Implementing PCA-Based Fault Detection System Based on Selected Imported Variables for Continuous-Based Process

Nowadays, the production based on chemical process was rapidly expanding either domestically or internationally. To produce the maximum amount of consistently high quality products as per requested and specified by the customers, the whole process must be considering included fault detection. This i...

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Main Author: Siti Nur Liyana, Ahamd
Format: Undergraduates Project Papers
Language:English
Published: 2013
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/7213/
http://umpir.ump.edu.my/id/eprint/7213/1/CD7097.pdf
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author Siti Nur Liyana, Ahamd
author_facet Siti Nur Liyana, Ahamd
author_sort Siti Nur Liyana, Ahamd
building UMP Institutional Repository
collection Online Access
description Nowadays, the production based on chemical process was rapidly expanding either domestically or internationally. To produce the maximum amount of consistently high quality products as per requested and specified by the customers, the whole process must be considering included fault detection. This is to ensure that product quality is achieved and at the same time to ensure that the quality variables are operated under the normal operation. There were several methods that commonly used to detect the fault in process monitoring such as using SPC or MSPC. However because of the MSPC can operated with multivariable continuous processes with collinearities among process variables, this technique was used widely in industry. In MSPC have a few methods that were proposed to improve the fault detection such as PCA, PARAFAC, multidimensional scaling technique, partial least squares, KPCA, NLPCA, MPCA and others. Here, in this thesis was to proposed new technique which was by implementing PCA-based fault detection system based on selected imported variables for continuous-based process. This technique was selected depends on the highest number of magnitude of correlation of variables using Matlab Software. The result in this thesis was the fault can be detected using only selected important variables in the process.
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format Undergraduates Project Papers
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institution Universiti Malaysia Pahang
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language English
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publishDate 2013
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spelling ump-72132021-06-08T06:58:26Z http://umpir.ump.edu.my/id/eprint/7213/ Implementing PCA-Based Fault Detection System Based on Selected Imported Variables for Continuous-Based Process Siti Nur Liyana, Ahamd QA Mathematics Nowadays, the production based on chemical process was rapidly expanding either domestically or internationally. To produce the maximum amount of consistently high quality products as per requested and specified by the customers, the whole process must be considering included fault detection. This is to ensure that product quality is achieved and at the same time to ensure that the quality variables are operated under the normal operation. There were several methods that commonly used to detect the fault in process monitoring such as using SPC or MSPC. However because of the MSPC can operated with multivariable continuous processes with collinearities among process variables, this technique was used widely in industry. In MSPC have a few methods that were proposed to improve the fault detection such as PCA, PARAFAC, multidimensional scaling technique, partial least squares, KPCA, NLPCA, MPCA and others. Here, in this thesis was to proposed new technique which was by implementing PCA-based fault detection system based on selected imported variables for continuous-based process. This technique was selected depends on the highest number of magnitude of correlation of variables using Matlab Software. The result in this thesis was the fault can be detected using only selected important variables in the process. 2013-02 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/7213/1/CD7097.pdf Siti Nur Liyana, Ahamd (2013) Implementing PCA-Based Fault Detection System Based on Selected Imported Variables for Continuous-Based Process. Faculty of Chemical and Natural Resources Engineering, Universiti Malaysia Pahang.
spellingShingle QA Mathematics
Siti Nur Liyana, Ahamd
Implementing PCA-Based Fault Detection System Based on Selected Imported Variables for Continuous-Based Process
title Implementing PCA-Based Fault Detection System Based on Selected Imported Variables for Continuous-Based Process
title_full Implementing PCA-Based Fault Detection System Based on Selected Imported Variables for Continuous-Based Process
title_fullStr Implementing PCA-Based Fault Detection System Based on Selected Imported Variables for Continuous-Based Process
title_full_unstemmed Implementing PCA-Based Fault Detection System Based on Selected Imported Variables for Continuous-Based Process
title_short Implementing PCA-Based Fault Detection System Based on Selected Imported Variables for Continuous-Based Process
title_sort implementing pca-based fault detection system based on selected imported variables for continuous-based process
topic QA Mathematics
url http://umpir.ump.edu.my/id/eprint/7213/
http://umpir.ump.edu.my/id/eprint/7213/1/CD7097.pdf