a mechanic's hand wearing gloves installing the right crank arm on the bottom bracket with a workshop background

META-aiviCase Study

Bicycle Frame Tubes Counting Using AR + AI

Customer

The customer is a manufacturer of high-quality bicycle frames with over 40 years of experience in the cycling industry.

Case

Streamlining Tube Counting for Accurate Production

The customer needed a more efficient way to account for the various metal tubes (such as the top tube, down tube, head tube, seat tube, bottom bracket, seat stays, and chain stays) used in frame production. With the goal of improving accuracy and streamlining operations, they explored advanced technologies like AR and AI to count materials automatically. This approach would ensure precise counting of components, align production output with demand, and reduce manual effort while enhancing overall efficiency.

a mechanic's hand wearing gloves installing the right crank arm on the bottom bracket with a workshop background

Challenge

Inaccurate Manual Counting and Material Management

Ensuring the exact quantity of tubes received from suppliers was crucial to meet production needs without surplus or shortages. In addition, manual counting of metal tubes for bicycle frame production often led to inaccuracies, resulting in discrepancies between the number of tubes available and the number required for bicycle frame assembly. These manual processes were prone to errors and inefficiencies, highlighting the need for a more reliable and precise counting solution.

Solution

AR + AI Solution for Precise Tube Counting

To address the counting challenges, the customer implemented META-aivi, a unique AR + AI vision system capable of precisely counting bicycle frame tubes. Operated easily through mobile devices like tablets and smartphones, META-aivi reduced human error by automating the counting process. The system’s user-friendly AI model training platform also enabled rapid development and customization of models for different types of tubes and bicycle frame components. This smart solution ensured accurate component counting, minimized errors, and significantly enhanced operational efficiency in bicycle frame production.

Outcome

Real-time automated counting, streamlining operations and boosting productivity
Achieved 100% counting accuracy, ensuring precise counting of bicycle frame tubes
Minimized human error by automating the counting process, reducing manual mistakes