Optimization of machining parameters during milling of carbon fibre reinforced plastics
This paper investigates the optimization of cutting parameters on tool life of carbide cutting tools during milling Carbon Fibre Reinforced Plastic (CFRP) of unidirectional fiber orientation of 90°. CFRP is one form of composite material which is highly demand by manufacturing sectors due to its li...
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2022
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my.iium.irep.1031722023-01-18T08:41:44Z http://irep.iium.edu.my/103172/ Optimization of machining parameters during milling of carbon fibre reinforced plastics Ramli, Siti Fatirah Muhamad Khairussaleh, Nor Khairusshima Mokhtar, Suhaily Dahnel, Aishah Najiah A. Raof, Natasha TJ Mechanical engineering and machinery This paper investigates the optimization of cutting parameters on tool life of carbide cutting tools during milling Carbon Fibre Reinforced Plastic (CFRP) of unidirectional fiber orientation of 90°. CFRP is one form of composite material which is highly demand by manufacturing sectors due to its light weight ratio and stronger than aluminium properties. Despite of having high demand in industry, researchers face a lot of problems during machining CFRP during assemble phase. High tool wear and short tool life of cutting tool used during machining, lead to high production cost are among the factors which concern the machinist the most. This research is carried out by using spindle speed of 1000 rpm to 8700 rpm, feed rate of 500 mm/min to 1000 mm/min and depth of cut of 1 mm to 1.5 mm which will be acted as the input variable. The output response is in form of tool wear and tool life of carbide cutting tool. In this study, CNC Mazak Milling Machine with maximum spindle speed of 12000 rpm is used to mill CFRP. Box Behnken Design under Response Surface Methodology is used as Design of Experiment to generate 15 runs. The optimization of cutting parameters for 90° is analyzed using Analysis of Variance (ANOVA). It was found that, higher spindle speed, lower feed rate and lower depth of cut lead to lowest tool wear and highest tool life. ANOVA analysis recorded that feed rate is the most significant factor that influence tool life. Springer Singapore 2022 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/103172/2/103172_Optimization%20of%20Machining%20parameters%20during%20milling%20of%20Carbon%20Fibre%20Reinforced%20Plastics%20%28CFRP%29-p164-171.pdf application/pdf en http://irep.iium.edu.my/103172/3/103172_Optimization%20of%20machining%20parameters%20during%20milling%20of%20carbon%20fibre%20reinforced%20plastics_SCOPUS.pdf Ramli, Siti Fatirah and Muhamad Khairussaleh, Nor Khairusshima and Mokhtar, Suhaily and Dahnel, Aishah Najiah and A. Raof, Natasha (2022) Optimization of machining parameters during milling of carbon fibre reinforced plastics. In: 3rd Malaysian International Tribology Conference, MITC 2020, 28 - 30 September 2020, Langkawi, Malaysia. https://link.springer.com/chapter/10.1007/978-981-16-9949-8_30 |
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TJ Mechanical engineering and machinery Ramli, Siti Fatirah Muhamad Khairussaleh, Nor Khairusshima Mokhtar, Suhaily Dahnel, Aishah Najiah A. Raof, Natasha Optimization of machining parameters during milling of carbon fibre reinforced plastics |
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This paper investigates the optimization of cutting parameters on tool
life of carbide cutting tools during milling Carbon Fibre Reinforced Plastic (CFRP) of unidirectional fiber orientation of 90°. CFRP is one form of composite material which is highly demand by manufacturing sectors due to its light weight ratio and stronger than aluminium properties. Despite of having high demand in industry, researchers face a lot of problems during machining CFRP during assemble phase. High tool wear and short tool life of cutting tool used during machining, lead to high production cost are among the factors which concern the machinist the most. This research is carried out by using spindle speed of 1000 rpm to 8700 rpm, feed rate of 500 mm/min to 1000 mm/min and depth of cut of 1 mm to 1.5 mm which
will be acted as the input variable. The output response is in form of tool wear and tool life of carbide cutting tool. In this study, CNC Mazak Milling Machine with maximum spindle speed of 12000 rpm is used to mill CFRP. Box Behnken Design under Response Surface Methodology is used as Design of Experiment to generate 15 runs. The optimization of cutting parameters for 90° is analyzed using Analysis of Variance (ANOVA). It was found that, higher spindle speed, lower feed rate and lower depth of cut lead to lowest tool wear and highest tool life. ANOVA analysis recorded that feed rate is the most significant factor that influence tool life. |
format |
Conference or Workshop Item |
author |
Ramli, Siti Fatirah Muhamad Khairussaleh, Nor Khairusshima Mokhtar, Suhaily Dahnel, Aishah Najiah A. Raof, Natasha |
author_facet |
Ramli, Siti Fatirah Muhamad Khairussaleh, Nor Khairusshima Mokhtar, Suhaily Dahnel, Aishah Najiah A. Raof, Natasha |
author_sort |
Ramli, Siti Fatirah |
title |
Optimization of machining parameters during milling of carbon fibre reinforced plastics |
title_short |
Optimization of machining parameters during milling of carbon fibre reinforced plastics |
title_full |
Optimization of machining parameters during milling of carbon fibre reinforced plastics |
title_fullStr |
Optimization of machining parameters during milling of carbon fibre reinforced plastics |
title_full_unstemmed |
Optimization of machining parameters during milling of carbon fibre reinforced plastics |
title_sort |
optimization of machining parameters during milling of carbon fibre reinforced plastics |
publisher |
Springer Singapore |
publishDate |
2022 |
url |
http://irep.iium.edu.my/103172/2/103172_Optimization%20of%20Machining%20parameters%20during%20milling%20of%20Carbon%20Fibre%20Reinforced%20Plastics%20%28CFRP%29-p164-171.pdf http://irep.iium.edu.my/103172/3/103172_Optimization%20of%20machining%20parameters%20during%20milling%20of%20carbon%20fibre%20reinforced%20plastics_SCOPUS.pdf http://irep.iium.edu.my/103172/ https://link.springer.com/chapter/10.1007/978-981-16-9949-8_30 |
_version_ |
1755872137205252096 |