Case Study
Building AI Driven Sustainable Automation for Steel Industry
Vendor Shopfloors in India
Reduction in Scrap
Increase in efficient Offcuts
Background
The steel industry is facing challenges in traditional cut-and-bend steel rebar operations manual methods lead to substantial steel scrap and inconsistent rebar dimensions. Heavy dependence on manual labor resulted in slow production, increased errors and high energy consumption. Additionally, inefficient inventory management causes overproduction, delays and material shortages resulting to high operational costs and environmental concerns, which ultimately affect profitability and customer satisfaction.
Aligned with Tata Group’s mission to contribute towards global sustainability goals, Tata Elxsi collaborated with Global Steel Manufacturing Company to integrate cutting-edge technologies (IoT, AI) and intelligent inventory management systems to achieve real-time visibility of materials across service centers to avoid material shortage or overstocking.
Challenge
Key Implementation Challenges:
- Integrating data from multiple centers into a single, accessible system to track in real-time to improve production visibility.
- Legacy cut-and-bend machines that were not designed for IoT connectivity, coupled with machines from different vendors, resulting in compatibility issues when exchanging data.
- Network reliability issues due to majority of the service centers located at remote locations.
- Inefficient delivery scheduling and improper loading of finished products leading to unnecessary transportation emissions.
Solution
Tata Elxsi integrated IoT, AI and intelligent cloud-based inventory management systems to achieve real-time tracking of materials across service centers to avoid material shortage or overstocking.- The solution migrated the on-premise database and application to AWS, categorizing data into structured and unstructured formats. Structured data was moved to Amazon Aurora, and unstructured data to Amazon S3. Auto Scaling was implemented to ensure high availability and low response times, optimizing performance and scalability.
- Using IoT to monitor the health of machines through predictive maintenance which in turn reduced downtime preventing unnecessary machine breakdowns.
- Leveraging AI and machine learning to predict the demand for different material grades across various centers, optimizing inventory management.
- Implementing cross-center collaboration on the availability and use of offcuts, ensuring efficient utilization and reducing waste.
- Additionally, just-in-time delivery and optimized vehicle loading helped reducing unnecessary transportation emissions.
Impact
- This collaboration also focuses on predictive maintenance for cut-and-bend machines, reducing the carbon footprint.
- Real-time offcuts optimization reduces waste, maximizes raw material usage, and boosts overall production efficiency.
- Real-time dashboarding enhanced visibility, enabling to make informed decisions and improve operational efficiency.
Services rendered
Tata Elxsi
- Industry 4.0
- Inventory and Supply chain optimization
- Sustainability Consulting
- Custom software development
- IoT Integration