Computational investigation on the predictability of laser engraving depth on SS304

• Main Author: M J Anantha Krishnan
• Other Authors: Lai Changquan
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2023
• Subjects: Engineering::Materials
• Online Access: https://hdl.handle.net/10356/166793
• Institution: Nanyang Technological University

In this study, a computational investigation was done on the predictability of laser engraving depth and surface roughness on SS304 material. The first part of this study covers the theory, fundamentals of laser engraving, the observations and discussions from the characterisation of the samples and finally, the data collection process. Similarly, the second half of the study covers theory, the fundamentals of machine learning, the machine learning process, the results and discussion. This computational investigation proved the relationships between laser parameters, laser engraving depth and surface roughness. However, the approach taken for machine learning was incompatible and produced poor accuracy results. This was partially due to poor data quality obtained from the first part of the study; and the complex nature of the parameter interactions. The study ends with suggestions and improvements for future studies.