Accurate counting of stacked materials is a critical task in automotive manufacturing, where even minor errors can disrupt production schedules and inventory management. Subpixel developed an AI-powered solution to automate the counting of stacked leather sheets, combining deep learning and machine vision to tackle a complex industrial challenge.
Challenges Addressed
- Variable Layer Thickness – leather sheets of differing thickness required precision beyond standard inspection methods.
- Subtle Layer Borders – identifying boundaries between layers is difficult due to minor differences in texture and color.
Innovative Solution
By leveraging advanced deep learning algorithms, our system can:
- Recognize subtle characteristics of each leather sheet,
- Differentiate layers accurately despite thickness variation,
- Automate a process that was previously time-consuming and error-prone.
Business Benefits
Implementing this solution allowed our client to:
- Improve production accuracy and maintain inventory consistency,
- Increase efficiency by automating a labor-intensive process,
- Enhance quality control, ensuring that the right number of sheets are processed for automotive parts.
Why Subpixel?
Subpixel applies machine vision, AI, and automation expertise to solve highly specific industrial challenges, delivering solutions that boost efficiency, accuracy, and reliability in manufacturing processes.
Looking to automate complex counting tasks in your production line?
Contact us at info@subpixel.hr to discover how Subpixel’s AI solutions can optimize your operations.