Integrating Machine Learning, Radio Frequency Identification, and Consignment Policy for Reducing Unreliability in Smart Supply Chain Management

Adopting smart technologies for supply chain management leads to higher profits. The manufacturer and retailer are two players, where the is unreliable may not send accurate demand information manufacturer. As an advanced technology, Radio Frequency Identification (RFID) implemented track trace each product’s movement on a real-time basis in inventory. It takes this management. This research proposes Machine Learning (ML) approach on-demand forecasting under Using Long-Short-Term Memory (LSTM), forecasted obtain exact reduce overstock or understock situation. A measurement environmental effect also incorporated with model. consignment policy applied controls inventory, gets fixed fee along commission selling product. installs RFID technology at retailer’s place. Two mathematical models solved using classical optimization technique. results from those show that ML-RFID model gives profit than existing traditional system.