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A comparative study on multi-objective optimization of drilling of hybrid aluminium metal matrix composite
To fulfil the present-day technological requirements of light weight materials with higher strength, hardness, stiffness, wear and corrosion resistance properties, aluminium metal matrix composites (Al-MMCs) now appear as viable alternative materials in many of the manufacturing industries. Hybrid Al-MMCs with heterogeneous reinforcement elements are now gradually substituting the single-reinforced composites due to their more improved physical and wear resistance properties. In this paper, hybrid Al-MMCs are developed using silicon carbide, fly ash and bagasse ash as the reinforcements, and an attempt is put forward to optimize its drilling operation treating spindle speed, feed rate and drill diameter as the input parameters, and material removal rate (MRR) and average surface roughness (Ra) as the responses. To overcome the drawbacks of standalone Taguchi methodology, this paper presents the applications of four simple multi-objective optimization techniques, i.e. grey relational analysis (GRA), multiple response signal-to-noise (MRSN) ratio, weighted signal-to-noise (WSN) ratio and technique for order of preference by similarity to ideal solution (TOPSIS) for identification of the optimal parametric combinations of the said drilling operation. It is observed that most of the adopted approaches recommend higher spindle speed (255 rpm), feed rate (82 mm/rev) and drill diameter (12 mm) as the optimal settings of the drilling parameters for achieving compromised values of both the responses when equal importance is assigned to them. Effects of varying weights allotted to the responses on the derived optimal parametric combinations are also studied along with confirmatory experiments.
A comparative study on multi-objective optimization of drilling of hybrid aluminium metal matrix composite
To fulfil the present-day technological requirements of light weight materials with higher strength, hardness, stiffness, wear and corrosion resistance properties, aluminium metal matrix composites (Al-MMCs) now appear as viable alternative materials in many of the manufacturing industries. Hybrid Al-MMCs with heterogeneous reinforcement elements are now gradually substituting the single-reinforced composites due to their more improved physical and wear resistance properties. In this paper, hybrid Al-MMCs are developed using silicon carbide, fly ash and bagasse ash as the reinforcements, and an attempt is put forward to optimize its drilling operation treating spindle speed, feed rate and drill diameter as the input parameters, and material removal rate (MRR) and average surface roughness (Ra) as the responses. To overcome the drawbacks of standalone Taguchi methodology, this paper presents the applications of four simple multi-objective optimization techniques, i.e. grey relational analysis (GRA), multiple response signal-to-noise (MRSN) ratio, weighted signal-to-noise (WSN) ratio and technique for order of preference by similarity to ideal solution (TOPSIS) for identification of the optimal parametric combinations of the said drilling operation. It is observed that most of the adopted approaches recommend higher spindle speed (255 rpm), feed rate (82 mm/rev) and drill diameter (12 mm) as the optimal settings of the drilling parameters for achieving compromised values of both the responses when equal importance is assigned to them. Effects of varying weights allotted to the responses on the derived optimal parametric combinations are also studied along with confirmatory experiments.
A comparative study on multi-objective optimization of drilling of hybrid aluminium metal matrix composite
Int J Interact Des Manuf
Sapkota, Gaurav (author) / Ghadai, Ranjan Kumar (author) / Das, Soham (author) / Das, Partha Protim (author) / Chakraborty, Shankar (author)
2023-12-01
11 pages
Article (Journal)
Electronic Resource
English
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