Areal surface roughness metrology using compact coherence scanning interferometry for machining process control

Abstract

Characterizing surface roughness early in a factory process is critical for understanding stability and predicting final performance. However, many conventional roughness measurement techniques rely on destructive sampling, contact-based probes, or limited line-scan geometries. These constrain measurement frequency, introduce the potential for tool-induced artifacts, and provide incomplete areal coverage. These limitations reduce the ability to establish quantitative correlations between surface-generation parameters and resulting roughness. This work presents a non-contact, non-destructive areal metrology approach based on a custom implementation of Coherence Scanning Interferometry (CSI) engineered specifically for deployment in machining environments. The optical system employs a compact interferometric design approximately the size of a soda can. This is achieved through a custom optical system design that maintains CSI coherence performance within a significantly reduced enclosure. The architecture captures full areal topography rather than 1D traces, eliminating direction-dependent sensitivity and enabling high-coverage surface characterization per acquisition. Unlike traditional CSI instruments that require transporting parts to a stationary metrology system, the presented sensor is designed to be mounted at the end of external motion systems such as robotic arms, gantries, or multi-axis positioning stages. This mobility allows the metrology head to be brought directly to large, heavy, or in-process machined components that cannot be easily moved. The ability to position the sensor dynamically enables roughness measurements earlier and more frequently in the machining workflow, improving the detection of process drift and enabling identification of shallow or localized defects before value-adding operations occur. Application examples demonstrate how integrating mobile, compact areal metrology into machining workflows enhances process control, reduces downstream rework, and increases predictability in the production of precision-machined components.