Iris Optics
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Supplier CorrelationOptical Metrology

Cross-Site Test Correlation

Aligning measurement results across internal and supplier sites.

Confidentiality & Anonymization Note

These examples are generalized and anonymized to illustrate Iris Optics capabilities. Details are modified to protect confidentiality and avoid disclosure of proprietary employer, client, or product information.

Challenge

Inconsistent measurement results between an OEM's internal labs and overseas supplier sites can cause ambiguity in yield and quality decisions.

Approach

We implemented a rigorous correlation methodology using golden samples, reference artifacts, and correlation matrices, establishing strict data governance and reviewing measurement physics at both sites.

Outcome

This correlation approach improves comparability, reduces yield debates, and ensures that both the OEM and the supplier speak the same language when it comes to optical quality.

Background

When optical hardware is designed in one country and manufactured in another, test correlation is paramount. If an OEM’s lab measures a part as a “pass” and the supplier’s factory measures the same part as a “fail”, the entire supply chain breaks down.

The Challenge

Hardware programs often face significant discrepancies in optical measurement results between their internal R&D labs and primary overseas suppliers. This leads to endless debates over yield, quality escapes, and root causes, significantly slowing down the NPI schedule.

The Approach

We deploy a comprehensive cross-site correlation strategy:

  1. Methodology Review: We first audit the measurement methodologies at both sites, identifying subtle differences in alignment, calibration, and environmental controls.
  2. Golden Samples & Artifacts: We establish a set of stable “golden samples” and reference artifacts that travel between the sites to baseline the equipment.
  3. Correlation Matrix: We run Gage R&R and correlation studies, building a matrix that quantifies offsets and scaling differences between measurement stations.
  4. Data Governance: We implement data governance policies to ensure that both sites analyze raw data using identical algorithms and parameters.

The Outcome

By quantifying and correcting differences between measurement sites, this methodology eliminates ambiguity in quality decisions. The OEM and the supplier can trust each other’s data, allowing teams to focus on resolving actual hardware issues rather than arguing over measurement discrepancies.