Automation of Metallographic Sample Etching Process

Abstract

Chemical etching is an integral part of metallographic sample preparation. Maintaining precise etch times can be difficult and therefore repeatability is limited. The aim of this work is to improve the repeatability of sample preparation using robotization. Prior to etching, metallographic samples of S355J2 (1.0577) structural steel were finely mechanically polished. For verification, 15 specimens were prepared using an in-house designed automated etching machine with a built-in 5-axis robotic arm and 15 specimens prepared manually by an expert metallographer. The samples were etched with Kourbatoff no. 4 reagent for 8 seconds in a beaker placed in an ultrasonic cleaner at 80 kHz. The samples were then cleaned in 7 beakers of cleaning fluid also placed in the ultrasonic cleaner. The robotic etching and cleaning process was optimized and the quality of the resulting surface is at least as good as that of the samples prepared by an expert metallographer. The surfaces were compared using a light optical microscope (LOM) and a confocal laser scanning microscope (CLSM). The repeatability of the preparation process is a key aspect for obtaining a large dataset of steel microphotographs for training a deep neural network that will be used in future research.