Case Study

TopX Inspection Analyzer

Offline-first analytics that makes inspection data easier to understand, validate, and act on after measurement — from pin-level CSV to customer acceptance.

Python / Flask3D CoplanarityPin MapsReport Export

Problem

Inspection systems generate large volumes of CSV, bitmap, and DAT output. Engineers need to review repeatability, spatial drift, coplanarity, and pin-level risk — often offline, often under production pressure, and often without a unified analytics tool.

Approach

  • Monitor folders recursively for InspectionResults and PinsFound CSV families.
  • Parse and cache pin-level data for low-latency dashboard responses.
  • Render spatial heatmaps, 3D coplanarity/seating-plane views, and tolerance-ring pin maps.
  • Compare sources across platforms with best-fit registration and drift timelines.
  • Export shareable interactive HTML reports and printable customer views.

Result

A self-contained analytics suite that closes the loop between raw inspection output and customer-reviewable acceptance — supporting validation workflows, defect drilldowns, and production-quality intelligence.

120µm
Pin map rings
12+
Analytics tabs
Offline
Factory-ready

My role

Sole designer and developer — architecture, CSV/DAT parsers, the in-memory inspection cache, every visualization (ECharts + ECharts GL), the report-export pipeline, licensing and customer/internal mode gating, and the in-app wiki and help system.

Stack

Python / FlaskECharts + GLVendored offline assets Best-fit registrationHTML / Word / PPT exportLicense gating
Inspection analytics dashboard with 3D heatmap and tolerance scatter plots High-density connector inspection target
Capabilities

Process intelligence

  • Overview, process health, deviation analysis
  • Spatial heatmap and repeatability review
  • Pin explorer and inspection list views

3D metrology views

  • 3D coplanarity with seating-plane analysis
  • Radial XYZ charts with tolerance rings
  • Optiviz DAT correlation and source matching