N Ramya Krishna, Y Priyanka, S Sai manikanta Reddy, K Dilip, P Madhu 03 09 The Raw Material Usage Tracker and Prediction system is designed to monitor analyze and predict the consumption of raw materials in an organization The system maintains detailed records of material purchases available stock daily usage production requirements and remaining inventory It helps organizations track raw material usage efficiently and identify consumption patterns over time Historical usage data is analyzed using data analytics and machine learning techniques to predict future raw material requirements The prediction feature helps estimate upcoming demand and supports timely material procurement The system can also identify materials with high consumption rates and provide useful insights for inventory management By continuously tracking stock levels it can help reduce the chances of material shortages and unnecessary overstocking Data visualization through charts and dashboards makes it easier for users to understand consumption trends and inventory status The system improves planning by providing datadriven estimates instead of relying only on manual calculations It can support better purchasing decisions reduce material wastage and improve production efficiency Overall the proposed system provides a centralized and intelligent solution for raw material tracking consumption analysis inventory monitoring and future usage prediction Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026