Computational investigation on the predictability of laser engraving depth on SS304
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...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/166793 |
| _version_ | 1811686423394254848 |
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| author | M J Anantha Krishnan |
| author2 | Lai Changquan |
| author_facet | Lai Changquan M J Anantha Krishnan |
| author_sort | M J Anantha Krishnan |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T05:00:11Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/166793 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:00:11Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1667932023-05-13T16:46:34Z Computational investigation on the predictability of laser engraving depth on SS304 M J Anantha Krishnan Lai Changquan School of Materials Science and Engineering cqlai@ntu.edu.sg Engineering::Materials 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. Bachelor of Engineering (Mechanical Engineering) 2023-05-12T12:27:09Z 2023-05-12T12:27:09Z 2023 Final Year Project (FYP) M J Anantha Krishnan (2023). Computational investigation on the predictability of laser engraving depth on SS304. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166793 https://hdl.handle.net/10356/166793 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Materials M J Anantha Krishnan Computational investigation on the predictability of laser engraving depth on SS304 |
| title | Computational investigation on the predictability of laser engraving depth on SS304 |
| title_full | Computational investigation on the predictability of laser engraving depth on SS304 |
| title_fullStr | Computational investigation on the predictability of laser engraving depth on SS304 |
| title_full_unstemmed | Computational investigation on the predictability of laser engraving depth on SS304 |
| title_short | Computational investigation on the predictability of laser engraving depth on SS304 |
| title_sort | computational investigation on the predictability of laser engraving depth on ss304 |
| topic | Engineering::Materials |
| url | https://hdl.handle.net/10356/166793 |
| work_keys_str_mv | AT mjananthakrishnan computationalinvestigationonthepredictabilityoflaserengravingdepthonss304 |