Using AI To Predict 3D Printing Attributes
Panth Korat
12th grade, Delhi Public School Surat, Dumas Surat, India
54-63
Vol: 14, Issue: 4, 2024
Receiving Date:
2024-09-28
Acceptance Date:
2024-11-06
Publication Date:
2024-11-14
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http://doi.org/10.37648/ijrst.v14i04.006
Abstract
Today, machine learning is being used in various fields, from quality control to medical diagnosis. Working in the same line, our paper focuses on a particular application of machine learning. In this paper, we have implemented machine learning algorithms to develop prediction for roughness and tension strength of 3D Printed object based on the 3D Printing Dataset. This paper first introduces the learning algorithms used. Then, it discusses multiple regression models and their parameter values. Based on the prediction results, the paper first compares the performance of ML (machine learning) models through quantitative metrics, evaluates the importance of attributes influencing the roughness and tension strength labels through SHAP values, replika klockor sverige and finally draws a conclusion on the labels using practical reasoning
Keywords:
3D Printer; Roughness and Tension Strength Prediction; Machine Learning; SHAP Values
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