It's tempting to blame declining quality outcomes on the people doing the work, but the data points elsewhere: 2.8 million manufacturing job openings are projected through 2033 from retirements alone, roughly a third of adults score at the lowest measured levels of numeracy, and 79% of manufacturing leaders call the labor shortage their top challenge, while only 29% expect quality headcount to grow. Institutional knowledge has to live somewhere other than the next senior hire

Give two quality engineers the same general AI assistant and the same 8D to review, and you won't reliably get the same depth of analysis or conclusion, and neither one used the tool wrong. This post explains why that's a chatbot's design, not a flaw, and how MAD-Ai starts with the standard instead of the prompt: structured inputs, required evidence fields, embedded rules, and escalation triggers that enforce the same rigor regardless of who's asking. The engineer still makes

Manufacturing spent decades making sure a new hire could run a stamping press at the same rate and scrap rate as a senior operator. Grading an 8D or evaluating a corrective action never got that same discipline. This post makes the case for applying the standardization manufacturing already trusts for physical work to analytical quality work: grading 8Ds, cross-walking PFMEAs, and reviewing PPAP submissions to the same standard regardless of who's available. The engineer stil

When your most experienced engineers retire, decades of quality judgment walk out with them. MAD-Ai captures that decision logic — tunable, scalable, and deployable across every plant and shift — so your organization retains what it knows.

When quality engineers talk about AI, they don't ask for dashboards. They ask for supplier 8D review, PFMEA crosswalks, and MRB workflow automation — the execution work that drains engineering capacity every week.

When quality engineers talk about AI, they don't ask for dashboards. They ask for supplier 8D review, PFMEA crosswalks, and MRB workflow automation — the execution work that drains engineering capacity every week.

There's a critical difference between AI that helps your team work faster and AI that does the work. Discover why execution AI transforms quality capacity — not just productivity — delivering 29x faster supplier quality management.

Quality teams need AI that executes, not AI that generates. Learn why chatbots fall short of what manufacturing quality work actually demands — and what execution AI does differently across 8D, PFMEA, and corrective action workflows.

We’re excited to announce that Rick Heilshorn has been selected to speak at the AIAG Quality Summit this September. This opportunity reflects years of hands-on experience in engineering, manufacturing, quality, and AI-driven innovation and we’re proud to see MAD-Ai contributing to the future of smarter manufacturing and quality systems. If you’re attending the summit, make sure to put Rick’s session on your to-do list.