Three Black Belt Projects, Three Predictive Engineering Wins

Originally published in Dr. Eric Maass's Predictive Engineering Newsletter (Design for Six Sigma and Supply Chain Resilience). Dr. Maass is Six Sigma BELT Guru's Master Black Belt certifying partner. Republished with credit.

This edition shares three Black Belt projects from a Medtronic site in Colorado that show what happens when DFSS meets real medical device challenges: in software and systems, in reliability and in manufacturing.

The anchor: Three Black Belt Projects, Three Predictive Engineering Wins

One of the most rewarding parts of training DFSS Black Belts is seeing the successful outcomes, and their impact on the product and the people. At the Medtronic site in Colorado, several DFSS (DRM in Medtronic terminology) candidates addressed different aspects of an important new medical product, StealthStation S8. Predictive Engineering helped each of them deliver results that would have been hard to achieve in any other way.

Yvan Paitel: StealthStation software performance (navigation latency)

StealthStation S8 allows the surgeon to perform brain surgery and see his or her actions overlaid on an image from a CT scan or MRI. Latency greater than 250 milliseconds would be noticeable and might distract the neurosurgeon during very intense procedures.

Yvan is among Medtronic's first Software DFSS Black Belts. He identified noise and control factors using a P-Diagram, ran a sequence of designed experiments and Response Surface models, and combined the response surface models with Monte Carlo Simulation to significantly reduce latency: the delay between when the surgeon moves a scalpel and sees it on the display.

Result: Latency went from being noticeable by the neurosurgeon about half the time to being noticeable less than 5% of the time.

Richard Hage: StealthStation reliability

The prior product, StealthStation S7, had a mean time between failures of about 2 years. I might have said, "not bad". Richard performed Pareto analysis of past reliability issues and complaints, identified possible causes of failures and complaints using a Use Condition matrix, and used Monte Carlo simulation of the reliability model he developed to determine how to improve MTBF (Mean Time Between Failures).

Result: Richard's effort doubled the MTBF from 2 to 4 years!

Lou Kucera: StealthStation manufacturing

Lou was one of Medtronic's first DFSS / DRM candidates to apply DFSS approaches to manufacturing and assembly challenges, merging Design for Six Sigma with Lean Six Sigma approaches.

Result: Lou enabled first-time successes in manufacturing and saved Medtronic half a million dollars in the first year alone.

A Hollywood moment

Late in the development cycle, Hollywood came calling. A new Marvel movie was underway, based on a superhero who was a neurosurgeon before a life-changing event. StealthStation S8 was used in an early scene. Medtronic people attended a showing of the movie, Doctor Strange, and cheered during the few seconds that their "baby", StealthStation S8, showed up on the silver screen!

— Eric Maass

From the field: INCOSE's September Journal Leads With AI Risk and Safety

INCOSE released the September issue of its Systems Engineering journal. The lead paper takes a systems-level approach to AI risk and ethics, relevant for teams integrating AI into medical devices or semiconductor processes. Risk assessment at the component level misses failure modes that only appear at the system level. DFSS practitioners have understood that for decades through P-diagrams and system-level transfer functions.

Also in this issue: SysML v2 extensions for safety analysis, model-based cybersecurity for automated vulnerability reporting, and LLM quantization trade-offs for engineering applications.

I keep the INCOSE journal in my working library because systems engineering guidance tends to run ahead of adoption in quality and DFSS practice. What gains traction there often appears later in standards and audit criteria.

Source: INCOSE Systems Engineering Journal, September 2026.

Links worth bookmarking

Sahajanand Medical Technologies Taps Siemens for PLM: An Indian medical device manufacturer adopts Siemens' product lifecycle management platform to integrate design, manufacturing and regulatory data under one system.
THINK Surgical Consolidates Design Controls and Quality Management with Cognition's Compass® MED
SOPHiA GENETICS Navigates First International Clinical Study with Greenlight Guru
ACME Medical Equipment Expands Engineering and Design Services: A Cleveland-based firm doubles down on engineering-driven medical device design, focusing on the early-phase development work where predictive methods matter most.
Sequenex Renews ISO 13485 QMS Certification for Medical Device Software: A reminder that quality management system certification is a living commitment, not a one-time milestone.