LYNA (Lina) Packaging Quantity Forecast

basic information

General machine learning requires vast amounts of training data, which poses challenges in the fast-changing environment of distribution, such as product modifications. "LYNA Package Quantity Forecast" utilizes a unique learning algorithm specialized for logistics data, developed based on the latest machine learning algorithms, achieving high accuracy predictions even from about a week's worth of training data. Since all learning is done automatically, there is no need for any product master data. For new products without shipping history, the AI automatically estimates package types and quantities based on category information. Furthermore, once actual shipments begin, it immediately learns and adjusts predictions based on a few days of actual data, enhancing accuracy. This frees busy site managers from the cumbersome and time-consuming task of managing size and packaging method masters for each product, eliminating unnecessary burdens and waste for picking operators and truck numbers through accurate predictions.

Price range

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Applications/Examples of results

- Based on the order, the AI automatically predicts the actual load (number of baskets, number of weights, etc.). - Since the AI calculates automatically, data organization skills (master management) are not required.