Better 3D Inspection with Structured Illumination Part I: Signal Formation and Precision

TL;DR

This paper introduces a theoretical model for structured illumination microscopy to enhance 3D inspection precision and speed in quality control, analyzing surface types and optimizing sensor parameters for better performance.

Contribution

Develops a comprehensive signal formation model for smooth and rough surfaces in structured illumination microscopy, guiding optimization of sensor parameters for improved 3D metrology.

Findings

Identifies physical limits of measurement precision.

Provides rules for sensor parameter optimization.

Suggests strategies to maximize space-bandwidth-speed-product.

Abstract

For quality control in the factory, 3D-metrology faces increasing demands for high precision and for more space-bandwidth-speed-product SBSP (number of 3D-points/sec). As a potential solution, we will discuss Structured-Illumination Microscopy (SIM). We distinguish optically smooth and rough surfaces and develop a theoretical model of the signal formation for both surface species. This model is exploited to investigate the physical limits of the precision and to give rules to optimize the sensor parameters for best precision or high speed. This knowledge can profitably be combined with fast scanning strategies, to maximize the SBSP, which will be discussed in paper part II.