A study on regression model using response surface methodology

Ahmad Nooraziah, Tiagrajah V. Janahiraman

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

3 Citations (Scopus)

Abstract

Response Surface Methodology (RSM) mostly employs statistical regression method as it is practical, economical and relatively easy to use. The first and second order polynomial equation was developed using RSM. This polynomial model usually refers as a regression model. In this research, the objective is to find the best response surface method to model three factors and three levels parameters in machining. From the study, the Box-Behnken Design can develop a good regression model rather than Central Composite Design or Full Factorial Design. While, the second order regression model has proved to be more effective in predicting the performance of the given data set.

Original languageEnglish
Title of host publicationElectronics, Mechatronics and Automation III
EditorsMaode Ma, Amanda F. Wu, Z. Afrasiabi, Z. Afrasiabi, Maode Ma, Amanda F. Wu
PublisherTrans Tech Publications Ltd
Pages235-239
Number of pages5
ISBN (Electronic)9783038352976, 9783038352976
DOIs
Publication statusPublished - 01 Jan 2014
Event3rd International Conference on Electronics, Mechatronics and Automation, ICEMA 2014 - Dubai, United Arab Emirates
Duration: 22 Aug 201423 Aug 2014

Publication series

NameApplied Mechanics and Materials
Volume666
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Other

Other3rd International Conference on Electronics, Mechatronics and Automation, ICEMA 2014
CountryUnited Arab Emirates
CityDubai
Period22/08/1423/08/14

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All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Nooraziah, A., & V. Janahiraman, T. (2014). A study on regression model using response surface methodology. In M. Ma, A. F. Wu, Z. Afrasiabi, Z. Afrasiabi, M. Ma, & A. F. Wu (Eds.), Electronics, Mechatronics and Automation III (pp. 235-239). (Applied Mechanics and Materials; Vol. 666). Trans Tech Publications Ltd. https://doi.org/10.4028/www.scientific.net/AMM.666.235