Development of an automation framework for 1D measurement

Abstract

Modern laser micromachining machines must move with very high accuracy to keep product quality consistent. At 3D-Micromac, the earlier calibration process used several separate tools: one for moving the axis, another for reading the laser inter- ferometer, and a spreadsheet for the calculations. This separation made the work slow, error-prone, and hard to repeat. This thesis builds a single, automated framework that joins all steps from axis motion, data capture, error calculation, and report creation inside the company’s microSTAGE software. The framework has four main parts Motion Control, Mea- surement, Analysis, and Reporting. The different parts can communicate with each other seamlessly thanks to standard file formats and clear programming interfaces. Python handles the maths and plots. Ready-made HTML templates turn the results into calibration certificates that follow the relevant international standard. Tests on a 200 mm linear axis show that the new tool matches the results of the old spreadsheet and more accurate while cutting total calibration time from about two hours to under twenty minutes. After applying the correction table produced by the framework, the overall positioning error fell by roughly one-third. The new system removes manual file handling, keeps a clear record of every data point, and can easily grow to cover more axes, different sensors, or future standards making 3D-Micromac’s machines easier to calibrate and more reliable.