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Demonstrates layout optimization and parallel scheduling in robotic conveyor systems, highlighting efficiency improvements.
Precast plants face labor shortages, tight delivery windows, and increasingly complex internal logistics, yet decision-level methods that couple robot-level processing times with factory layout–routing–scheduling remain limited. This paper proposes an integrated workflow for designing or retrofitting an Optimized Robotic Conveyor for Precast Concrete (ORC-PC) line and demonstrates it on a six-story reference building. Elements are grouped into product families and mapped to robotic operational units ( U₀ U 0 – U₁₂ U 12 ), each representing a defined workcell or resource in the ORC-PC line, in a Rhino3D factory model consistent with KUKA workspaces, safety envelopes, and formwork geometry. Family-dependent cycle times from KUKA.sim drive a Particle swarm optimisation layout model that minimizes flow-weighted conveyor length under non-overlap and clearance constraints, yielding a compact layout of approximately 43× 29 43 × 29 m with a loop length of about 96.6 m and implied internal transport times on the order of 10–15 min per element. A Resource-Constrained Project Scheduling Problem then embeds transport and processing times to identify bottlenecks and quantify parallelisation strategies. Results show that curing time and curing-capacity limits dominate throughput, with cage fabrication and downstream drilling acting as secondary bottlenecks under nominal parameters. Overall, under the assumed curing-capacity and scheduling parameters, the ORC-PC line approaches a production rate on the order of one story per day for the structural frame of the reference building (footprint ≈ 320~m² ≈ 320 m 2 ), providing a transferable, data-driven workflow to link robot cycle times to layout decisions and capacity-planning recommendations.
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Baghdadi et al. (2026) studied this question.
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