Performance analysis of ELM-PSO architectures for modelling surface roughness and power consumption in CNC turning operation

Tiagrajah V. Janahiraman, Nooraziah Ahmad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The turning operation in the Computer Numerical Control (CNC) needs optimal machining parameters to achieve higher machining efficiency. The selection of machining parameters is very important to find the best performances in machining process. In this study, two different architectures of particle swarm optimization based extreme learning machine were analyzed for modelling inputs parameters: feed rate, cutting speed and depth of cut to output parameters: surface roughness and power consumption. The data were collected from 15 experiments using carbon steel AISI 1045 which were separated into training and testing dataset. Our experimental results shows that Architecture II is the most outstanding model with mean absolute percentage error (MAPE) of 0.0469 for predicting the training data and 0.204 for predicting the testing data.

Original languageEnglish
Title of host publicationConference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN
Subtitle of host publicationCultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages303-307
Number of pages5
ISBN (Electronic)9781479954230
DOIs
Publication statusPublished - 23 Mar 2015
Event6th International Conference on Information Technology and Multimedia, ICIMU 2014 - Putrajaya, Malaysia
Duration: 18 Nov 201420 Nov 2014

Other

Other6th International Conference on Information Technology and Multimedia, ICIMU 2014
CountryMalaysia
CityPutrajaya
Period18/11/1420/11/14

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Software

Cite this

V. Janahiraman, T., & Ahmad, N. (2015). Performance analysis of ELM-PSO architectures for modelling surface roughness and power consumption in CNC turning operation. In Conference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN: Cultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014 (pp. 303-307). [7066649] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIMU.2014.7066649