Flanders Make clip on our self-learning PFMEA
(03-12-2025) There's an amazing video that was produced by Flanders Make on "A Self-learning PFMEA to Optimise Quality Risk Management", detailing research done in the AQUME SBO project by our researchers, in collab with UHasselt and Flanders Make.
Flanders Make made a two-minute clip of our research and development on "A Self-learning PFMEA to Optimise Quality Risk Management", which is part of the research "Making Root Cause Analysis (RCA) faster by combining process Failure Mode and Effects Analysis (PFMEA) with data collected from the factory floor."
Watch the video here: https://www.youtube.com/watch?v=YTrVYJqHo3U.
Our researchers Angel Lopez Aguirre and Mahdi Mokhtarzadeh developed this data-supported extension of PFMEA, together with Jan Van den Bergh of Digital Future Lab @UHasselt, in collaboration with Flanders Make as part of the AQUME SBO project. Their work brings a new level of objectivity and cost-effectiveness to quality risk management.
PFMEA is a systematic method used to identify, evaluate and prevent potential failures in manufacturing processes. Conventional PFMEA, however, relies heavily on expert judgement and can become outdated as conditions change.
The solution combines existing PFMEA documentation with quality control and production data through hierarchical modelling. As new data becomes available, the system automatically updates risk assessments, prioritises failure modes and causes, and reveals the trade-offs between mitigation cost and impact. In doing so, it transforms a static PFMEA into a living, data-driven system that evolves with every new data point, supporting more informed, evidence-based decisions during corrective and preventive action meetings.
Get involved on the socials on this topic via our LinkedIn post.
Watch the video here: https://www.youtube.com/watch?v=YTrVYJqHo3U.
Our researchers Angel Lopez Aguirre and Mahdi Mokhtarzadeh developed this data-supported extension of PFMEA, together with Jan Van den Bergh of Digital Future Lab @UHasselt, in collaboration with Flanders Make as part of the AQUME SBO project. Their work brings a new level of objectivity and cost-effectiveness to quality risk management.
PFMEA is a systematic method used to identify, evaluate and prevent potential failures in manufacturing processes. Conventional PFMEA, however, relies heavily on expert judgement and can become outdated as conditions change.
The solution combines existing PFMEA documentation with quality control and production data through hierarchical modelling. As new data becomes available, the system automatically updates risk assessments, prioritises failure modes and causes, and reveals the trade-offs between mitigation cost and impact. In doing so, it transforms a static PFMEA into a living, data-driven system that evolves with every new data point, supporting more informed, evidence-based decisions during corrective and preventive action meetings.
Get involved on the socials on this topic via our LinkedIn post.