How a 3PL warehouse scaled operations with autonomous mobile robots (AMRs) and collaborative pick-pack-ship automation, achieving 60% throughput increase.
AutoPack Warehouse is a 50,000 sqft 3PL (third-party logistics) facility handling 15,000+ SKUs for e-commerce and retail clients. The warehouse operated with manual picking, packing, and sorting processes — causing high labor costs (60% of operating expenses) and peak-season bottlenecks. The company needed to scale without proportional labor increases.
GridMatrix designed and implemented a hybrid automation strategy combining Autonomous Mobile Robots (AMRs), collaborative robotic arms, and intelligent workflow automation — enabling 60% throughput increase with 45% labor cost reduction.
The system integrates 25 MiR/RMF-controlled AMRs with 6 UR collaborative arms via a centralized Warehouse Execution System (WES) built on Node.js + Python. Computer vision systems use YOLO for barcode detection and item verification. The WES communicates with the WMS (SAP) via REST APIs for real-time task orchestration. AR-guided mobile app helps workers locate items 40% faster. All warehouse equipment connects via industrial WiFi with edge computing for low-latency response. Safety systems include force-limited collaborative zones and emergency stop mechanisms throughout the facility. Real-time dashboards track 100+ KPIs for management visibility.
AutoPack Warehouse achieved 60% throughput increase while reducing labor costs by 45%. The hybrid human-robot workforce now processes 40,000+ orders daily with 99.1% accuracy — up from 97.9%. Peak season staffing requirements dropped from 40% temporary increase to 15%, improving retention and workforce stability. The 3.2x ROI on automation investment was achieved within 14 months. AutoPack has now become a preferred logistics partner for high-volume e-commerce clients, winning 15+ new contracts leveraging the company's automation competitive advantage.
