Application of advanced analysis and predictive algorithm for warehouse picking zone capacity and content prediction

Abstract

Implementing a successful warehouse management system from scratch contains many challenges of different nature. The most important aspect is the financial status of the company that is implementing the system. How many resources is the company willing to spend is always a difficult dilemma. The second important issue is the actual usefulness of the developed solution. If the system cannot be implemented in the real world, as advanced as it may be in theory, it has very little or no use at all. In this paper, the current state of the picking zone of a medium-to-large logistics company warehouse is analyzed through a real-world case study. On the top of the collected results, a method for the optimal strategic and quantitative item placement in the picking zone is constructed through the usage of fitting algorithms. One month after the method was released to production, a quality check of the system by supervising the warehouse activities of the picking zone is conducted and the results are analyzed.