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Customers / FAQs

Frequently asked questions.

Answers to common questions about Waywiser inspection systems, deployment, AI-driven quality decisions, and production integration.

General

Waywiser systems detect surface defects such as scratches, dents, cracks, contamination and coating irregularities, as well as dimensional deviations from defined tolerances. Detection capabilities depend on the inspection modality (2D, 3D or combined) and the configured sensor setup tailored to your specific part characteristics and quality requirements.

Waywiser systems are designed for inspection at production speed. Actual cycle time depends on part geometry, inspection scope and sensor configuration. Each system is engineered to match your required throughput without creating bottlenecks in the production flow.

2D inspection detects visible surface deviations such as scratches, contamination, coating defects and visual anomalies. 3D inspection performs dimensional verification against defined tolerances, including lengths, diameters, thread geometry and form deviations. Many deployments combine both modalities within a single inspection cycle, depending on part requirements and quality objectives.

Yes. Waywiser systems support combined 2D and 3D inspection within a single station. Surface inspection and dimensional measurement are executed in one cycle, resulting in a single inspection decision per part — fully documented with both surface data and dimensional results.

Waywiser systems learn from a single reference part. Calibration and teach-in are performed automatically, without the need for large datasets, manual feature programming or external vision specialists.

No. Waywiser systems do not require CAD data or manual feature programming. The inspection model is generated automatically based on the reference part and configured inspection parameters, enabling fast and flexible deployment.

Integration & Deployment

Yes. Waywiser systems can be deployed as compact stand-alone inspection cells or as fully integrated stations within automated production lines. Integration scope including part feeding, sorting, line control and MES/ERP connectivity is configured to match your existing production environment and process architecture.

Waywiser systems support standard industrial interfaces for seamless integration into existing IT and automation environments. Inspection data including results, images, heatmaps and measurement values can be transferred via database connections, APIs or file-based export and integrated into MES, ERP and quality management systems.

Deployment timelines depend on system configuration and integration complexity. The reference-part-based teach-in significantly reduces commissioning effort. The system learns from a single part, without requiring defect libraries or manual feature programming. Stand-alone systems can be deployed within a short timeframe, while fully integrated solutions include additional validation and process alignment steps.

AI & Software

The system is trained using a single reference part that represents a known-good condition. During automated teach-in, the AI learns the acceptable geometry and surface characteristics. No defect datasets, manual labeling or feature programming are required. This enables fast deployment while ensuring consistent inspection aligned with your production standards.

The system learns the appearance and geometry of a reference part during automated teach-in. During production, each part is compared against this learned reference. Deviations are detected, visualized as a heatmap and classified as OK or NOK. All inspection results including images, measurements and decision data are stored to ensure full traceability and transparency.

Yes. Training and inference run directly on the inspection system. The architecture is designed for self-contained operation without reliance on external compute infrastructure, ensuring stable performance and data availability within production environments.

Each inspected part generates a heatmap highlighting deviations from the learned reference. This visualization enables precise localization of defects and provides transparent, verifiable inspection results supporting root cause analysis, process optimization and auditability.

Handling of part orientation is defined by the overall inspection and feeding concept. For controlled environments, consistent orientation ensures maximum inspection stability. In less controlled scenarios, the system configuration is adapted to handle expected variation.

Yes. Inspection setups are stored as configurable recipes for each part type. Changeovers are fast and require no reprogramming, enabling efficient inspection across small batches, high-mix production and frequent product changes.

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