We design complete inspection solutions from requirement to deployment, translating production constraints into robust architectures. TR2 defines the sensing stack (RGB, 3D, SWIR, hyperspectral), optics and illumination, mechanical integration and line interfaces, then validates performance through test plans and acceptance criteria. Our experience spans high-throughput conveyor setups, constrained installation spaces and demanding surface/material conditions, ensuring designs that remain stable under real industrial variability.

Key capabilities
- Requirements engineering: defect taxonomy,               tolerances, throughput, environmental constraints
- System architecture: sensor selection,    optics,           lighting design, triggering and synchronization 
- Mechanical and automation integration: mounts, 
 encoders, PLC I/O, reject handling
- Validation: GR&R-style repeatability checks, golden
samples, acceptance protocols

Typical deliverables
- System concept and BOM, integration drawings and
risk assessment
- Inspection recipes and calibration procedures
- FAT/SAT methodology and performance report

TR2 develops production-grade AI pipelines for inspection, classification and anomaly detection, designed for reliability, traceability and maintainability.
We build models that handle real factory variation (lighting drift, material batches, edge cases), using curated datasets, controlled labeling and continuous evaluation.
Our deployments include edge inference optimization and enterprise integration, enabling scalable rollouts across multiple lines and sites.

Key capabilities
- Model development: detection, segmentation,
anomaly detection, multi-class grading
- Dataset engineering: labeling guidelines, imbalance
handling, hard-negative mining
- MLOps: versioning, reproducible training, 
performance monitoring and drift detection
- Deployment: edge optimization
(latency/throughput), API integration, user workflows

Typical deliverables
- Trained models with metrics, confusion analysis and
acceptance thresholds
- Inference pipeline and monitoring dashboards
- Update strategy for continuous improvement (new defects, new SKUs) 

We convert raw inspection data into actionable quality intelligence, enabling root cause analysis and process optimization.
TR2 structures inspection outputs (features, scores, measurements, events) and correlates them with production metadata (time, batch, machine parameters) to identify trends, drift and recurring failure modes.
This supports faster decisions on line tuning, maintenance and yield improvement.


Key capabilities
- Data structuring: event logs, defect maps,
measurement series, traceability links
- Analytics: SPC indicators, trend/drift detection,
anomaly clustering and dashboards
- Correlation: defect-to-parameter analysis, batch
comparisons, line-to-line benchmarking
- Reporting: audit-ready records, quality summaries
and continuous improvement insightsz

Typical deliverables
- Data model and storage pipeline (edge-to-cloud or
on-prem)
- KPI dashboards and automated reports
- Root cause investigation tools (filters, comparisons, drill-down views)