An experimental study on material removal rate and surface roughness of Cu-Al-Mn ternary shape memory alloys using CNC end milling

Abstract This study investigates the impact of Computer Numerical Control (CNC) milling parameters on Cu-Al-Mn SMAs (Shape memory alloys) to evaluate the effects on Surface Roughness (SR) and Material Removal Rate (MRR). The primary variables examined comprise of cutting speed, feed rate, and depth of cut. Results indicate that the Shape Memory Effect (SME) is higher in Copper Aluminium Manganese (CAM 3) compared to CAM 1 and CAM 2, with SME improving from 3.5% to 5.5% as Manganese (Mn) content increases, reflecting an increase in dislocations within the metal’s crystal structure. Surface roughness increases with higher feed rates and depths of cut but decreases with increased cutting speed. MRR shows a positive correlation with feed rate, depth of cut, and cutting speed, though it decreases with higher Mn content. Notably, CAM 3 exhibits lower MRR compared to CAM 1 and CAM 2. Scanning Electron Microscopy (SEM) reveals that at lower feed rates (0.10 mm rev −1 ), the surface is smooth and free of ridges or feed marks, while at higher feed rates (0.18 mm rev −1 ), noticeable surface imperfections and plastic deformation occur. The addition of Mn improves surface smoothness and machinability, it also affects MRR. Further suggesting that Mn content and milling parameters significantly influence both the mechanical properties and machinability of Cu-Al-Mn SMAs respectively.

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Publication Details

Journal
Materials Research Express
Published
2024-09-01
DOI
https://doi.org/10.1088/2053-1591/ad76fc
Citations
5
Primary Topic
Shape Memory Alloy Transformations
Type
article
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article

An experimental study on material removal rate and surface roughness of Cu-Al-Mn ternary shape memory alloys using CNC end milling

Subramanya R B Prabhu, Saravana Bavan, Prakash Kumar, C. Durga Prasad et al.
5 citations
Materials Research Express
Shape Memory Alloy Transformations
0.59
article

An experimental study on material removal rate and surface roughness of Cu-Al-Mn ternary shape memory alloys using CNC end milling

Subramanya R B Prabhu, Saravana Bavan, Prakash Kumar, C. Durga Prasad, N. Praveen, M. Pradeep Kumar, H Hrishikesh, S. Vinoth Kumar, Siddesh Kumar N G
article en
5 citations

Abstract

Abstract This study investigates the impact of Computer Numerical Control (CNC) milling parameters on Cu-Al-Mn SMAs (Shape memory alloys) to evaluate the effects on Surface Roughness (SR) and Material Removal Rate (MRR). The primary variables examined comprise of cutting speed, feed rate, and depth of cut. Results indicate that the Shape Memory Effect (SME) is higher in Copper Aluminium Manganese (CAM 3) compared to CAM 1 and CAM 2, with SME improving from 3.5% to 5.5% as Manganese (Mn) content increases, reflecting an increase in dislocations within the metal’s crystal structure. Surface roughness increases with higher feed rates and depths of cut but decreases with increased cutting speed. MRR shows a positive correlation with feed rate, depth of cut, and cutting speed, though it decreases with higher Mn content. Notably, CAM 3 exhibits lower MRR compared to CAM 1 and CAM 2. Scanning Electron Microscopy (SEM) reveals that at lower feed rates (0.10 mm rev −1 ), the surface is smooth and free of ridges or feed marks, while at higher feed rates (0.18 mm rev −1 ), noticeable surface imperfections and plastic deformation occur. The addition of Mn improves surface smoothness and machinability, it also affects MRR. Further suggesting that Mn content and milling parameters significantly influence both the mechanical properties and machinability of Cu-Al-Mn SMAs respectively.

Materials Research ExpressVol. 11(9)
National Institute of Technology Karnataka (IN), Magadh University (IN), Manipal Academy of Higher Education (IN), Sardar Vallabhbhai National Institute of Technology Surat (IN), Dayananda Sagar University (IN), Tumkur University (IN), Dr. Hari Singh Gour University (IN)
Openalex Percentile: Top 34%
Shape Memory Alloy Transformations
0.59
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