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Application of loss functions in process economic risk assessment


Khan, FI and Wang, H and Yang, M, Application of loss functions in process economic risk assessment, Chemical Engineering Research and Design, 111 pp. 371-386. ISSN 0263-8762 (2016) [Refereed Article]

Copyright Statement

2016 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

DOI: doi:10.1016/j.cherd.2016.05.022


Loss functions describe the economical consequences of the deviations from the target values. In recent years they have been used in wide range of application including process safety assessment. This paper provides a novel analysis to assess potential loss due to process deviation. The assessed losses help to better estimate process economic risk, which in turn assist in effective process system design and operational decision-making. The analysis is presented in four different development stages: (i) loss functions focusing on simple functions; (ii) loss functions with estimated maximum loss; (iii) loss functions focusing on probability distributions; and (iv) loss functions in which both distributions of variables and their dependencies are considered (i.e., hierarchical Bayesian based loss functions). Details discussion on development stages three and four are presented with case studies. First case study demonstrates application of inverted probability distribution and while second case study provides application of the hierarchical Bayesian loss functions. Advantage and disadvantages of different types of loss functions are also discussed. Finally, future research directions have been proposed.

Item Details

Item Type:Refereed Article
Keywords:hierarchical Bayesian loss function, inverted beta loss function, inverted normal loss functions, loss functions, Markov Chain Monte Carlo, decision making, Markov processes, risk assessment, risk perception, development stages, loss functions
Research Division:Engineering
Research Group:Engineering practice and education
Research Field:Risk engineering
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Khan, FI (Professor Faisal Khan)
ID Code:120425
Year Published:2016
Web of Science® Times Cited:14
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2017-08-24
Last Modified:2017-11-06

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