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The Development of Multivariate Statistical Process Monitoring (MSPM) Tools using Microsoft® Excel

Multivariate statistical process control methods have been proven in the process industries to be an effective tool for process monitoring, modelling and fault detection.This paper describes the approach used by the writer in the development of a Multivariate Statistical Process Monitoring (MSPM)...

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Main Author: Che Elliaziz, Mohd Syaufi
Format: Final Year Project
Language:English
Published: Universiti Teknologi PETRONAS 2009
Subjects:
TP Chemical technology
Online Access:http://utpedia.utp.edu.my/9164/1/2009%20-%20The%20Development%20of%20Multivariate%20Statistical%20Process%20Monitoring%28MSPM%29%20Tool%20using%20Microsoft%20.pdf
http://utpedia.utp.edu.my/9164/
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spelling my-utp-utpedia.91642013-10-22T09:46:07Z http://utpedia.utp.edu.my/9164/ The Development of Multivariate Statistical Process Monitoring (MSPM) Tools using Microsoft® Excel Che Elliaziz, Mohd Syaufi TP Chemical technology Multivariate statistical process control methods have been proven in the process industries to be an effective tool for process monitoring, modelling and fault detection.This paper describes the approach used by the writer in the development of a Multivariate Statistical Process Monitoring (MSPM) tools using Microsoft Excel. This developed MSPM tools will act as a process monitoring tools in order to monitor the performance of any equipment or process. In addition, this project will be testing on actual plant data to see the performance of the project. The tool will be developed in Microsoft Excel and Matlab. Microsoft Excel is chosen because of it is easy to use and user-friendly. Furthermore, it has macro function and easier to use when the user wants to develop many tools to the Microsoft Excel. In multivariate statistical process monitoring, a process monitoring model must be developed firstly. The model must be free from any abnormality, fault or outliers. Then the model will be tested on the future data to detect any abnormality in the process by applying the appropriate Hmits. As a conclusion, the MSPM method can be develop in Microsoft Excel. This tool can help to detect the problem or abnormality of the process and help in diagnoss assignable cause for the process IV Universiti Teknologi PETRONAS 2009-01 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/9164/1/2009%20-%20The%20Development%20of%20Multivariate%20Statistical%20Process%20Monitoring%28MSPM%29%20Tool%20using%20Microsoft%20.pdf Che Elliaziz, Mohd Syaufi (2009) The Development of Multivariate Statistical Process Monitoring (MSPM) Tools using Microsoft® Excel. Universiti Teknologi PETRONAS. (Unpublished)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
Che Elliaziz, Mohd Syaufi
The Development of Multivariate Statistical Process Monitoring (MSPM) Tools using Microsoft® Excel
description Multivariate statistical process control methods have been proven in the process industries to be an effective tool for process monitoring, modelling and fault detection.This paper describes the approach used by the writer in the development of a Multivariate Statistical Process Monitoring (MSPM) tools using Microsoft Excel. This developed MSPM tools will act as a process monitoring tools in order to monitor the performance of any equipment or process. In addition, this project will be testing on actual plant data to see the performance of the project. The tool will be developed in Microsoft Excel and Matlab. Microsoft Excel is chosen because of it is easy to use and user-friendly. Furthermore, it has macro function and easier to use when the user wants to develop many tools to the Microsoft Excel. In multivariate statistical process monitoring, a process monitoring model must be developed firstly. The model must be free from any abnormality, fault or outliers. Then the model will be tested on the future data to detect any abnormality in the process by applying the appropriate Hmits. As a conclusion, the MSPM method can be develop in Microsoft Excel. This tool can help to detect the problem or abnormality of the process and help in diagnoss assignable cause for the process IV
format Final Year Project
author Che Elliaziz, Mohd Syaufi
author_facet Che Elliaziz, Mohd Syaufi
author_sort Che Elliaziz, Mohd Syaufi
title The Development of Multivariate Statistical Process Monitoring (MSPM) Tools using Microsoft® Excel
title_short The Development of Multivariate Statistical Process Monitoring (MSPM) Tools using Microsoft® Excel
title_full The Development of Multivariate Statistical Process Monitoring (MSPM) Tools using Microsoft® Excel
title_fullStr The Development of Multivariate Statistical Process Monitoring (MSPM) Tools using Microsoft® Excel
title_full_unstemmed The Development of Multivariate Statistical Process Monitoring (MSPM) Tools using Microsoft® Excel
title_sort development of multivariate statistical process monitoring (mspm) tools using microsoft® excel
publisher Universiti Teknologi PETRONAS
publishDate 2009
url http://utpedia.utp.edu.my/9164/1/2009%20-%20The%20Development%20of%20Multivariate%20Statistical%20Process%20Monitoring%28MSPM%29%20Tool%20using%20Microsoft%20.pdf
http://utpedia.utp.edu.my/9164/
_version_ 1739831638957752320
score 13.211869

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