Characteristics of machining data and machine learning models - A case study

Natarajan, Elango and Fiorna, Vxynette and Al-Talib, Ammar Abdulaziz Majeed and Elango, Sangeetha and Gnanamuthu, Ezra Morris Abraham and Sarah Atifah, Saruchi (2023) Characteristics of machining data and machine learning models - A case study. In: IET Conference Proceedings. 2023 International Conference on Green Energy, Computing and Intelligent Technology, GEn-CITy 2023 , 10 - 12 July 2023 , Hybrid, Iskandar Puteri. pp. 117-122., 2023 (11). ISSN 2732-4494 (Published)

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Abstract

Advancement of technologies in computing such as internet of things, cloud computing, and artificial intelligence drive manufacturing industries to adopt and implement automation in production. One of the key technologies or preferable methods to increase the productivity is implementing prediction models or machine learning (ML) algorithms in production. This article is aimed to show a comprehensive review on AI implementation in machining of materials, and to present methodology in prediction model development. The characteristic of experimental data and the key attributes in the model development are presented and discussed with a case study.

Item Type:	Conference or Workshop Item (Poster)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Engineering education; Machine learning
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TS Manufactures
Faculty/Division:	Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	30 Aug 2024 00:17
Last Modified:	30 Aug 2024 00:17
URI:	http://umpir.ump.edu.my/id/eprint/41926
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