Autonomous systems for
critical manufacturing.

DR produces an image immediately, allowing the control system to assess image quality and adjust source settings, detector parameters or robot pose. It is better suited to robotic closed-loop inspection than workflows that require a separate imaging-plate readout step.

Qualification note: resolution, penetration and coverage must be confirmed with representative parts, image quality indicators and the applicable Canadian inspection standard.

Large aerostructures can be costly or risky to reposition. A mobile robot or long-travel gantry brings the process to the component and can combine visual localization, automatic measurement and quality checking in the same work cell.

The reference AFP figures describe a specific engineering configuration and are not universal guarantees.

Measurements in Fx, Fy, Fz, Tx, Ty and Tz give the controller information about both contact force and moment. This helps manage surface variation, tool wear and contact transitions during finishing tasks.

Process feasibility depends on material removal rate, abrasive selection, surface tolerance and robot stiffness.

AI can assist with background removal, image enhancement, defect classification and marking. The intended role is decision support and consistent record creation; final acceptance remains aligned with the qualified inspection procedure and responsible personnel.

Training data, false-call rate and validation samples should be agreed during the feasibility stage.

Start with geometry, material, wall thickness, weld map, current process, required standard and production rate. A representative sample is used to establish access, image or process quality, cycle time and acceptance criteria before a production system is specified.