Quality control remains a primarily manual process in the manufacturing sector. This talk draws upon real-world instances, showcasing how high-precision manufacturers grapple with costly recalls due to inspection errors and how traditional manufacturers risk losing vital operational knowledge due to the turnover in their aging workforce—an issue that is particularly challenging to address in the current labor market.

We will show how AI-assisted visual inspection systems can mitigate these challenges and reduce QA costs. These systems augment the quality and speed of human inspections, create a digital store of operational knowledge, and facilitate data-driven root cause analysis to eliminate defects. Using tailored AI software and off-the-shelf hardware, we will discuss how these systems can be installed and retrofitted onto existing equipment within days.