AI-Based Product Counting Solution for Electronic Connector Manufacturer
ThirdEye Data developed and deployed an AI-powered product counting solution to automate and optimize the manual process of counting finished components in a high-volume manufacturing environment. The computer vision-based system allows production floor staff to use a mobile application to capture images of bundled products, such as wires and connectors, which are then analyzed by AI algorithms to deliver accurate, real-time counts. This solution has eliminated manual counting errors, improved operational efficiency, and enabled real-time analytics via a centralized dashboard. After the successful deployment of the MVP, discussions are underway for the next phase, focusing on enterprise-wide scalability and integration with existing systems.
THE CUSTOMER
BUSINESS GOALS OR CHALLENGES
Business Goals
- Automate Product Counting: Eliminate manual counting processes to reduce time, effort, and errors.
- Improve Packaging Accuracy: Ensure accurate quantities of components are packaged and shipped.
- Optimize Workforce Productivity: Free up staff from repetitive tasks to focus on more strategic activities.
- Enhance Decision-Making: Provide real-time data and insights into counting operations.
- Enable Scalable Deployment: Build a solution that can be expanded to additional product lines and facilities.
Understanding the Challenges:
- Manual Errors in High-Volume Counting: Human errors in counting bundles led to incorrect shipments and customer dissatisfaction.
- Time-Intensive Process: Staff had to double or triple-check counts to ensure accuracy, reducing operational throughput.
- Lack of Real-Time Visibility: Supervisors lacked immediate visibility into counting operations and discrepancies.
- Limited Scalability: Manual processes could not keep pace with growing production lines and product variants.
- Integration Needs: The solution had to fit seamlessly into the customer’s existing production workflows without major disruption.
Prerequisites and Preconditions:
To ensure successful deployment of the AI-based product counting solution, the following setup was implemented:
- Mobile Application Interface: Android- and iOS-compatible app for capturing product images and displaying counts.
- Curated Training Dataset: Created a labeled image dataset covering 50 different products during the PoC phase.
- Custom AI Models: Developed object detection models using YOLOv5, fine-tuned for wires, connectors, and small parts.
- Image Quality Assurance Module: Integrated an image pre-check to validate clarity and suitability for accurate counting.
- Web-Based Analytics Dashboard: Built a centralized dashboard for tracking counts, accuracy rates, and session logs.
- Secure Architecture: Ensured secure authentication, encrypted data transmission, and compliance with enterprise data policies.
THE SOLUTION
ThirdEye Data delivered an end-to-end mobile-first AI solution for automated product counting in a production environment, leveraging state-of-the-art computer vision and deep learning techniques.
Solution Highlights
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AI-Powered Image Counting: Used YOLOv5 models to detect and count bundled items from images taken via the mobile app.
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User-Friendly Mobile App: Provided staff with an intuitive interface to capture and review product counts on the shop floor.
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Image Quality Control: Built-in image clarity check ensured high accuracy before AI analysis.
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Real-Time Feedback: Counts displayed instantly to the user, confirming accuracy before packaging.
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Centralized Analytics Dashboard: Aggregated operational insights including session timestamps, count history, and user activity.
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Cross-Platform Support: App developed for both Android and iOS to maximize usability across the workforce.
Technologies Used
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YOLOv5: Real-time object detection optimized for identifying multiple components in crowded images.
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Convolutional Neural Networks (CNNs): Used for image feature extraction and segmentation to differentiate between individual units.
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Image Preprocessing Pipelines: Enhanced image clarity, contrast, and object boundaries for improved model accuracy.
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Mobile App Framework (React Native): Ensured smooth cross-platform user experience and fast performance on mobile devices.
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Secure APIs & Cloud Backend: Managed data flow, user sessions, and AI model hosting with encrypted communication.
VALUE CREATED
The AI-powered solution has significantly transformed the customer’s product counting process:
- 99% Accuracy Rate: Virtually eliminated manual counting errors, increasing packaging accuracy.
- 80% Time Savings: Reduced the average time to count components by over 80%.
- Enhanced Workforce Productivity: Staff were able to redirect efforts from repetitive counting to higher-value tasks.
- Data-Driven Oversight: Supervisors gained real-time visibility into counting activity and performance metrics.
- MVP Operational Across Units: Successfully deployed across multiple product lines with consistent performance.
- Scalable and Future-Ready: Currently in discussion for expansion into new departments and integration with inventory and ERP systems.
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