MULTIVARIATE SHORT-RUN PRODUCTION CONTROL CHART FOR MONITORING VARIABILITY AND MEANS PROCESS

RAHMAN, FATHUR (2017) MULTIVARIATE SHORT-RUN PRODUCTION CONTROL CHART FOR MONITORING VARIABILITY AND MEANS PROCESS. Masters thesis, Faculty of Mathematics and Science.

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Abstract

Statistical process control methods to monitor short-run production its considering by multivariate measurement, or the method is relatively new in control charts can also be called, multivariate control charts for short-run production to monitor the process mean and variability. To monitor the process mean control charts used influence function (IF) of mean and covariance matrix that is expected to detect small shifts, and to identify shifts in the variability of the process is used as the main component and eigenvalue influence function. The technique used is general, and the influence functions can be used to build multivariate control charts for both short-run nominal value or estimated. The methodology applied to the data creation subsea pipeline in the production PT.KHI (Krakatau Hoogeven International) in the 2014 period. A Results of the study showed the using conventional control charts can not detect a shift for variability and mean processes effectively, as is evident in the T2 control charts only two shifts that can be detected is the observation to 15 and 21 and on control charts for variables there are not any significant shifts can be detected, In the process of implementing the control charts for Short Production Run the shift of variability and mean the process can be detected with more leverage, which used influence functions (IF) of eigenvaluve and eigen vectors of the principal component for detecting a shift. in process variability and control chart T2 based influence functions (IF) of mean and matrix covariance of the principal component to detect the mean shift of the process by which each can detect three shifts simultaneously, in the observation to 15, 21 and 24. ======================================================================================================= Metode statistik proses kontrol untuk memantau proses jangka pendek (short-run) dengan mempertimbangkan pengukuran multivariat, atau metode diagram kontrol yang terbilang baru ini bisa juga disebut, diagram kontrol multivariat jangka pendek (short-run control chart) untuk memantau proses mean dan variabilitas. Untuk memantau mean proses pada diagram kontrol digunakan fungsi pengaruh mean dan matriks kovarian yang di harapkan dapat mendeteksi pergeseran kecil, dan untuk mengetahui pergeseran pada variabilitas proses maka digunakan komponen utama dan eigenvalue sebagai pengaruh fungsi. Teknik yang digunakan bersifat umum, dan pengaruh fungsi dapat digunakan untuk membangun diagram kontrol multivariat jangka pendek (short-run) baik untuk nilai nominal atau estimasi. Metode ini lebih lanjut diterapkan pada data pembuatan pipa bawah laut yang di produksi PT.KHI (Krakatau Hoogeven International) pada periode 2014. Hasil dari penelitian menujukan penggunaan diagram kontrol konvensional tidak dapat mendeteksi pergeseran variabilitas dan mean proses secara efektif, ini terbukti pada diagram kontrol T2 hanya dua pergeseran yang dapat dideteksi yaitu pada observasi ke 15 dan 21 sedangkan pada diagram kontrol variabel tidak terdapat satu pun pergeseran yang signifikan. Pada proses penerapan diagram kontrol Short Production Run pergeseran variabilitas dan mean proses dapat di deteksi dengan lebih maksimal, dimana digunakan fungsi pengaruh (IF) eigen valuve dan eigen vektor dari komponen utama (principal component) untuk mendeteksi pergeseran pada variabilitas proses dan diagram kontrol T2 berbasis fungsi pengaruh (IF) mean dan matriks kovarian dari komponen utama untuk mendeteksi pergeseran mean proses dimana dari masing-masing observasi dapat mendeteksi 3 pergeseran secara bersamaan yaitu pada observasi ke 15, 21 dan 24.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Statistical Process Control, Short Run Production, Eigen value, Eigen vectors, Influence Function, statistik proses kontrol, Principal Component
Subjects: H Social Sciences > HA Statistics
Q Science
Q Science > Q Science (General)
Q Science > QA Mathematics
Divisions: Faculty of Mathematics and Science > Statistics > (S2) Master Theses
Depositing User: Fathur Rahman
Date Deposited: 25 Jan 2017 07:33
Last Modified: 06 Mar 2019 07:28
URI: http://repository.its.ac.id/id/eprint/3053

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