I prove out processes for a living. AI is just the newest one.
Roughly 30 years across manufacturing engineering, operations, and quality management, most of it hands-on in FDA-regulated medical-device manufacturing.
Who this is for
Manufacturers that need senior quality and operations work, or just an operation that runs, and cannot keep a senior quality engineer or a turnaround team on staff.
- Manufacturers whose CAPAs, audits, or nonconformances have outgrown the people available to work them.
- Operations priced out of enterprise consulting and six-figure eQMS suites, who still need the discipline those things promise.
- Teams that want AI applied to a real problem and proven before they rely on it, with someone who has run operations, not a chatbot demo.
Three ways the work shows up
Quality systems & investigations
CAPA and root cause rescue, nonconformance handling and disposition, response to audit findings, and QMS structure. The elements reviewers look for (verified causes, alternatives ruled out, evidence citations, real effectiveness checks), built into how your team works, not bolted on before the audit.
Controlled AI adoption
AI put to work on your real workflows, proven the way you'd prove any new process. The front door is the AI Control Plan: one workflow, failure modes identified, detection wired in, tested hard against your data, released with a control plan your team owns. The control has to match what the output can cost you.
Process optimization & hands-on support
Lean, PDCA, and Kata applied to bottlenecks, downtime, and waste. This is the work behind the measured results below. Done on the floor, with your people, so the improvement holds after the engagement ends.
The real results
Two years as plant manager of a $65M contract manufacturing plant, on an automated line that had never hit its rated output. I worked the Pareto: repeat motor failures first, then the next band of equipment failures behind them, attacking both how fast a failure was recovered and how often it happened at all.
Equipment availability went from 40% to 85%, and the throughput that freed carried on-time delivery from 91% to 99.8%.
The plant went from a $100,000 monthly loss in January 2020 to $450,000 a month in gross profit by February 2021. Those are the controller's numbers, not my estimates.
Verify the background on LinkedIn.
BS Mechanical Engineering (Oregon State) · MBA (University of Oregon) · ASQ Certified Manager of Quality / Organizational Excellence (CMQ/OE), held 2008 to 2020 · Quality leadership of teams ranging from 10 to 23 people · Plant management of a $65M operation with 120+ employees
How an engagement starts
Thirty minutes on the problem that is costing you sleep. Leave with a clear next step, whether or not we work together.
The first job is always the same: make it safe to see what's actually happening (no blame, no pitch) because once your team can see it clearly, they can act on it.
30 Minutes. Your Process. No Pitch.Need a defensible investigation right now? The Root Cause Analyzer is this same discipline, packaged so your team can run it themselves.