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.
Citation
Aslan, A., Vasantha, G., El-Raoui, H., Quigley, J., Hanson, J., Corney, J., & Sherlock, A. (in press). Smarter Facility Layout Design: Leveraging Worker Localisation Data to Minimise Travel Time and Alleviate Congestion. International Journal of Production Research,
Journal Article Type
Article
Acceptance Date
Jun 22, 2024
Deposit Date
Jun 24, 2024
Print ISSN
0020-7543
Electronic ISSN
1366-588X
Publisher
Taylor & Francis
Peer Reviewed
Peer Reviewed
Keywords
SDG 9: Industry, innovation and infrastructure; facility layout optimisation; smart manufacturing; mixed-integer linear programming; process mining; indoor localisation sensors
