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Reinforcement Learning and Digital Human Modeling for Multi-objective Factory Layout Planning
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Production and Logistics, Scania CV AB, Södertälje, Sweden. (User Centred Product Design (UCPD))ORCID iD: 0000-0003-1390-8803
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Production and Logistics, Scania CV AB, Södertälje, Sweden. (User Centred Product Design (UCPD))ORCID iD: 0000-0002-7985-0010
Production and Logistics, Scania CV AB, Södertälje, Sweden.
Production and Logistics, Scania CV AB, Södertälje, Sweden.
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2025 (English)In: Proceedings of the 22nd Congress of the International Ergonomics Association, Volume 5: Better Life Ergonomics for Future Humans (IEA 2024) / [ed] Sangeun Jin; Jeong Ho Kim; Yong-Ku Kong; Jaehyun Park; Myung Hwan Yun, Singapore: Springer, 2025, p. 281-286Conference paper, Published paper (Refereed)
Abstract [en]

Factory layout planning involves allocating resources and arranging equipment in manufacturing facilities to enhance system performance and ensure a safe work environment. Integrating digital human modeling tools into factory layout planning facilitates early worker well-being analysis, mitigating musculoskeletal disorders. This paper presents methods for modeling factory layout planning as a multi-objective reinforcement learning problem, leveraging digital human modeling-based simulations. 
Place, publisher, year, edition, pages
Singapore: Springer, 2025. p. 281-286
Series
Springer Series in Design and Innovation, ISSN 2661-8184, E-ISSN 2661-8192 ; 57
Keywords [en]
Digital human modeling, Factory layout planning, Multi-objective optimization, Reinforcement learning
National Category
Production Engineering, Human Work Science and Ergonomics Robotics and automation
Research subject
User Centred Product Design; Virtual Production Development (VPD)
Identifiers
URN: urn:nbn:se:his:diva-25918DOI: 10.1007/978-981-96-9334-4_44Scopus ID: 2-s2.0-105017877124ISBN: 978-981-96-9334-4 (electronic)ISBN: 978-981-96-9336-8 (print)ISBN: 978-981-96-9333-7 (print)OAI: oai:DiVA.org:his-25918DiVA, id: diva2:2006743
Conference
22nd Triennial Congress of the International Ergonomics Association (IEA), Jeju, South Korea, August 25 to 29, 2024
Note

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025

Correspondence Address: V. Elango; School of Engineering Sciences, University of Skövde, Skövde, Sweden; email: veeresh.elango@scania.com

Available from: 2025-10-16 Created: 2025-10-16 Last updated: 2025-10-21Bibliographically approved

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Elango, VeereshLind, AndreasHanson, LarsSyberfeldt, Anna

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