Austin, TX (February 21, 2023) – Today, at the Retailers International Leaders Association, (RILA), AutoScheduler.AI, an innovative Warehouse Management System (WMS) accelerator, introduces the Make-n-Ship warehouse optimization platform that optimizes loading products straight off the production line to better orchestrate production, warehousing, and transportation plans. Moving production runs directly to a truck eliminates touches, helps with labor shortages and reduces the need for storage space in a warehouse or distribution center located at the manufacturing site.
“Most WMS can’t efficiently handle products coming directly from the production line to a truck at the dock because of a mismatch between pre-built stock transfer orders and what gets produced, causing trucks to remain idling at the dock waiting to be filled. Without the buffer of the warehouse storage, companies struggle to have a ready supply of trailers that match the production output. Make-n-Ship will handle the movement of products directly from production to various deployment destinations."
~ Keith Moore, Chief Executive Officer, AutoScheduler
Make-n-Ship:
Clients using Make-n-Ship free up 10% more space capacity, reduce production planning loads by 33%, increase floor productivity by 8%, increase container fill by 2%, and increase service levels by 4%.
About AutoScheduler.AI
AutoScheduler.AI creates dynamic warehouse plans directly injected into the WMS to optimize activities based on constraints, ensuring sites run optimally at peak performance. Our intuitive AI and Machine Learning platform, developed with P&G and implemented at P&G, Unilever, General Mills, and others, streamlines operations by seamlessly integrating with existing WMS & ERP. We provide dynamic dock scheduling, labor level-loading, inventory balancing, proactive cross-docking, redundant workforce elimination, and more. Clients benefit from prescriptive analytics to drive efficiencies and create value in the supply chain. For more information, email info@autoscheduler.ai.