Clustering Framework for Supply Chain Management (SCM) System

The cram of supply chain management (SCM) is being considered as center of attention and motivation, not only among academics but also among practitioners in recent years. SCM systems face complexity, processes time compression, and lackness of process optimization. In our current work, we present a broad framework for SCM, based on K-means clustering algorithm which concentrates on the supply chain (SC) processes for lessen the complexity, optimization factors in SC process communication, product variability and inaccurate forecast. Results show a feasibility to adopt this technique from a business analyst viewpoint.