Facilitate Machine Learning to Detect Pseudo Errors in Quality Assurance

June 13, 2018

Machine learning can optimise production processes by detecting pseudo defects in quality assurance – turning data into actionable improvements.

I highlight this case because it shows how AI makes organisations more resilient – by using data to improve quality, reduce waste and support people in making better decisions.

A new article published by me on the platform Industry of Things.

Machine learning methods can be used to optimize production processes. A practical example shows how machine learning contributes to the detection of pseudo defects in quality assurance.

Most companies now have a digital strategy and are aware of the need to further develop their products, services and internal processes on the basis of intelligent, digital solutions. However, practical experience with the technologies is often still very limited. Therefore, many companies try out first approaches in Proof of Concepts in order to quickly expand the new competencies and, if necessary, to live positive cultures of failure.

Here is the link to the full article (in German): Machine Learning in der Qualitätssicherung: Pseudofehler erkennen.