Data-Driven Replenishment Method Choice in a Picking System

Abstract

Designing the operating policies of picking systems, which connect inventory and production/assembly lines in a manufacturing system, involves determining replenishment methods for individual items. These replenishment methods affect the overall labor cost and flexibility of the picking system by determining the frequency and quantity of item picking. To design the replenishment method, in this paper, we propose a data-driven decision support framework that provides guidance in comprehending features in a picking system based on demand, size, and value of individual items. The proposed framework is then applied to a real-world case for validation.