Posts tagged AI Quality Engineering
4 articles
CAPA Closure Criteria: The Six Things That Have to Be True Before \"Closed\" Means Anything
A CAPA marked closed is a claim, not a fact. Containment recorded, corrective action recorded as a system change, effectiveness criteria written as a record instead of a checkbox, verification marked verified against evidence, an independent reviewer, and a recurrence window sized to the part, not the calendar. What the platform enforces for each, in practitioners' own words, and where the automatic recurrence chase is real but scoped.
PPAP Rejection Reasons: Why Packages Bounce and How Each One Gets Caught Before Submission
Most PPAP rejections are not a missing document, they are two elements that are supposed to say the same thing about the same characteristic and do not. Five recurring rejection categories from the reviewer's seat, the AIAG PPAP element and IATF 16949 clause behind each, and how QualityEngineer.ai's linked traceability graph surfaces the gap before a reviewer does.
PPAP Readiness Score: Why 'Complete' and 'Ready to Submit' Are Two Different Numbers
A PPAP package can show every element checked off and still bounce on the first read. Here is how QualityEngineer.ai splits readiness into two numbers that are never averaged together, an element completion headline and a structure quality score built from AIAG capability and traceability rules, plus the proactive findings that catch a gap before a reviewer does.
Fishbone and 5 Why Root Cause Analysis: How AI Keeps the Investigation From Stopping at Operator Error
Most fishbone sessions end with six branches that all say operator error, because whoever talks first in the room wins. Here is how our AI-guided Fishbone and 5 Why coach runs four distinct personas, tags every cause with an evidence level, seeds the board from your PFMEA and CAPA history, and blocks you from finalizing on an unproven hypothesis.