Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach

Existing of autocorrelation will bring a significant effect on the performance and accuracy of process control if the problem does not handle carefully. When dealing with autocorrelated process, Box-Jenkins method will be preferred because of the popularity. However, the computation of Box-Jen...

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Main Authors: Salleh, R. M., Zawawi, N. I., Gan, Z. F., Nor, M. E.
Format: Conference or Workshop Item
Language:English
Published: 2018
Subjects:
Online Access:http://eprints.uthm.edu.my/7018/1/P9919_1fb1df699a1a3afcf9fd57d9eb6b730c.pdf
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author Salleh, R. M.
Zawawi, N. I.
Gan, Z. F.
Nor, M. E.
author_facet Salleh, R. M.
Zawawi, N. I.
Gan, Z. F.
Nor, M. E.
author_sort Salleh, R. M.
collection UTHM
description Existing of autocorrelation will bring a significant effect on the performance and accuracy of process control if the problem does not handle carefully. When dealing with autocorrelated process, Box-Jenkins method will be preferred because of the popularity. However, the computation of Box-Jenkins method is too complicated and challenging which cause of time-consuming. Therefore, an alternative method which known as Geometric Brownian Motion (GBM) is introduced to monitor the autocorrelated process. One real case of furnace temperature data is conducted to compare the performance of Box-Jenkins and GBM methods in monitoring autocorrelation process. Both methods give the same results in terms of model accuracy and monitoring process control. Yet, GBM is superior compared to Box-Jenkins method due to its simplicity and practically with shorter computational time.
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spelling uthm.eprints-70182022-05-24T01:28:12Z http://eprints.uthm.edu.my/7018/ Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach Salleh, R. M. Zawawi, N. I. Gan, Z. F. Nor, M. E. T Technology (General) Existing of autocorrelation will bring a significant effect on the performance and accuracy of process control if the problem does not handle carefully. When dealing with autocorrelated process, Box-Jenkins method will be preferred because of the popularity. However, the computation of Box-Jenkins method is too complicated and challenging which cause of time-consuming. Therefore, an alternative method which known as Geometric Brownian Motion (GBM) is introduced to monitor the autocorrelated process. One real case of furnace temperature data is conducted to compare the performance of Box-Jenkins and GBM methods in monitoring autocorrelation process. Both methods give the same results in terms of model accuracy and monitoring process control. Yet, GBM is superior compared to Box-Jenkins method due to its simplicity and practically with shorter computational time. 2018 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/7018/1/P9919_1fb1df699a1a3afcf9fd57d9eb6b730c.pdf Salleh, R. M. and Zawawi, N. I. and Gan, Z. F. and Nor, M. E. (2018) Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach. In: ISMAP 2017, October 28, 2017, Batu Pahat, Johor. https://doi.org/10.1088/1742-6596/995/1/012039
spellingShingle T Technology (General)
Salleh, R. M.
Zawawi, N. I.
Gan, Z. F.
Nor, M. E.
Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach
title Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach
title_full Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach
title_fullStr Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach
title_full_unstemmed Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach
title_short Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach
title_sort autocorrelated process control geometric brownian motion approach versus box jenkins approach
topic T Technology (General)
url http://eprints.uthm.edu.my/7018/1/P9919_1fb1df699a1a3afcf9fd57d9eb6b730c.pdf
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