Markov Decision Process to Optimise Long-term Asset Maintenance and Technologies Investment in Chemical Industry

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F21%3APU141356" target="_blank" >RIV/00216305:26210/21:PU141356 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/abs/pii/B9780323885065502874?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/abs/pii/B9780323885065502874?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/B978-0-323-88506-5.50287-4" target="_blank" >10.1016/B978-0-323-88506-5.50287-4</a>

Result language
angličtina
Original language name
Markov Decision Process to Optimise Long-term Asset Maintenance and Technologies Investment in Chemical Industry
Original language description
The decisions on synthesising a process network are often to optimise the payback periods based on investment cost. In addition to the core investment and the cost of used resources, the long-term reliable operation of the process is also crucial. Given available states and technologies of the assets, this study aims to identify the long-term optimal asset planning policy. Markov Decision Process (MDP) is a promising tool in identifying the optimal policy under different states of the assets or equipment. The failure probability of the unit is modelled with the ‘bathtub’ model and each of the condition states are incorporated in the MDP. The decisions to implement the redundant units in the process with variety of technologies are allowed. This paper applied the MDP into an equivalent Mixed Integer Non-linear Programming (MINLP) to solve for the optimal long-term assets decision and the maintenance policy. The applicability of the method is tested on a real case study from Sinopec Petrochemical Plant. The capital and expected operational cost that accounts for equipment maintenance for an infinite time horizon are determined.
Czech name
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Czech description
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Project
<a href="/en/project/EF15_003%2F0000456" target="_blank" >EF15_003/0000456: Sustainable Process Integration Laboratory (SPIL)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name
31st European Symposium on Computer Aided Process Engineering
ISBN
9780323885065
Number of pages of the result
6
Pages from-to
1853-1858
Number of pages of the book
2140
Publisher name
Elsevier Ltd.
Place of publication
Neuveden
UT code for WoS chapter
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