# Service: Quality Inspection Implementation

## metadata
- title: Quality Inspection Implementation Service | Klyff
- route: /services/quality-inspection-implementation
- timeline: 8-12 weeks turnkey deployment
- outcome: Automated optical defect detection

## Overview
Full-lifecycle optical inspection delivery for manufacturing quality teams: camera mounting, strobe illumination, PLC interlock integration, dataset annotation, and production commissioning within 8 to 12 weeks.

## Performance Benchmarks
- **Implementation Window:** Complete defect detection live on lines in 8-12 weeks.
- **Labor Overhead:** 60%+ reduction in manual visual inspection labor.
- **Detection Precision:** 95%+ defect detection accuracy across microscopic and surface flaws.
- **Return on Investment:** Average 3-month payback period.

## What We Do

### 1. Custom Model Training on Defect Images
- Fine-tunes pre-trained vision architectures (YOLO, ResNet, EfficientNet, ViTs) on your proprietary defect classes (scratches, solder voids, paint blemishes, dimensional flaws).
- Uses transfer learning to achieve 95%+ precision within 2-4 weeks without requiring massive labeled datasets.
- Delivers production models calibrated to your specific line lighting and production speeds.

### 2. Dataset Preparation & Annotation
- Hands-off dataset curation: bounding boxes and segmentation masks generated via human-in-the-loop and automated pre-annotation tools.
- Rigorous dataset split validation (train/val/test), class-imbalance correction, and filtering of ambiguous samples.
- Versioned dataset deliverables with full audit manifests for reproducible future retraining.

### 3. Edge Device Compilation & Deployment
- Compiles validated models for chosen industrial silicon (NVIDIA Jetson, Coral, Seeed reComputer, x86 IPCs) using TensorRT, OpenVINO, or ONNX.
- Handles quantization, runtime wrappers, containerization, and automated failover configurations.
- Validates real-time inference on active assembly lines within 2-4 weeks.

### 4. Integration with Quality & Plant Systems (MES, ERP, SCADA)
- Integrates inspection triggers and results via industrial APIs, MQTT, OPC-UA, and database connectors.
- Generates real-time operator alerts with visual bounding boxes, defect coordinates, and confidence metrics.
- Logs historical trends into Statistical Process Control (SPC) dashboards for continuous yield improvement.

### 5. Operator Training & Documentation
- Hands-on workshops for floor operators, manufacturing engineers, and quality managers on interpreting alerts and managing thresholds.
- Complete runbooks, architecture diagrams, API specifications, and troubleshooting manuals.
- Post-deployment support packages ensuring immediate response to model drift.

## Engagement Model
1. **Weeks 1-4:** Model training and proprietary dataset curation.
2. **Weeks 5-8:** Edge hardware compilation, line optical integration, and MES setup.
3. **Weeks 9-10:** Operator team training and process validation.
4. **Months 3+:** 3 months post-launch operational support and threshold tuning.