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Figure AI
Figure AI logoFigure AI · Feature trail

High-Volume Robot Manufacturing

1 post · Mar 2025 – Apr 2026

What this trail covers

Figure AI has established BotQ, a high-volume manufacturing facility capable of producing up to 12,000 humanoid robots annually. This initiative involves vertically integrated manufacturing, the development of supporting software infrastructure (MES, PLM, ERP, WMS), and the utilization of robots to build other robots. The process redesign includes rethinking robot architecture for mass production, shifting from CNC machining to tooled processes like injection molding and diecasting, and building a robust supply chain and manufacturing team. The facility also incorporates advanced automation and AI-driven robotics for assembly tasks.

All Figure AI trails
  1. Ramping Figure 03 ProductionThis post details the scaling of Figure 03 production at the BotQ manufacturing facility, achieving a 24x throughput improvement (1 robot/hour) in under 120 days. Key technical contributions include the development of custom manufacturing execution software across 150+ networked workstations, drastic improvements in supplier quality and in-process inspection (over 50 points), leading to an 80%+ end-of-line first pass yield and 99.3% yield on the battery line. Sophisticated EOL and in-process testing, including over 80 functional verification tests and 'burn-in' sessions, are implemented. For robot operations, the post highlights the development of an advanced alert system and diagnostics for failure analysis, engineered software 'fallback ladders' for graceful degradation, and a focus on solving the 'long tail' of edge-case failures. Furthermore, it describes the creation of an internal Field Service Management system, a custom Fleet Management System coordinating robots autonomously, and an Over-the-Air (OTA) software update infrastructure for fleet-wide upgrades.
  2. F.02 Contributed to the Production of 30,000 Cars at BMWThis post details the operational deployment and learnings from the Figure 02 robot at BMW's automotive manufacturing plant. It highlights key performance indicators (KPIs) such as cycle time, placement accuracy, and intervention rates for a sheet-metal loading task. The post also discusses hardware reliability, specifically identifying the forearm as a failure point in Figure 02 and detailing architectural improvements in Figure 03's wrist electronics to enhance reliability and thermal management. These learnings directly inform the design and operational readiness of Figure 03 for scaled production.
  3. Introducing Figure 03Figure 03 has been engineered from the ground up for high-volume manufacturing, representing a significant shift from previous prototype designs. This involved a ground-up redesign of nearly every component with manufacturability and cost as primary drivers, aggressively reducing part count and assembly steps. The manufacturing process has moved from CNC machining to toled processes like die-casting, injection molding, and stamping, requiring substantial upfront tooling investment but dramatically reducing per-unit cost. A new, vertically integrated supply chain has been established for critical module builds (actuators, batteries, sensors, structures, electronics) to meet high-volume production goals. BotQ, the dedicated manufacturing facility, will initially produce up to 12,000 robots annually, anchored by an internally developed MES for traceability and quality control.
  4. BotQ: A High-Volume Manufacturing Facility for Humanoid RobotsThis post details the establishment of BotQ, Figure AI's high-volume manufacturing facility, outlining the strategic decisions and technical implementations for scaling robot production. Key contributions include the redesign of robot architecture for mass production (shifting from CNC to toled processes like injection molding and diecasting), the development of essential manufacturing software infrastructure (MES, PLM, ERP, WMS), and the integration of robots (powered by AI like Helix) into the assembly line for 'robots building robots'. It also highlights the establishment of a dedicated reliability team focused on accelerated lifecycle testing and root cause failure analysis, and the strategic approach to building a scalable supply chain for complex components.