Monitoring autocorrelated process: a geometric brownian motion process approach

Autocorrelated process control is common in today's modern industrial process control practice. The current practice of autocorrelated process control is to eliminate the autocorrelation by using an appropriate model such as Box-Jenkins models or other models and then to conduct process control...

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Main Authors: Li, L. S., Djauhari, M. A.
Format: Conference or Workshop Item
Published: 2013
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Online Access:http://eprints.utm.my/id/eprint/51178/
http://dx.doi.org/10.1063/1.4823976
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Institution: Universiti Teknologi Malaysia
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spelling my.utm.511782017-09-17T08:13:34Z http://eprints.utm.my/id/eprint/51178/ Monitoring autocorrelated process: a geometric brownian motion process approach Li, L. S. Djauhari, M. A. Q Science Autocorrelated process control is common in today's modern industrial process control practice. The current practice of autocorrelated process control is to eliminate the autocorrelation by using an appropriate model such as Box-Jenkins models or other models and then to conduct process control operation based on the residuals. In this paper we show that many time series are governed by a geometric Brownian motion (GBM) process. Therefore, in this case, by using the properties of a GBM process, we only need an appropriate transformation and model the transformed data to come up with the condition needs in traditional process control. An industrial example of cocoa powder production process in a Malaysian company will be presented and discussed to illustrate the advantages of the GBM approach. 2013 Conference or Workshop Item PeerReviewed Li, L. S. and Djauhari, M. A. (2013) Monitoring autocorrelated process: a geometric brownian motion process approach. In: AIP Conference Proceedings. http://dx.doi.org/10.1063/1.4823976
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic Q Science
spellingShingle Q Science
Li, L. S.
Djauhari, M. A.
Monitoring autocorrelated process: a geometric brownian motion process approach
description Autocorrelated process control is common in today's modern industrial process control practice. The current practice of autocorrelated process control is to eliminate the autocorrelation by using an appropriate model such as Box-Jenkins models or other models and then to conduct process control operation based on the residuals. In this paper we show that many time series are governed by a geometric Brownian motion (GBM) process. Therefore, in this case, by using the properties of a GBM process, we only need an appropriate transformation and model the transformed data to come up with the condition needs in traditional process control. An industrial example of cocoa powder production process in a Malaysian company will be presented and discussed to illustrate the advantages of the GBM approach.
format Conference or Workshop Item
author Li, L. S.
Djauhari, M. A.
author_facet Li, L. S.
Djauhari, M. A.
author_sort Li, L. S.
title Monitoring autocorrelated process: a geometric brownian motion process approach
title_short Monitoring autocorrelated process: a geometric brownian motion process approach
title_full Monitoring autocorrelated process: a geometric brownian motion process approach
title_fullStr Monitoring autocorrelated process: a geometric brownian motion process approach
title_full_unstemmed Monitoring autocorrelated process: a geometric brownian motion process approach
title_sort monitoring autocorrelated process: a geometric brownian motion process approach
publishDate 2013
url http://eprints.utm.my/id/eprint/51178/
http://dx.doi.org/10.1063/1.4823976
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