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Multi-Response Optimization of Parameters during Turning of AA7075/ SiC Composite for Minimum Surface Roughness and Maximum Tool Life
- Source :
- Silicon. 13:2845-2856
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- Turning of 7075 Al alloy reinforced with SiC particulates was done on CNC machine by using tungsten carbide tools. Experimental were planned as per face centered central composite design (FCCCD). Response surface methodology (RSM) was utilized for modeling impact of parameters viz. cutting speed, feed, depth of cut and nose radius on responses viz. surface roughness and tool life. Single objective optimization for surface roughness and tool life was carried out. To obtain balance between surface roughness and tool life, a system for concurrent optimization of several objectives founded on an overall desirability function was utilized. Multi response optimization provided cutting speed of 90 m/min, feed of 0.15 mm/rev, depth of cut of 0.20 mm and nose radius of 0.68 mm. turning at these conditions will result in lowest surface roughness and maximum tool life. Which signify a satisfactory whole desirability. Components of AA7075/ SiC composite are being used in automobiles, ships, aero planes due to their high specific strength and wear resistance. Machining of AA7075/10 wt.% SiC (10-20 μm) composites is still a challenge due to poor surface roughness and high tool wear. Novelty of this work is that values of parameters to simultaneously achieve minimum surface roughness and maximum tool life was obtained by multi response optimization of process parameters. Very little research is available on this issue in literature.
- Subjects :
- 010302 applied physics
Materials science
Central composite design
Mechanical engineering
02 engineering and technology
021001 nanoscience & nanotechnology
01 natural sciences
Electronic, Optical and Magnetic Materials
Specific strength
chemistry.chemical_compound
Machining
chemistry
Tungsten carbide
0103 physical sciences
Surface roughness
Numerical control
Response surface methodology
Tool wear
0210 nano-technology
Subjects
Details
- ISSN :
- 18769918 and 1876990X
- Volume :
- 13
- Database :
- OpenAIRE
- Journal :
- Silicon
- Accession number :
- edsair.doi...........1035582bf1f89e0b048f1d5a45cc75aa