Case Study: How Design for Metrology reduced time to market.

Take a look at how designing for metrology can bring real gains in time to market realisation for product development.

Mike John CEng MBA

3/4/20263 min read

Insulin injection medical devices during assembly and manufacturing process.
Insulin injection medical devices during assembly and manufacturing process.

How Design for Metrology Reduced Time to Market in a Medical Device Validation Project

Introduction

In medical device manufacturing, failing a Gauge R&R study can halt product launch entirely. When this happens during IQ–OQ–PQ validation, production progression stops, regulatory timelines slip, and commercial impact follows.

In this case, a 0.1 mm surface profile tolerance prevented a product from moving to the next stage of validation — not because the component was nonconforming, but because the inspection strategy made statistical approval mathematically unachievable.

This case study demonstrates how upstream design decisions directly impact downstream validation performance — and how applying design-for-metrology principles eliminated the barrier without capital expenditure.

By applying Design for Metrology principles, we eliminated the validation barrier without capital investment and restored production momentum.

The Challenge

The product was an injection-moulded laryngoscopic device manufactured by a large US-based medical device company. The component featured:

  • Complex overmoulded geometry

  • Multiple overmoulding stages

  • A metal insert forming the structural core

The metal insert contained the only primitive geometry (planes, cylinders, circles) and therefore formed the datum structure for inspection.

The Complication

After overmoulding, most of this datum geometry became hidden.

The primary datum (Datum A) was a small planar land on the insert. While theoretically valid, it introduced high measurement sensitivity. One of the key inspection requirements was a 0.1 mm surface profile tolerance applied to the complex overmoulded surface.

At first glance, this appeared reasonable, however, when combined with the datum instability, the issue became clear:

  • A 1–2 micron variation in Datum A

  • Generated 8–16 microns variation in surface profile result

  • Consumed 16–32% of the tolerance

  • Resulted in Gauge R&R well above the required <10% threshold

The product could not progress through validation.

Why the Gauge R&R Was Failing

Surface profile tolerances carry a 2× sensitivity coefficient.

This means:

  • A 0.1 mm profile tolerance effectively creates a 0.2 mm measurement window.

  • To achieve <10% Gauge R&R, measurement variation must be ≤5 microns.

  • To achieve that, the inspection system must have capability near 0.5 micron.

For a medium-criticality feature on an injection-moulded overmoulded device, this level of measurement precision would likely require new capital equipment. The initial reaction internally was to attempt optimisation through programming and measurement strategy refinement.

However, the issue was not programming. It was structural.

The datum strategy amplified micro-level instability into macro-level statistical failure.

Our Approach: Moving Upstream

Rather than applying brute-force inspection refinement or recommending capital investment, we moved vertically in the process — engaging directly with the design engineering team.

The discussion focused on three questions:

  1. What is the true functional requirement of the feature?

  2. Why was the 0.1 mm surface profile tolerance selected?

  3. What is the real criticality classification?

What We Learned
  • The feature controlled cap fit and cosmetic continuity.

  • Z-axis control was significantly more critical than X/Y deviation.

  • The feature was medium criticality and not patient-critical.

  • The tolerance had been applied conservatively rather than functionally derived.

  • The design team were unaware of the 2× sensitivity multiplier of surface profile tolerances and its impact on Gauge R&R.

This was not a quality failure - It was a tolerance issue.

The Recommendation

Following analysis and discussion, we proposed:

1. Redefine the Primary Datum

Move Datum A from the small metal insert land to a larger overmoulded “shelf” feature that:

  • Covered a larger area

  • Provided improved stability

  • Better represented functional assembly geometry

2. Apply a Compound Surface Profile

Instead of a uniform 0.1 mm tolerance:

  • Z profile tolerance increased to 0.15 mm

  • X/Y profile tolerance increased to 0.3 mm

This aligned the tolerance with functional necessity rather than geometric uniformity.

The Results

The impact was immediate.

  • Inspection program updated

  • Datum stability significantly improved

  • Tolerance sensitivity reduced

  • First Gauge R&R study post-change achieved <10%

No new equipment.
No capital expenditure.
No redesign of tooling.

The product progressed to the next stage of validation without further delay. Most importantly, validation bottleneck risk was removed before market launch impact became material.

Key Lessons
  • Surface profile tolerances inherently double sensitivity.
  • Datum stability can dictate statistical success more than equipment capability.

  • Many Gauge R&R failures originate in design decisions, not inspection systems.

  • Design-for-metrology thinking reduces validation delays and unnecessary capital spend.

Conclusion

This case illustrates a critical principle in regulated manufacturing:

Measurement system problems are often tolerance architecture problems expressed statistically.

By aligning design intent, functional requirement, and metrology capability, it is possible to remove validation barriers without increasing inspection precision.

In this case, applying design-for-metrology principles reduced time to market, avoided unnecessary capital investment, and strengthened cross-functional understanding between engineering and quality.

About Aegis Metrology

At Aegis Metrology, we operate at the intersection of design, metrology, and regulated manufacturing — helping organisations reduce validation risk, improve measurement capability, and accelerate compliant product introduction.