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1860799642044727296
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| building |
INTELEK Repository
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Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2016-08-11 10:29:13
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| eventvenue |
Seoul, South Korea
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| format |
Restricted Document
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| id |
6810
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UniSZA
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1116-01-FH03-FSTK-16-06329.jpg
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| person |
norman
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6810
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| spelling |
6810 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6810 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper image/jpeg inches 96 96 norman 1423 770 2016-08-11 10:29:13 1423x770 62 62 1116-01-FH03-FSTK-16-06329.jpg UniSZA Private Access 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 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. International Conference on Materials Science and Nanotechnology, ICMSNT 2016 Seoul, South Korea
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| spellingShingle |
Down milling cutting parameters optimization utilizing the two level full factorial design approach
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| summary |
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.
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| title |
Down milling cutting parameters optimization utilizing the two level full factorial design approach
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| title_full |
Down milling cutting parameters optimization utilizing the two level full factorial design approach
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| title_fullStr |
Down milling cutting parameters optimization utilizing the two level full factorial design approach
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| title_full_unstemmed |
Down milling cutting parameters optimization utilizing the two level full factorial design approach
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| title_short |
Down milling cutting parameters optimization utilizing the two level full factorial design approach
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| title_sort |
down milling cutting parameters optimization utilizing the two level full factorial design approach
|