Case Study

AI-based Quality Inspection for Salt Packet Quality Monitoring and Counting​

Leveraging Artificial Intelligence to Enhance Precision and Efficiency in Salt Packet Production​
Specialized cameras capturing images of salt packets​
%

Accuracy in tracking packet count​

%

Reduction in undetected defective packets

tonnes

of salt bags analysed and counted every day ​

Background

The chemical manufacturing industry is increasingly adopting AI and machine learning to streamline operations and improve accuracy. This shift towards digital transformation enhances quality control, reduces costs, and boosts production efficiency. AI-based quality inspection systems offer real-time monitoring and data analytics, becoming standard practice to ensure high production standards and operational excellence in manufacturing.

A leading chemical manufacturer aimed to enhance its salt bags assembly line's efficiency and accuracy, moving away from error-prone manual methods to address operational challenges with a more advanced AI-powered monitoring solution.

Challenge

The client, a leading chemical manufacturing company, faced significant challenges in enhancing the efficiency and accuracy of its salt pack assembly line operations. 

The challenges encompassed:

  • Accurate Inspection of Defective Packets: Ensuring thorough and precise detection of defective packets, which was difficult with traditional manual methods.
  • Tracking On-loading and Offloading Processes: Monitoring the movement of packets during loading and unloading in trucks to maintain logistical oversight.
  • Maintaining Precise Production Records: Keeping accurate production records was hampered by the error-prone nature of manual data entry.

These industry-wide issues have driven a shift towards AI and machine learning to enhance quality control, regulatory compliance, and operational excellence in manufacturing.

The client sought to address these challenges by integrating an AI-based quality inspection solution for enhanced accuracy and efficiency.

Solution

Tata Elxsi implemented a cutting-edge AI-based video analytics platform to revolutionise the client's salt pack assembly line operations. The AI-based quality inspection system involved the installation of specialised high-resolution cameras to capture detailed images of salt packets, enabling precise visual inspection. Advanced AI algorithms were deployed for defect detection and flag defective packets in real-time, ensuring high-quality control standards.

The system also monitored on-loading and offloading activities in trucks, providing comprehensive oversight of logistical processes. Real-time data analytics were integrated to maintain accurate production tracking, enhancing transparency and operational efficiency.

Salt pack analysis on conveyor belt
Loading and unloading process being monitored​
Analytics dashboard showcasing real-time alerts​

Impact

The implementation of Tata Elxsi's AI-based quality inspection system significantly enhanced the client's salt pack assembly line operations, aligning with current market trends. Key highlights include:

  • Defect Detection: Reduced undetected defective packets by 90%, ensuring superior quality control.
  • Operational Efficiency: Increased efficiency by 40% through automated monitoring.
  • Production Accuracy: Achieved 99.97% accuracy in tracking production and packet counts.
  • Time Savings: Reduced manual monitoring efforts by 70%.

In a single quarter, the AI system analysed over 250 tonnes of packs being counted every day through AI, showcasing the transformative impact of AI-driven solutions on manufacturing operations.

Services rendered

Tata Elxsi

  • Market Research and Need Assessment
  • Hardware Procurement and Support
  • AI Model Development
  • System Integration
  • Continuous Support and Optimisation

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