Reconfigurable process-aware factory layout planning: a human-centric multi-objective optimization approach
2026 (English)In: Engineering optimization (Print), ISSN 0305-215X, E-ISSN 1029-0273, p. 1-27Article in journal (Refereed) Epub ahead of print
Abstract [en]
Factory layout planning is central to manufacturing performance. By aligning productivity with worker well-being, factories can achieve more sustainable operations. Traditional approaches often treat the process sequence as static, limiting adaptability. This article introduces a human-centric approach that treats the process sequence as reconfigurable, enabling dynamic adjustment of resources and equipment across the assembly line. The approach integrates sequence generation with precedence constraints, block layout creation and resource positioning into a unified multi-objective optimization process. A genetic algorithm combined with digital human modelling evaluates proposals in terms of worker well-being, walking distance and area utilization, while ensuring compliance with work-environment regulations. Unlike previous studies, this method integrates reconfigurable sequencing with resource positioning into full assembly-line optimization, validated in an industrial testbed. The findings show how adaptable layouts improve performance and embed human factors and ergonomics into decision making, supporting Industry 5.0 principles of sustainable, human-centric manufacturing.
Place, publisher, year, edition, pages
Taylor & Francis, 2026. p. 1-27
Keywords [en]
Factory layout, multi-objective optimization, reconfigurable process description, human factors and ergonomics (HFE), Industry 5.0
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Socio-TEchnicAl SysteMs Engineering (STEAM); Processes in Intelligent Simulation, Manufacturing & Materials (PRISM); VF-KDO
Identifiers
URN: urn:nbn:se:his:diva-26996DOI: 10.1080/0305215x.2026.2718913ISI: 001862273600001Scopus ID: 2-s2.0-105048840822OAI: oai:DiVA.org:his-26996DiVA, id: diva2:2096627
Projects
Data-Driven Product RealisationLeveraging Industry 4.0 Technologies for Human-Centric Sustainable Production
Part of project
Virtual factories with knowledge-driven optimization (VF-KDO), Knowledge Foundation
Funder
Vinnova, 2026-00314Chalmers University of TechnologyUniversity of SkövdeKnowledge Foundation, 2018-0011Knowledge Foundation, 20240013
Note
CC BY 4.0
Contact: Andreas Lind, andreas.lind@scania.com
Received 08 Oct 2025, Accepted 10 Aug 2026, Published online: 27 Aug 2026
Taylor & Francis by informa
The authors gratefully acknowledge the support of Scania CV AB, the research project Data-Driven Product Realisation [grant number 2026-00314], funded by Vinnova through Chalmers University of Technology, and the research projects Virtual Factories with Knowledge-Driven Optimization [grant number 2018-0011] and Leveraging Industry 4.0 Technologies for Human-Centric Sustainable Production [grant number 20240013], both funded by the Knowledge Foundation via the University of Skövde; Stiftelsen för Kunskaps- och Kompetensutveckling.
2026-08-312026-08-312026-09-11Bibliographically approved