Product Positioning Optimization in Intelligent Warehouse

To obtain competitive advantages in the global market scenario, companies have aimed at reducing logistic costs as well as streamlining the order fulfillment. The use of tools to efficiently manage the warehouse, ensuring a best allocation of the products has been growing. The method of the ABC Curve, based on the Principle of Pareto qualifies the portfolio of a company so that products can be separated into classes. The items of Class A deserve special attention since they represent 80% of the financial transactions of a company. On the other hand, the AHP multi-criteria tool enables the analysis of several criteria (demand, financial transaction, seasonality, among others) to determine the best alternative to achieve the main goal. In this context, this paper presents a tool/technique to ensure the correct positioning of the products optimized by either the allocation based on the ABC classification or the allocation by prioritizing the products established by the AHP. The tool/technique was implemented in language C and 1,620 loading and unloading tasks were simulated for random allocation, ABC and AHP to assure the flow of inputs and outputs from the storage. The results show that the system proposed is viable and efficient, as it shortens the distances traveled and streamlines the order fulfillment time, reducing the logistic costs. The reductions achieved with the allocations based on the ABC method ensure 8.42% for the traveled distances and 8.43% for the time spent to unload the trunks. The multi-criteria tool allowed reductions of 12.81% and 13.47% in the traveled distances and time spent, respectively, to allocate the items into the storage. The research is of great relevance for the area, as it ensures an optimum flow of the storage, reducing the unnecessary movements.