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Logic's advanced warehouse automation platform integrates digital twin technology to redefine efficiency, visibility, and control within warehouse operations. By creating a virtual replica of the warehouse and its inventory, Logic enables seamless operations while empowering businesses to make data-driven decisions with confidence.
Logic’s digital twin creates a live, interactive model of the entire warehouse, replicating its layout, operations, and workflows. This real-time virtualization provides complete visibility into the movement of goods, robots, and inventory across the facility. It also allows managers to test operational changes or new workflows in the digital twin without disrupting real-world operations.
Using the digital twin, Logic continuously monitors and optimizes robot missions and routes in real time. The system simulates travel paths, predicts congestion, and evaluates energy usage before deploying tasks to the fleet. This enhances travel efficiency, reduces operational bottlenecks, and balances workload distribution across robots.
Logic’s platform extends beyond physical warehouse visualization by digitizing the customer’s inventory. Through the Logic Item Master, the system identifies and tracks items by assigning unique digital identifiers, ensuring precise tracking from receipt to dispatch. It continuously updates inventory data with real-time weight and location monitoring and flags anomalies in inventory movement to minimize theft or misplacement.
Digital twins empower Logic to optimize space utilization by simulating predictive storage needs based on incoming shipments and demand forecasts. They help enhance picking efficiency by visualizing and streamlining picking routes to reduce time and improve accuracy. Workflow design is improved by identifying inefficiencies in facility layout and recommending actionable improvements.
Logic’s digital twin integrates with existing Building Management Systems (BMS) to monitor environmental factors such as temperature, humidity, and air quality, ensuring optimal storage conditions for sensitive goods. It simulates energy usage scenarios and recommends adjustments to minimize costs, while enabling businesses to test expansions or reconfigurations within the digital twin to avoid costly mistakes.anticipated needs.
By integrating data from across the middle mile, Logic’s digital twin continuously learns and adapts to evolving operational needs. It provides actionable insights such as bottleneck identification and resolution, predictive demand planning, and scenario modeling for peak periods or unexpected disruptions.
Interviews with the World’s Leading Minds On Robotics, Automation and AI