Optimization of Machining Parameters in Milling Process for High Speed Machining using Taguchi Method for Best Surface Roughness

High-speed machining (HSM) in milling has known is one of the technologies in rapid tooling and manufacturing applications. The cutting mechanism, spindle speed and feed rate are not the same for HSM compared to traditional machining. Coated carbide cutting tools are widely used in high speed and cu...

Full description

Saved in:
Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2020-05, Vol.864 (1), p.12110
Main Authors: Mohd Fadly Bin Syed Hassan, Syed, Binti Shafei, Suzana, Rashid, Rokayah Binti A
Format: Article
Language:English
Subjects:
Carbide cutting tools
Carbide tools
Cutting speed
Cutting tools
Feed rate
Glass fiber reinforced plastics
High speed machining
Machine shops
Milling (machining)
Optimization
Orthogonal arrays
Parameter identification
Polymers
Process parameters
Rapid prototyping
Rapid tooling
Signal processing
Spindles
Surface roughness
Taguchi methods
Variance analysis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:High-speed machining (HSM) in milling has known is one of the technologies in rapid tooling and manufacturing applications. The cutting mechanism, spindle speed and feed rate are not the same for HSM compared to traditional machining. Coated carbide cutting tools are widely used in high speed and cutting temperature situations. It is more efficient and providing a lower surface roughness in HSM. Throughout these days, the demand of standard surface roughness is very high aligned to achieve quality in product. This paper shows an optimization method of machining parameters in milling process for high speed machining of glass fibre reinforce polymer (GFRP) using coated carbide cutting tool to achieve better surface roughness. Taguchi Method are used and it is the best method to optimize a parameter, where a response variable can be determined. Standard orthogonal array of L9 (32) was applied in this research using signal to noise (S/N) ratio response analysis from optimization process results and analysis of variance (ANOVA) to identify the most significant parameters affecting surface roughness. The common machining parameters are significantly affecting surface roughness are spindle speed and feed rate. Then, conformation tests were executed to analyse the improvement of the optimization. As result, the feed rate parameter are significant for affecting the surface roughness and 90.3 % improvement on the surface roughness performance of milling process for glass fibre reinforce polymer (GFRP).
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/864/1/012110