Publication
Recommendation system using reinforcement learning for what-If simulation in digital twin
| dc.contributor.author | Pires, Flávia | |
| dc.contributor.author | Ahmad, Bilal | |
| dc.contributor.author | Moreira, António Paulo G. M. | |
| dc.contributor.author | Leitão, Paulo | |
| dc.date.accessioned | 2023-02-16T16:00:21Z | |
| dc.date.available | 2023-02-16T16:00:21Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | The research about the digital twin concept is growing worldwide, especially in the industrial sector, due to the increasing digitisation level associated to Industry 4.0. The application of the digital twin concept improves performance of a system by implementing monitoring, diagnosis, optimisation, and decision support actions. In particular, the decision-making process is very time consuming since the decision-maker is presented with hundreds of different scenarios that can be simulated and assessed in a what-if perspective. Bearing this in mind, this paper proposes to integrate a digital twin-based what-if simulation with a recommendation system to improve the decision-making cycle. The recommendation system is based on a reinforcement learning technique and takes user knowledge of the system into consideration and trust in the system recommendation. The applicability of the proposed approach is presented in an assembly line case study for recommending the best configurations for the system operation, in terms of the optimal number of AGVs (Autonomous Guided Vehicles) in various scenarios. The achieved results show its successful application and highlight the benefits of using AI-based recommendation systems for what-if simulation in digital twin systems. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Pires, Flavia; Ahmad, Bilal; Moreira, Antonio Paulo; Leitão, Paulo (2021). Recommendation system using reinforcement learning for what-If simulation in digital twin. In 19th International Conference on Industrial Informatics (INDIN). Palma de Mallorca, Spain. p. 1 - 6 | pt_PT |
| dc.identifier.doi | 10.1109/INDIN45523.2021.9557372 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10198/27010 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | IEEE | pt_PT |
| dc.relation | Research Centre in Digitalization and Intelligent Robotics | |
| dc.relation | An Intelligent Decision Support Approach for Industrial Digital Twin | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Digital twin | pt_PT |
| dc.subject | What-if simulation | pt_PT |
| dc.subject | Recommendation systems | pt_PT |
| dc.subject | Reinforcement learning | pt_PT |
| dc.title | Recommendation system using reinforcement learning for what-If simulation in digital twin | pt_PT |
| dc.type | conference paper | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Research Centre in Digitalization and Intelligent Robotics | |
| oaire.awardTitle | An Intelligent Decision Support Approach for Industrial Digital Twin | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/POR_NORTE/SFRH%2FBD%2F143243%2F2019/PT | |
| oaire.citation.conferencePlace | Palma de Mallorca, Spain | pt_PT |
| oaire.citation.endPage | 6 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | 19th International Conference on Industrial Informatics (INDIN) | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | POR_NORTE | |
| person.familyName | Pires | |
| person.familyName | Leitão | |
| person.givenName | Flávia | |
| person.givenName | Paulo | |
| person.identifier | https://scholar.google.pt/citations?user=an9quSsAAAAJ&hl=pt-PT | |
| person.identifier | A-8390-2011 | |
| person.identifier.ciencia-id | A119-72AB-6255 | |
| person.identifier.ciencia-id | 8316-8F13-DA71 | |
| person.identifier.orcid | 0000-0001-7899-3020 | |
| person.identifier.orcid | 0000-0002-2151-7944 | |
| person.identifier.scopus-author-id | 57200412919 | |
| person.identifier.scopus-author-id | 35584388900 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | restrictedAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
| relation.isAuthorOfPublication | 3ac8f73e-ecb2-44b6-9c6f-1ee99474e00f | |
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