to sample size, Commun. Statist. Theor. and Meth. 38 (2009) pp. 939-951.

Sahabuddin, dkk. 2013. Pengendalian Proses Variabilitas Multivariate Melalui Vektor Variansi. Tesis. Program Studi Matematika Fakultas Matematika dan Ilmu pengetahuan Alam. Makassar. Universitas Hasanuddin.

Susanto, A.M. 2017. Statistical Quality Control on Process Electric Resistence Welded (ERW) Pipe in PT X. Skripsi. Program Studi Matematika Fakultas Matematika dan Ilmu pengetahuan Alam. Surabaya: Institute Teknologi Sepuluh November.

Walpole, R.E., Myers, R.H., Myers, S.L., &Ye, K .(2012). Probability & Statistics for Engineers & Scientists (9th ed.). United States of America: Person Education Inc.




DOI: http://dx.doi.org/10.20956/jmsk.v16i1.6485

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  Departemen Matematika,

Fakultas MIPA, Universitas Hasanuddin

 Indonesia

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