Use Case Design Change

1-Click-AI-Trainer in action

Technical Paper

Abstract

Adapting quality assurance to frequent design changes in manufacturing is costly, time-consuming, and prone to human error. Traditional methods require extensive equipment modifications, personnel training, and complex reprogramming. This use case demonstrates how maXerial's 1-Click-AI-Trainer enables manufacturers to rapidly deploy custom AI models for quality inspection without coding expertise or AI specialists. Using the example of an automotive supplier adapting to PCB design changes, the paper shows how domain experts transform their industrial knowledge into actionable AI models through simple supervised learning. The platform enables rapid adaptation to design changes, reduces operator bias, automates repetitive tasks, and eliminates vendor lock-in. Operating on standard hardware at just 25W power consumption, the solution supports both cloud and offline deployment with double encryption for data security. By combining human expertise with AI-driven efficiency, the 1-Click-AI-Trainer provides manufacturers a cost-effective, agile approach to quality assurance in competitive, rapidly changing production environments.