Improve utilization of Kanban bins, forklifts, molds, facility assets, and truck turnaround times in a yard, and accurately forecast production and shipping times to offer firm delivery commitments. Enhance customer experience with a precise, real-time work-in-process (WIP) order status in a manufacturing line or at a warehouse with a click of a button.
Get a DemoToday, the standard method employed to track manufacturing velocity and dwell/detention times in warehouses and yards is inefficient due to:
RFID's "line of sight" requirement for accurate reads and extensive infrastructure requirement in the facility.
Challenge #2RFID’s dependence on standard operating procedures for movement of Kanban bins, molds, forklifts, etc.
Challenge #3Lack of live data visualizations on process chokes, manufacturing velocity, and ship date ETA changes.
Better visibility by combining production planning, WMS, TMS, and order information with real-time, zone-level location and condition data of Kanban bins, molds, sub-assemblies, or finished goods tagged with IoT sensors.
Step 2: Alerts & SignalsBuilt on verifiable visibility, alerts & signals empower better decisions and drive automation. For example, a business signal on work-in-process (WIP) status is derived by sensing the manufacturing milestone/stage to enable timely order shipping.
Step 3: IntelligenceUse AI-powered network insights & foresights for better supply chain planning & execution. For example, assess production line chokepoints by zone, SKU, and factory and forecast this key performance indicator (KPI).
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A large automotive OEM with sub-assembly lines witnessed choke points and inefficiencies, leading to inaccurate estimation of the production schedules during a particular day, week, or month. It further generates downstream delays through a bullwhip effect in logistics planning and fulfillment of customer orders. With Roambee's intelligence, they transformed their manufacturing by accurately diagnosing that the slowest and fastest processes varied heavily (about 57%). They further analyzed that just two lines were to be optimized by 18% to run all sub-assembly lines in synchrony to prevent inventory pileups.
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