01. Problem Overview
Sonalika Tractors, one of India's leading agricultural machinery manufacturers, faced challenges in managing their vast inventory spread across multiple locations. The traditional methods for inventory tracking and management were inefficient, leading to delays, inaccuracies, and excessive manual intervention. As production demand increased, so did the need for a smarter, more efficient system to streamline inventory operations while reducing operational costs.
02. Proposed Solution
PredCo proposed a Smart Inventory Management system powered by RFID technology to address these challenges. By integrating RFID tags with our Industrial AI platform, Sonalika Tractors gained real-time visibility over their entire inventory, from raw materials to finished products.
The solution involved:
- RFID-enabled Asset Tracking: Implementing RFID sensors to tag every critical inventory item for seamless tracking across the supply chain. The system automatically updates the location and status of materials as they move through the production line.
- AI-Driven Inventory Optimization: Our platform utilized AI and machine learning to analyze data collected from RFID tags, predicting stock levels and reducing the risk of overstocking or stockouts.
- Real-Time Dashboards: Operators were given access to a unified dashboard that provided a single source of truth for inventory status, stock levels, and usage trends in real time, eliminating guesswork and manual updates.
- Automated Alerts and Replenishment: The system automatically generated alerts when stock levels dipped below predefined thresholds and triggered timely reordering processes to avoid interruptions in production.
03. Benefits
With the Smart Inventory Management system, Sonalika Tractors saw:
- Improved Inventory Accuracy: RFID tagging enabled over 99% accuracy in tracking, ensuring that inventory levels were always up to date.
- Reduction in Manual Labor: Automated data collection and reporting led to a significant reduction in manual labor hours, allowing staff to focus on more critical tasks.
- Optimized Stock Levels: AI-driven insights helped Sonalika manage stock more efficiently, reducing the holding cost of excess inventory and improving the flow of materials across production lines.
- Increased Operational Efficiency: The real-time inventory tracking system reduced downtime caused by stock discrepancies, leading to smoother production cycles and on-time deliveries.
