HVLV-Motor-KC: Production Efficiency of HVLV Motor Classification using K-means Clustering

This paper aims to introduce the K-means clustering algorithm to complement the Group Technology (GT) methodology as part of a multi-product, low-volume production system. This challenge aims to overcome the limitations of the GT methodology and optimize the production schedule to increase efficiency. We propose a high-variation, low-volume K-means clustering (HVLV-Motor-KC) algorithm, which is a K-means clustering algorithm that focuses on high-variety, low-volume data. This algorithm helps to optimize production by placing motors with similar characteristics in the same cluster.