Smarter facility layout design : leveraging worker localisation data to minimise travel time and alleviate congestion
Aslan, Ayse and Vasantha, Gokula and El Raoui, Hanane and Quigley, John and Hanson, Jack and Corney, Jonathan and Sherlock, Andrew (2024) Smarter facility layout design : leveraging worker localisation data to minimise travel time and alleviate congestion. International Journal of Production Research. pp. 1-28. ISSN 0020-7543 (https://doi.org/10.1080/00207543.2024.2374847)
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Abstract
This paper introduces a novel methodology leveraging worker localisation data from ultrawide-band sensors to formulate alternative facility layouts aimed at minimising travel time and congestion in labour-intensive manufacturing systems. The system preprocesses sensor data to discern flow patterns between existing stations within the production facility, such as machine tools, workbenches, and stores. This information about the movement of people and materials informs the generation of optimised layouts through scenario-based optimisation. We explored two methods to devise these new layouts: a mixed-integer linear programming method and a simulated annealing metaheuristic, the latter being specifically developed to find high-quality solutions to the quadratic layout design formulation. Both methods employ biobjective formulations, focusing on the minimisation of travel time and the reduction of congestion risk on the manufacturing floor, an aspect often neglected in prior studies. Our methodology, applied to a real-world manual assembly line case study, demonstrated the potential to reduce travel time by a minimum of 32% and alleviate congestion while maintaining significant safety distances between facilities. This was achieved by automatically identifying design features that position high-traffic facilities closely and align them to eliminate movement overlaps.
ORCID iDs
Aslan, Ayse, Vasantha, Gokula, El Raoui, Hanane ORCID: https://orcid.org/0000-0002-9079-3248, Quigley, John ORCID: https://orcid.org/0000-0002-7253-8470, Hanson, Jack, Corney, Jonathan and Sherlock, Andrew;-
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Item type: Article ID code: 90110 Dates: DateEvent28 July 2024Published28 July 2024Published Online22 June 2024AcceptedSubjects: Technology > Engineering (General). Civil engineering (General) Department: Strathclyde Business School > Management Science
Faculty of Engineering > Design, Manufacture and Engineering Management > National Manufacturing Institute ScotlandDepositing user: Pure Administrator Date deposited: 02 Aug 2024 11:46 Last modified: 01 Oct 2024 15:26 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/90110