leftover plastic parts from plastic injection molding machine

META-aiviCase Study

Verifying Plastic Parts for Recycling Using AI

Customer

The customer is a leading provider of semiconductor packaging and testing services, specializing in developing innovative electronics.

Case

Mixed Plastic Recycling

In the pursuit of sustainable practices, companies often encounter challenges in effectively managing their waste, particularly when it comes to recycling. In this case, the customer was aiming to improve their waste management process of leftover plastic components before being recycled.

leftover plastic parts from plastic injection molding machine

Challenge

Preventing Recycling Contamination

The challenge stemmed from the repetitive and physical nature of the tasks involved in waste disposal, leading to workers inadvertently mixing items in the wrong bins. Despite efforts to enforce proper sorting procedures, some workers continued to place items incorrectly. This posed a significant concern for the customer as mixing items could result in fines. Furthermore, while automation was considered, it was deemed not viable to fully automate the process, necessitating the search for a more practical solution.

Solution

AI-Based Item Verification

To address these challenges, the customer implemented an innovative solution involving the setup of IP camera workstations integrated with META-aivi. Advanced AI models allowed for real-time classification of plastic parts, aiding workers in verifying that items were not mixed during the sorting process. As workers placed plastic components into designated bins, the AI model provided additional verification and reassurance, reducing the likelihood of errors and contamination. This AI technology-driven approach not only improved the efficiency of the waste management process but also offered a cost-effective alternative to full automation with robotics.

Outcome

Real-time classification reduced errors and contamination
Ensured proper waste disposal and compliance with recycling regulations
Contributed to the customer’s environmental sustainability goals
More Case
  • food quality inspection of apples on a conveyor in a factory

    Food Quality Inspection Using AR + AI

    META-aivi enables real-time detection of foreign objects in food production, addressing challenges associated with manual inspection such as worker fatigue and the risk of human error.
  • Deep Learning Inspection of Liquid Biotech Medicines

    SolVision’s deep learning facilitates the recognition of varying colored liquids and sedimentation levels for accurate classification and quality control
  • black and white labeled box

    Automating Quality Inspection of Lead Frames

    As semiconductor manufacturing becomes more sophisticated, the process of creating lead frames needs to improve in accuracy and yield.
  • a welder welding a piece of metal with sparks

    Welding Bead Defect Detection

    AI models can be trained and uploaded into the system for qualified welding points. This enables AI inspection of welded sections using AR glasses or a tablet device to quickly recognize defective welds.