Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties
This paper reports how the economic performance of a chemical process plant is affected by material flow uncertainties from the plant inlet and outlet. Two chance-constrained optimization models were proposed. The models were tested using case studies of an existing gas processing plant. Profit opti...
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my.utp.eprints.324852022-03-29T14:03:56Z Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties Getu, M. Mahadzir, S. Lee, M. This paper reports how the economic performance of a chemical process plant is affected by material flow uncertainties from the plant inlet and outlet. Two chance-constrained optimization models were proposed. The models were tested using case studies of an existing gas processing plant. Profit optimization for the case studies was made with respect to the reliability of holding the process constraints at a certain confidence level 0.5, 1. The optimal profit change for uncertainty from the plant inlet within the confidence interval 0.96, 1 was 86%. On the other hand, the optimal profit change for uncertainty from the plant outlet was only 2% for the same confidence level interval considered. This suggests that the uncertainty from the plant inlet has a major impact on the overall economic performance of the plant. Sensitivity analysis showed how uncertain parameters from both plant sides can affect the overall profit significantly. © 2013 Elsevier Ltd. 2013 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886386532&doi=10.1016%2fj.compchemeng.2013.05.026&partnerID=40&md5=28678c43cddab78117a5103b33670824 Getu, M. and Mahadzir, S. and Lee, M. (2013) Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties. Computers and Chemical Engineering, 59 . pp. 186-196. http://eprints.utp.edu.my/32485/ |
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This paper reports how the economic performance of a chemical process plant is affected by material flow uncertainties from the plant inlet and outlet. Two chance-constrained optimization models were proposed. The models were tested using case studies of an existing gas processing plant. Profit optimization for the case studies was made with respect to the reliability of holding the process constraints at a certain confidence level 0.5, 1. The optimal profit change for uncertainty from the plant inlet within the confidence interval 0.96, 1 was 86%. On the other hand, the optimal profit change for uncertainty from the plant outlet was only 2% for the same confidence level interval considered. This suggests that the uncertainty from the plant inlet has a major impact on the overall economic performance of the plant. Sensitivity analysis showed how uncertain parameters from both plant sides can affect the overall profit significantly. © 2013 Elsevier Ltd. |
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Getu, M. Mahadzir, S. Lee, M. |
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Getu, M. Mahadzir, S. Lee, M. Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties |
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Getu, M. Mahadzir, S. Lee, M. |
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Getu, M. |
title |
Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties |
title_short |
Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties |
title_full |
Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties |
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Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties |
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Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties |
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profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties |
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2013 |
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886386532&doi=10.1016%2fj.compchemeng.2013.05.026&partnerID=40&md5=28678c43cddab78117a5103b33670824 http://eprints.utp.edu.my/32485/ |
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