Without data, you’re just another person with an opinion.” (W. Edwards Deming) What if your quality assurance is missing more defects than it detects? It sounds drastic, but it's a reality in  many companies. In industrial production, quality and cost efficiency are key. Yet, even in modern facilities, quality processes often overlook hidden patterns and anomalies buried in data. This is where machine learning comes into play: recognizing what humans can’t – early, automatically, and continuously learning. In this talk, I’ll show how quality assurance can be reimagined – from raw data to insightful visualization. We’ll look at an automotive supplier example, showing how machine learning can revolutionize QA – even without a high-end infrastructure. With retrofitted sensors, data can be collected from older machines to optimize processes, reduce waste, and gain a competitive edge. The tools are here, the data is there – it’s time to turn insights into impact!