Materials Engineering & Applied AI

Iver
Olsen

I develop teams, systems, and strategies that work.

15 years in medical device manufacturing — from failure analysis and materials selection to quality management and regulatory strategy. Now applying that same approach to AI/ML tooling for engineering teams.

15+
Years Experience
$500M
Portfolio Supported
85%
Plating FPY From 11%
40%
Cost Reduction via Insourcing
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About

I build the thing that doesn't exist yet

I started as a lab tech — running tensile tests, prepping metallographic samples, learning how materials actually behave. That hands-on foundation carried me through seven years in medical devices, a stint in Houston doing failure analysis for the energy sector, and eventually into engineering leadership at A-dec, where I manage the materials and clinical engineering function for a global dental manufacturing operation.

The common thread across all of it: someone points at a gap — no lab, no quality system, no process, no data — and I figure out how to stand it up, prove it works, and make it stick. That's taken the shape of building an ISO 17025 QMS from scratch, turning around a plating line that was scrapping 90% of parts, standing up a BSL-2 microbiology program, and developing EU MDR compliance strategy for a $140M device portfolio.

I hold a BS in Materials Science & Engineering from the University of Utah. ISO 13485 auditor trained, Lean Six Sigma Black Belt coursework. Selected from 7,500 global engineers to present original research at TE Connectivity's annual conference in Prague.

ISO 13485ISO 17025EU MDR Failure AnalysisSEM / EDSPython Analytics Lean Six SigmaProcess ValidationElectroplating BiocompatibilityPLM SystemsKPI DevelopmentApplied AI/ML
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Areas of Practice

These are the areas I work in and the problems I solve. Most of my career has been in medical devices and manufacturing — the AI/ML work is where I'm heading next.

Materials Engineering
Materials selection, failure analysis, and characterization across medical device, energy, and precision manufacturing. I've spent most of my career understanding why materials behave the way they do - and specifying the right ones for the job.
Failure AnalysisSEM/EDS/XRFSpec Development
Applied AI/ML
Actively building skills in machine learning and AI tooling for engineering applications. Current focus areas include RAG systems for technical documentation, automation workflows, and exploring how ML can improve materials and process decision-making.
Python / ML FundamentalsRAG & LLM ToolingAutomation WorkflowsAzure
Root Cause Analysis
Structured, systematic problem-solving for manufacturing and quality issues. My approach starts with the process, not the symptom - mapping the system, identifying critical-to-quality factors, and driving to root cause before jumping to fixes.
Fishbone DiagramsCTQsProcess MappingResolution
Quality Management Systems
Design, implementation, and remediation of ISO 13485 and ISO 17025 quality systems. I've built QMS programs from scratch and led teams through successful accreditation and audit cycles.
ISO 13485ISO 17025QMS DesignAudit Prep
Regulatory Compliance
EU MDR strategy development, FDA 21 CFR Part 820 compliance, and technical file authorship for Class I, II, and III medical devices.
EU MDRFDA 21 CFR 820Technical FilesPMCF
Process Validation
IQ/OQ/PQ protocol development and execution for manufacturing processes and test methods, aligned to ASTM, ISO, and FDA standards.
IQ/OQ/PQASTM / ISOTMVBiocompatibility
Process Improvement
DMAIC-driven improvement for high-scrap manufacturing lines. Plating, extrusion, assembly - diagnosing the bottleneck, implementing controls, and getting first-pass yield where it needs to be.
DMAICRoot CauseSPCLean
Lab Strategy & Analytics
Laboratory insourcing strategy, KPI framework development, and Python-based analytics for engineering and quality teams. I've built lab programs from the ground up and developed the metrics to prove they work.
PythonKPI DesignLab InsourcingData Visualization