Systems and methods for use of a global registry with automated demand profiling via machine learning to optimize inventory management

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.