Automated visual inspections for wind turbine blade manufacturing
Spotter enables factory quality inspectors to automatically assess defects, removing ambiguity in acceptance criteria
Higher first-time quality
Spotter eliminates variability in damage assessment caused by human interpretation. This ensures consistent results regardless of operator training levels and minimizes risks of overprocessing or missing defects.
Lower cycle time
The system accelerates the inspection process by enabling operators to instantly capture the accurate location and size of defects on a part without requiring physical measurements.
Increased job satisfaction
By reducing repetitive inspection tasks, Spotter empowers technicians to focus on higher-value activities, problem-solving, and quality improvements. This makes inspection more meaningful and engaging.
Improve first-time quality
Factory QC inspectors validate defects against the predetermined acceptance criteria automatically just by taking a picture. Decisions are made by the Machine Learning algorithms trained on the most common shell and web defects aligned with the blade-specific acceptance criteria.
- Detect laminate wrinkles in seconds
- Interpret defects consistently
- Avoid quality escapements
Reduce cycle time
Defect size and location are marked in augmented reality and recorded along with a high-resolution picture and other information critical for the engineering team. This in turn streamlines engineering disposition and repair by enabling access to the layup beneath the damaged area, and generating contextual repair limits, chamfering, and lamination instructions specifically tailored to the individual blade design.
- Forget about tape measurements
- Eliminate paperwork
- Optimize staffing
What is Spotter?
Spotter is a digital quality control system for wind turbine blade manufacturing. It is designed for technicians conducting visual inspections of the shells and other components between infusion and closure.
Common problems faced by the quality professionals during visual inspections
Spotter enables shop floor technicians and engineering with superpowers and insights
Smartphone app for QC inspectors
Instead of performing manual measurements, operators simply point a smartphone at the approximate defect location. The system automatically records the damage, including its precise size and positional references to the leading edge and blade root. For more complex cases, the system prompts the operator to capture a higher-resolution image for detailed analysis in line with acceptance criteria.
- Real-time defect detection
- Augmented reality markers
- Contextual acceptance criteria
- Digital-first inspection form
Web-portal for engineers
Engineering teams monitor inspection progress through an interactive dashboard that visualizes damage on 3D models of the components. The dashboard allows defects to be filtered by status, type, component, and severity. Additionally, factory leadership benefits from performance reports that provide actionable insights into quality and production metrics.
- Prioritization of repairs
- Analytics for performance improvement
- Heatmaps
Backend
REST API Integration
Spotter features a REST API that is integration-ready, enabling connectivity with existing enterprise systems such as ERP, PLM, and MES. The system can be deployed on-premises using Docker containers for flexible and scalable implementation. Individual user profiles align with the roles and responsibilities of the quality department.