Robotic conveyor line for precast-concrete building production: units, layout optimisation, and parallel scheduling

Engineering notes

Key topics: autonomous driving, planning. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Abstract 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 ( $$U_0$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>U</mml:mi> <mml:mn>0</mml:mn> </mml:msub> </mml:math> – $$U_{12}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>U</mml:mi> <mml:mn>12</mml:mn> </mml:msub> </mml:math> ), 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 $$43\times 29$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>43</mml:mn> <mml:mo>×</mml:mo> <mml:mn>29</mml:mn> </mml:mrow> </mml:math> 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 $$\approx 320~\text {m}^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>≈</mml:mo> <mml:mn>320</mml:mn> <mml:mspace/> <mml:msup> <mml:mtext>m</mml:mtext> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> </mml:math> ), providing a transferable, data-driven workflow to link robot cycle times to layout decisions and capacity-planning recommendations.

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