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.
Original language | English |
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Pages (from-to) | 1326-1353 |
Number of pages | 28 |
Journal | International Journal of Production Research |
Volume | 63 |
Issue number | 4 |
Early online date | 28 Jul 2024 |
DOIs | |
Publication status | Published - 16 Feb 2025 |
Funding
This work was supported by the Engineering and Physical Sciences Research Council, UK [grant number EP/V051113/1 -Productivity and Sustainability Management in the Responsive Factory]
Keywords
- SDG 9: industry
- facility layout optimisation
- smart manufacturing
- mixed-integer linear programming
- process mining
- indoor localisation sensors