Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC

A new approach for detecting and diagnosing fault via correlation technique is introduced in this study. The correlation coefficient is determined using multivariate analysis technique, Partial Correlation Analysis (PCorrA). Individual charting technique such as Shewhart, Exponential Weight Moving A...

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Main Authors: Harun, Noorlisa, Ibrahim, Kamarul Asri
Format: Conference or Workshop Item
Language:English
Published: 2004
Subjects:
Online Access:http://eprints.utm.my/5943/
http://eprints.utm.my/5943/1/NoorlisaHarun2004_FaultDetectionAndDiagnosisFDD.pdf
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author Harun, Noorlisa
Ibrahim, Kamarul Asri
author_facet Harun, Noorlisa
Ibrahim, Kamarul Asri
author_sort Harun, Noorlisa
building UTeM Institutional Repository
collection Online Access
description A new approach for detecting and diagnosing fault via correlation technique is introduced in this study. The correlation coefficient is determined using multivariate analysis technique, Partial Correlation Analysis (PCorrA). Individual charting technique such as Shewhart, Exponential Weight Moving Average (EWMA), and Moving Average and Moving Range (MAMR) charts are a used to facilitate the Fault Detection and Diagnosis (FDD). A precut multi component distillation is used as the case study in this work. Based on the result from this study Shewhart control chart gives the best performance with the highest FDD efficiency.
first_indexed 2025-11-15T20:53:31Z
format Conference or Workshop Item
id utm-5943
institution Universiti Teknologi Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T20:53:31Z
publishDate 2004
recordtype eprints
repository_type Digital Repository
spelling utm-59432017-09-10T08:32:07Z http://eprints.utm.my/5943/ Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC Harun, Noorlisa Ibrahim, Kamarul Asri T Technology (General) A new approach for detecting and diagnosing fault via correlation technique is introduced in this study. The correlation coefficient is determined using multivariate analysis technique, Partial Correlation Analysis (PCorrA). Individual charting technique such as Shewhart, Exponential Weight Moving Average (EWMA), and Moving Average and Moving Range (MAMR) charts are a used to facilitate the Fault Detection and Diagnosis (FDD). A precut multi component distillation is used as the case study in this work. Based on the result from this study Shewhart control chart gives the best performance with the highest FDD efficiency. 2004 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/5943/1/NoorlisaHarun2004_FaultDetectionAndDiagnosisFDD.pdf Harun, Noorlisa and Ibrahim, Kamarul Asri (2004) Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC. In: 18th Symposium of Malaysian Chemical Engineers (SOMChe) 2004, 13 - 14 Dec. 2004, UTP, Perak, Malaysia.
spellingShingle T Technology (General)
Harun, Noorlisa
Ibrahim, Kamarul Asri
Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC
title Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC
title_full Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC
title_fullStr Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC
title_full_unstemmed Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC
title_short Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC
title_sort fault detection and diagnosis, fdd via improved univariate statistical process control charts, uspc
topic T Technology (General)
url http://eprints.utm.my/5943/
http://eprints.utm.my/5943/1/NoorlisaHarun2004_FaultDetectionAndDiagnosisFDD.pdf