Optimization of Machining Parameters for Product Quality and Productivity in CNC Machining of Aluminium Alloy

This study focused on optimizing the process of CNC machining to enhance productivity and product quality of surface finish Ra via the process parameters of the cutting speed (vc), feed rate (vf), and cutting depth (doc). Experimentation was performed on workpieces of AA-6061 to investigate the response Ra through variation of the process parameters to analyze their best fit using RSM with 23 full factorial designs L-8 of DOE. The analysis of variance (ANOVA) was then used to find the major contributors among them that were responsible for the Ra. Based on the result, better Ra was obtained at 0.103 μm using the best fit of vf (150 mm/min), vc (220 m/min), and doc (0.1 mm). ANOVA shows vf contributed better Ra followed by vc and doc respectively. In addition, the level of Ra’s was analyzed through contour plots represented by different colours. It continued to analyze the effect of the process parameters via the main effects plot, Pareto chart, and the contour plot in the predictive desirability model, which indicated that the plots and chart confirmed the vf had more influence compared to others. The studyconfirmed that the low-level parameters provided better Ra to be used for polishing.

Authors

Publication Details

Journal
Journal of Mechanical Engineering
Published
2024-09-10
DOI
https://doi.org/10.24191/jmeche.v21i3.27351
Citations
4
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
1.40

Funders

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article

Optimization of Machining Parameters for Product Quality and Productivity in CNC Machining of Aluminium Alloy

Armansyah Armansyah
4 citations
Journal of Mechanical Engineering
Manufacturing Process and Optimization
1.40
article

Optimization of Machining Parameters for Product Quality and Productivity in CNC Machining of Aluminium Alloy

Armansyah Armansyah
article en
4 citations

Abstract

This study focused on optimizing the process of CNC machining to enhance productivity and product quality of surface finish Ra via the process parameters of the cutting speed (vc), feed rate (vf), and cutting depth (doc). Experimentation was performed on workpieces of AA-6061 to investigate the response Ra through variation of the process parameters to analyze their best fit using RSM with 23 full factorial designs L-8 of DOE. The analysis of variance (ANOVA) was then used to find the major contributors among them that were responsible for the Ra. Based on the result, better Ra was obtained at 0.103 μm using the best fit of vf (150 mm/min), vc (220 m/min), and doc (0.1 mm). ANOVA shows vf contributed better Ra followed by vc and doc respectively. In addition, the level of Ra’s was analyzed through contour plots represented by different colours. It continued to analyze the effect of the process parameters via the main effects plot, Pareto chart, and the contour plot in the predictive desirability model, which indicated that the plots and chart confirmed the vf had more influence compared to others. The studyconfirmed that the low-level parameters provided better Ra to be used for polishing.

Journal of Mechanical EngineeringVol. 21(3)
Universiti Teknologi MARA
Openalex Percentile: Top 17%
Manufacturing Process and Optimization
1.40
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