Optimizing Extended Warehouse Management for Make-to-Order Plants: Slotting, Wave Picking, and Yard Orchestration at Scale

Abstract

The make-to-order (MTO) production setting introduces high levels of operational complexity to the warehouse execution because of the high variability of products, variable demand trends, and high levels of synchronization with production and outbound logistics. The conventional management techniques in the warehouse, based on unchangeable slotting policies, fixed wave formations, and separated yard activities, cannot normally be scaleable to these circumstances. The given paper offers a combined optimization model of Extended Warehouse Management (EWM) in large-scale MTO plants, and the central issues to be considered are correlated ameliorations of slotting approach, wave picking, and yard coordination. The offered solution is a hybrid of demand-based SKU profiling, dynamically-based slotting heuristics, workload-based wave generation, and event-based yard and dock coordination, which allows real-time flexibility in warehouse and yard activities. The concept of an integrated architectural framework is presented to bring EWM and upstream production planning and downstream transportation system at par with one another so that there is consistency in the end-to-end execution. The validation of the framework is made by the industrial scale case study that proves the quantifiable reduction of order cycle time, picking productivity, dock turnaround time, and the overall warehouse throughput compared to the baseline settings. Findings suggest that co-optimisation of storage, picking and yard operations is fundamental to attain scalability, resilience and performance efficiency of MTO manufacturing settings, where advanced EWM has the potential to be deployed as a strategic enabler to responsive and high-performance execution of supply chain operations.