Down milling cutting parameters optimization utilizing the two level full factorial design approach

The direction of feeding the work piece and cutter rotation determines the type of machining mode either it is up milling or down milling. Each of this machining mode affects the quality of machined surface produced. This paper described the experimental design of down milling operation on a stack o...

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Main Authors: Ismail, J., Mohamad, M., Mohamed, S.B., Mohd, A., Mohamad, W.N.F., Ibrahim, Z., Musanih, M.R.
Format: Conference or Workshop Item
Language:English
Published: 2016
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Online Access:http://eprints.unisza.edu.my/1116/1/FH03-FSTK-16-06329.jpg
http://eprints.unisza.edu.my/1116/
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spelling my-unisza-ir.11162020-11-09T07:15:14Z http://eprints.unisza.edu.my/1116/ Down milling cutting parameters optimization utilizing the two level full factorial design approach Ismail, J. Mohamad, M. Mohamed, S.B. Mohd, A. Mohamad, W.N.F. Ibrahim, Z. Musanih, M.R. Q Science (General) TJ Mechanical engineering and machinery The direction of feeding the work piece and cutter rotation determines the type of machining mode either it is up milling or down milling. Each of this machining mode affects the quality of machined surface produced. This paper described the experimental design of down milling operation on a stack of multidirectional CFRP/Al2024. Three cutting parameters were considered namely, spindle speed (N), feed rate (fr) and depth of cut (dc). Two level full factorial design was utilized to plan systematic experimental methodology. The analysis of variance (ANOVA) was used to analyse the influence and the interaction factors associated to surface quality. The results show that the depth of cut is the most significant factor for Al2024, and for CFRP the spindle speed and feed rate are significant. Surface roughness of CFRP is found to be at 0.594 μm at the setting of N = 11750 rpm, fr = 750 mm/min and dc = 0.255 mm. Meanwhile for Al2024, the surface roughness is found to be at 0.32 μm. The validation test showed average deviation of predicted to actual value surface roughness is 3.11% for CFRP and 3.43% for Al2024. 2016 Conference or Workshop Item NonPeerReviewed image en http://eprints.unisza.edu.my/1116/1/FH03-FSTK-16-06329.jpg Ismail, J. and Mohamad, M. and Mohamed, S.B. and Mohd, A. and Mohamad, W.N.F. and Ibrahim, Z. and Musanih, M.R. (2016) Down milling cutting parameters optimization utilizing the two level full factorial design approach. In: International Conference on Materials Science and Nanotechnology, ICMSNT 2016, 12-14 May 2016, Seoul, South Korea.
institution Universiti Sultan Zainal Abidin
building UNISZA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sultan Zainal Abidin
content_source UNISZA Institutional Repository
url_provider https://eprints.unisza.edu.my/
language English
topic Q Science (General)
TJ Mechanical engineering and machinery
spellingShingle Q Science (General)
TJ Mechanical engineering and machinery
Ismail, J.
Mohamad, M.
Mohamed, S.B.
Mohd, A.
Mohamad, W.N.F.
Ibrahim, Z.
Musanih, M.R.
Down milling cutting parameters optimization utilizing the two level full factorial design approach
description The direction of feeding the work piece and cutter rotation determines the type of machining mode either it is up milling or down milling. Each of this machining mode affects the quality of machined surface produced. This paper described the experimental design of down milling operation on a stack of multidirectional CFRP/Al2024. Three cutting parameters were considered namely, spindle speed (N), feed rate (fr) and depth of cut (dc). Two level full factorial design was utilized to plan systematic experimental methodology. The analysis of variance (ANOVA) was used to analyse the influence and the interaction factors associated to surface quality. The results show that the depth of cut is the most significant factor for Al2024, and for CFRP the spindle speed and feed rate are significant. Surface roughness of CFRP is found to be at 0.594 μm at the setting of N = 11750 rpm, fr = 750 mm/min and dc = 0.255 mm. Meanwhile for Al2024, the surface roughness is found to be at 0.32 μm. The validation test showed average deviation of predicted to actual value surface roughness is 3.11% for CFRP and 3.43% for Al2024.
format Conference or Workshop Item
author Ismail, J.
Mohamad, M.
Mohamed, S.B.
Mohd, A.
Mohamad, W.N.F.
Ibrahim, Z.
Musanih, M.R.
author_facet Ismail, J.
Mohamad, M.
Mohamed, S.B.
Mohd, A.
Mohamad, W.N.F.
Ibrahim, Z.
Musanih, M.R.
author_sort Ismail, J.
title Down milling cutting parameters optimization utilizing the two level full factorial design approach
title_short Down milling cutting parameters optimization utilizing the two level full factorial design approach
title_full Down milling cutting parameters optimization utilizing the two level full factorial design approach
title_fullStr Down milling cutting parameters optimization utilizing the two level full factorial design approach
title_full_unstemmed Down milling cutting parameters optimization utilizing the two level full factorial design approach
title_sort down milling cutting parameters optimization utilizing the two level full factorial design approach
publishDate 2016
url http://eprints.unisza.edu.my/1116/1/FH03-FSTK-16-06329.jpg
http://eprints.unisza.edu.my/1116/
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score 13.211869