Machine Vision

The technical materials for this project are confidential. Below is a brief summary of the work.

Background: When a tire gets manufactured, a Tire Building Machine (TBM) cuts a long piece of rubber, with each piece intended for a single tire. However, various factors and external abnormalities that can cause the TBM to make cuts slightly too early or late, resulting in defective tires and material waste.

Aim: The goal of our team was to develop and implement an adaptive control system to significantly reduced material waste caused by inaccurate cuts.

Action: We developed a program that automatically detects and predicts when the TBM cutter was making inaccurate cuts, and then automatically adjusts the machine accordingly in real-time to correct the issue. The analysis was performed using Python and the program was deployed through ThingWorx for implementation.

Result: At the plants where this system was implemented, a substantial reduction in rubber waste was achieved, contributing to improved efficiency and reduced material costs.