Industrial Visual Inspection with TinyML for High-Performance Quality Control

In industrial processes, predictive maintenance or automated optical analysis of artifacts is fundamental to ensure high-quality products with low costs. However, this step is still done by sophisticated systems or human operators. Automating this process with low-cost solutions while keeping high product quality is one of the most challenging goals of the Industrial Internet of Things (IIoT). IIoT fosters an automation-based production model that uses machine data to enable faster, more flexible, and more efficient production lines [1], leading companies to produce higher-quality goods at lower costs.