Abstract: An inventory machine learning process can be applied iteratively. The inventory machine learning process can be applied by a computing device. The inventory machine learning process can include determining similarity scores between demand profiles for individual parts and group centers for similarity groups of parts. The inventory machine learning process can include assigning individual parts into the similarity groups using similarity scores. The inventory machine learning process can include calculating representative demand profiles for each similarity group and determining whether the representative demand profile meets a threshold. When the threshold is met, inventory parameters can be determined for each similarity group based on the inventory machine learning process.

Abstract: In various embodiments, the disclosed system may be utilized in managing supply and demand chains to optimize creation and management of inventory buffer levels via machine learning. In several embodiments, optimizing inventory buffer levels may lead to minimizing costs while maximizing the availability and timeliness of product deliveries. In multiple embodiments, the disclosed system may utilize supply chain data and performance monitoring with automated machine learning and derivation of demand signatures and profiles to provide optimized creation and management of inventory buffer levels.