Iris Optics
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Data PipelinesOptical MetrologyManufacturing Test

AR/VR Waveguide OQC Dashboard

Building a test-data dashboard for optical KPI monitoring, lot disposition, yield analysis, and cross-vendor comparison.

Challenge

The client faced high-dimensional optical KPI data spanning multiple builds, configurations, and component vendors. It was difficult to make timely and accurate Outgoing Quality Control (OQC) decisions.

Approach

We architected a structured data pipeline that mapped complex measurement data to specification tables. We organized the data into KPI families and performed automated Cpk and yield analysis, surfacing the results in targeted dashboard views.

Outcome

The engineering and quality teams experienced significantly faster review cycles, better visibility into supplier performance, and clearer, data-driven release decisions.

Background

Advanced optical components like AR/VR waveguides generate vast amounts of measurement data during quality control. When multiple vendors are supplying different configurations, tracking performance and yield across builds becomes a massive data management challenge.

The Challenge

The engineering team was drowning in high-dimensional optical KPI data. Different vendors provided data in varying formats, and the relationships between different optical performance metrics were not easily comparable. Making objective, rapid disposition decisions at OQC was nearly impossible without hours of manual data wrangling.

The Approach

We designed and implemented a structured data pipeline specifically for optical test data:

  1. Data Standardization: We created ingestion scripts to parse varying vendor data formats into a unified schema.
  2. Specification Mapping: We mapped the ingested data directly against the product specification tables, automatically flagging out-of-tolerance parameters.
  3. KPI Family Grouping: We organized hundreds of individual metrics into logical “families” (e.g., efficiency, uniformity, stray light) to make the data digestible.
  4. Dashboard Implementation: We built interactive dashboard views that presented automated Cpk (process capability) calculations, yield trends, and cross-vendor comparisons.

The Outcome

The automated dashboard transformed the OQC process. What previously took days of manual analysis was reduced to minutes. The quality team gained immediate visibility into supplier performance trends, enabling clearer, faster release decisions and accelerating the overall hardware development cycle.