Increase Manufacturing Productivity with Edge Machine Learning

Working with the Edge Impulse team, Advantech developed a monitoring system that flags even tiny delays, for more precise fine-tuning with less human oversight.

Case Study Overview

Manufacturing at full capacity means making every second count. If you can find the bottlenecks that are slowing down your assembly line, you can increase efficiency and productivity. Manufacturing managers, roaming the factory floor, can address delays, but they can’t be everywhere at once. The engineers in Advantech’s new AIoT division wondered if they could help, by using video analytics to find holdups faster. Working with the Edge Impulse team and their industry-leading edge ML development platform, Advantech developed a monitoring system that flags even tiny delays, for more precise fine-tuning with less human oversight. The new setup, now in place on a live assembly line, can easily be re-trained to monitor other production tasks.

In this case study, learn how they achieved the following results:

Faster detection of idle time raises assembly-line productivity
Managers free up time to focus on production planning and operations
Manufacturers can easily deploy video analytics to improve production efficiency, even if they have no AI experience