The Nassau Factory Reallocation & Shipping Optimization System is an AI-powered machine learning solution developed to improve supply chain efficiency and reduce operational lead time. The system predicts lead time and recommends the most suitable factory based on operational factors such as product type, region, shipping mode, sales, cost, units ordered, and factory location. A Random Forest Regression model was used to predict lead time and optimize factory allocation decisions. Additionally, an interactive Streamlit dashboard was developed to provide real-time business insights, factory performance analysis, region-wise lead time comparison, and downloadable optimization reports. This research demonstrates the use of predictive analytics and artificial intelligence for improving logistics and supply chain efficiency.
chetan bhagade (2026) studied this question.