Traditionally, separating large pallets of products has been a labor-intensive task. Due to labor shortages and ongoing staffing issues, robotic automation is an ideal solution to the problem. The customer sought to automate the warehouse fulfillment process for a batch of raw material shipping orders. The system must separate the boxes in the pallet layer by layer and transfer these layers to the shipping pallet according to the order. Finally, the system had to be integrated into the company's existing warehouse operations and software.
Solution. The systematic approach to WLJS is to receive a batch of original transport orders and then use a visual camera system to separate the layer quantity order lines from the non-layer quantities in the source pallet. The system then takes the layer quantity order from the source pallet and builds the order pallet that is ready for shipping. This is achieved by using a modbustcp to canopen, a software application that is simple to configure to find the optimized build order and maximize the number of pallet builds. The software also provides users with analytics and operational insights to optimize labor utilization.
Given a set of orders from a customer work management system (WMS) and validation of on-hand quantities, the modbustcp to CANopen gateway determines the best build order to complete the order. The automated layer picking system then guides the operator through the ideal feed sequence for building and ordering pallets while minimizing the labor required to build the order. Once the pallet order is complete, the pallet will be transferred to the shrink wrapping station, where the pallet will be shipped and labeled. The pallet order is then removed from the system and placed in a staging area ready for final shipping. Incomplete orders are staged in the buffer until the next line item is ready to be picked from the source pallet.
The customer maximized throughput while minimizing reliance on unreliable manual labor. The Modbustcp to CanOpen solution for this customer has a layer pick cycle time of 30 seconds, and its throughput is unmatched.