Alignment issues, correlation techniques and their assessment for a visible light imaging-based 3D printer quality control system

Abstract

Quality control is critical to manufacturing. Frequently, techniques are used to define object conformity bounds, based on historical quality data. This paper considers techniques for bespoke and small batch jobs that are not statistical model based. These techniques also serve jobs where 100% validation is needed due to the mission or safety critical nature of particular parts. One issue with this type of system is alignment discrepancies between the generated model and the physical part. This paper discusses and evaluates techniques for characterizing and correcting alignment issues between the projected and perceived data sets to prevent errors attributable to misalignment.