Optimization of Multiple Roughness Characteristics for Turning of AISI 1040 Steel under Different Cutting Conditions

Haque, Tanveer; Kumar, Shubham; Upadhaya, Devjyoti; Barman, Manik; Mukhopadhyay, Arkadeb

doi:10.56431/p-5m9237

Cited by 1 publication

(1 citation statement)

References 23 publications

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“…The optimization of parameters is a vital step in improving the performance and efficiency of many operations. Taguchi-Grey relational analysis is a technique that evaluates multiple variables simultaneously in engineering & production [38][39][40]. The analysis begins with the selection of control factors and their corresponding levels.…”

Section: Multi Response Optimizationmentioning

confidence: 99%

Experimental investigation and parametric optimization of rotary ultrasonic machining of different bio-ceramic materials

Vishnoi,

Mamatha,

Singh

et al. 2024

Phys. Scr.

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Rotary ultrasonic machining (RUM) is a highly promising technique for machining bio-ceramic materials due to its ability to achieve high precision and superior surface quality. This research focuses on an experimental investigation and parametric optimization of RUM for different bio-ceramic materials, intending to optimize multiple machining responses simultaneously. The experimental setup involves utilizing a 3-axis CNC ultrasonic machine to machine three different workpieces with slot cutting. Various machining parameters, such as tool feed rate and tool rotating speed, are studied to determine their impacts. An orthogonal array design based on Taguchi optimization is used to execute the experiments effectively. Material removal rate (MRR) and surface roughness (SR) are monitored and statistically analyzed as a consequence of the responses. ANOVA demonstrates that the tool feed rate has a considerable impact on the output reactions, with material type and tool rotational speed also playing a role. For multiple response optimizations, the Taguchi-Grey method is used to achieve the best trade-off between MRR and SR. The results demonstrate that material type has the most substantial impact on surface roughness, followed by feed rate and spindle speed. In contrast, feed rate has the most significant effect on the material removal rate, followed by the material type and spindle speed. The optimal parameter settings for achieving the desired output parameter are determined. The confirmation experiments validate the effectiveness of the optimized parameters. The feed rate of 5 mm/min, and spindle speed of 2500 rpm were discovered to be the optimal condition for achieving maximum MRR and minimum Ra. The MRR and surface roughness values were measured as 1.7266 mm3/min and 1.5611 microns respectively.

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Section: Multi Response Optimizationmentioning

confidence: 99%