During the pandemic, I became involved with a company that was rethinking the work of the quality professional at fabrication shops. The traditional practice was to dispatch a company person to the fabrication business to see what was being built to make sure it conformed to the specification. The pandemic rendered site visits hard to pull off, but the quality standards could not be relaxed.
Such equipment manufacturers have to comply some of the strictest standards of any sector. It’s still surprises me that many companies manage the delivery of quality through spreadsheets, paper documents, disconnected folders, and manual processes. Systems like these are what technical people call fragile. They don’t cope well with change, they’re a pain to maintain, expensive to run, and are dangerously dependent on the knowledge of a handful of insiders.

When a defective part turns up, particularly if it has caused an upset, it’s then a five alarm fire trying to find the cause. Inspection records, supplier documents, and production histories may be scattered across multiple systems. And heaven forbid that the quality manager retires, or leaves for better opportunities.

You might not be surprised that the fragile quality system environment is attracting the attention of AI as a solution. Modern quality management platforms can connect previously disconnected processes, automate documentation, track corrective actions, and make quality information available through natural language conversations. Rather than hunting for the elusive records related to an obscure part, quality managers can just ask their systems questions, issue instructions, and focus on improving operations.

In this episode, I’m speaking with Onega Ulanova, co-founder of QMS2GO, and a former American Petroleum Institute auditor. We discuss the shortcomings of traditional quality management, the potential of AI-powered quality systems, and how better compliance can improve reliability, productivity, and cash flow.

👤 About The Guest

Onega Ulanova is the co-founder of QMS2GO, a company developing AI-powered quality management solutions for industrial manufacturers and service providers.

Her career includes roles as a quality manager, consultant, and lead auditor for the American Petroleum Institute, where she audited more than 200 facilities worldwide. She has extensive experience with API Q1, API Q2, and ISO 9001 quality management standards.

Together with her husband and business partner, Konstantin Dolgan, she is applying this experience to make quality management more accessible, automated, and effective.