NDLI: Application of Regression and ANN Techniques for Modeling of the Surface Roughness in End Milling Machining Process

Content Provider	IEEE Xplore Digital Library
Author	Zain, A.M. Haron, H. Sharif, S.
Copyright Year	2009
Abstract	Development of mathematical models to predict the values of performance measure is important in order to have a better understanding of the machining process. Surface roughness is one of the most common performance measures in machining process and an effective parameter in representing the quality of machined surface. The minimization of the machining performance measures such as surface roughness must be formulated in the standard mathematical model. To predict the minimum values of surface roughness, the process of modeling is taken in this study. The developed model deals with real experimental data of the surface roughness performance measure in the end milling machining process. Two modeling approaches, Regression and Artificial Neural Network techniques are applied to predict the minimum value of surface roughness. The result of the modeling process indicated that Artificial Neural Network technique gave a better prediction of surface roughness compared to the result of Regression technique.
Starting Page	188
Ending Page	193
File Size	334757
Page Count	6
File Format	PDF
ISBN	9781424441549
DOI	10.1109/AMS.2009.76
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-25
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	ANN modeling surface Artificial neural networks Machining Predictive models Regression Surface roughness Rough surfaces Metalworking machines Equations Analytical models machining Milling Mathematical model
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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