Real Time Deamand Forecasting and Its Role in Inventory Optimization in Manufacturing - Tulli, Sai krishna Chaitanya (International Journal of Scientific Research and Management (IJSRM), 2024)
Real-time demand forecasting has emerged as a transformative tool in the manufacturing sector, enabling businesses to align production with market needs dynamically. Traditional demand forecasting methods often rely on historical data and static models, which fail to adapt to rapid market fluctuations. Real-time forecasting leverages advanced technologies such as artificial intelligence (AI), machine learning (ML), and IoT sensors to provide accurate and timely insights into consumer demand. This research investigates the integration of real-time demand forecasting with inventory optimization strategies to reduce costs, minimize waste, and enhance operational efficiency. Through case studies and simulation models, we demonstrate significant improvements in forecast accuracy and inventory turnover rates. The findings underscore the potential of real-time systems to revolutionize inventory management and suggest practical implementation strategies for manufacturers aiming to stay competitive in a volatile market.