A Soft Computing-Based Analysis of Cutting Rate and Recast Layer Thickness for AZ31 Alloy on WEDM Using RSM-MOPSO

Goyal, Kapil Kumar; Sharma, Neeraj; Gupta, Rahul Dev; Singh, Gurpreet; Rani, Deepika; Banga, Harish Kumar; Kumar, Raman; Pimenov, Danil Yurievich; Giasin, Khaled

doi:10.3390/ma15020635

Cited by 35 publications

(10 citation statements)

References 56 publications

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“…An increase in the T on value creates larger dispersive energy, which in turn melts more work material. With the increased value of T on , the dielectric is unable to flush the molten metal, due to which it gets deposited on the machined surface [ 62 ]. This unflushed molten metal then quenches and re-solidifies by forming a thick RLT [ 63 ].…”

Section: Resultsmentioning

confidence: 99%

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy

et al. 2022

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Shape memory alloy (SMA), particularly those having a nickel–titanium combination, can memorize and regain original shape after heating. The superior properties of these alloys, such as better corrosion resistance, inherent shape memory effect, better wear resistance, and adequate superelasticity, as well as biocompatibility, make them a preferable alloy to be used in automotive, aerospace, actuators, robotics, medical, and many other engineering fields. Precise machining of such materials requires inputs of intellectual machining approaches, such as wire electrical discharge machining (WEDM). Machining capabilities of the process can further be enhanced by the addition of Al2O3 nanopowder in the dielectric fluid. Selected input machining process parameters include the following: pulse-on time (Ton), pulse-off time (Toff), and Al2O3 nanopowder concentration. Surface roughness (SR), material removal rate (MRR), and recast layer thickness (RLT) were identified as the response variables. In this study, Taguchi’s three levels L9 approach was used to conduct experimental trials. The analysis of variance (ANOVA) technique was implemented to reaffirm the significance and adequacy of the regression model. Al2O3 nanopowder was found to have the highest contributing effect of 76.13% contribution, Ton was found to be the highest contributing factor for SR and RLT having 91.88% and 88.3% contribution, respectively. Single-objective optimization analysis generated the lowest MRR value of 0.3228 g/min (at Ton of 90 µs, Toff of 5 µs, and powder concentration of 2 g/L), the lowest SR value of 3.13 µm, and the lowest RLT value of 10.24 (both responses at Ton of 30 µs, Toff of 25 µs, and powder concentration of 2 g/L). A specific multi-objective Teaching–Learning-Based Optimization (TLBO) algorithm was implemented to generate optimal points which highlight the non-dominant feasible solutions. The least error between predicted and actual values suggests the effectiveness of both the regression model and the TLBO algorithms. Confirmatory trials have shown an extremely close relation which shows the suitability of both the regression model and the TLBO algorithm for the machining of the nanopowder-mixed WEDM process for Nitinol SMA. A considerable reduction in surface defects owing to the addition of Al2O3 powder was observed in surface morphology analysis.

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Section: Resultsmentioning

confidence: 99%

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy

et al. 2022

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“…The TOPSIS assumes that the chosen alternative will have the shortest Euclidean divergence from the ideal positive solution and the most distant from the ideal negative. The steps usually employed in this technique are in line with [ 49 , 50 , 51 ].

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Section: Statistical Analysis Of Fsw Butt Joint Propertiesmentioning

confidence: 99%

Joining of Dissimilar Al and Mg Metal Alloys by Friction Stir Welding

Sidhu

Kumar

Goel³

et al. 2022

Materials

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In engineering applications, such as automobile, marine, aerospace, and railway, lightweight alloys of aluminum (Al) and magnesium (Mg) ensure design fitness for fuel economy, better efficiency, and overall cost reduction. Friction stir welding (FSW) for joining dissimilar materials has been considered better than the conventional fusion welding process because of metallurgical concerns. In this study, dissimilar joints were made between the AA6061 (A), AZ31B (B), and AZ91D (C) combinations based on the varying advancing side (AS) and retreating side (RS). The dissimilar joints prepared by the FSW process were further characterized by tensile testing, impact testing, corrosion testing, fracture, and statistical and cost analysis. The results revealed a maximum tensile strength of 192.39 MPa in AZ91 and AZ31B, maximum yield strength of 134.38 MPa in a combination of AA6061 and AZ91, maximum hardness of 114 Hv in AA6061 and AZ31B, and lowest corrosion rate of 7.03 mV/A in AA6061 and AZ31B. The results of the properties were supported by photomicrographic fracture analysis by scanning electron microscopy (SEM) observations. Further, the performance of dissimilar joints was statistically analyzed and prioritized for preference by similarity to the ideal solution (TOPSIS) method.

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“…The response surface methodology (RSM) was utilized to develop a model [50,51] for TWR while EDM machined AA6061 + TiB2 MMC material. TWR could be estimated using the mathematical model of peak current A, pulse on time B, and voltage gap C. To construct quadratic TWR models, the test plans were created.…”

Section: Modelling and Anova Of Tool Wear Ratementioning

confidence: 99%

Investigation of Tool Wear Rate during EDM for Aluminium Metal Matrix Composite (5-10% TiB2) Prepared by Squeeze Casting

Channi

Bains

Grewal

et al. 2022

J. Electrochem. Sci. Eng.

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Squeeze casting was used to prepare aluminium alloy-6061/titanium diboride (TiB2) to create a composite with varied TiB2 quantities. The composite's metallographic structure, tensile strength, and hardness have been explored. The tensile strength and hardness of produced metal matrix composites increased when a particle of TiB2 was increased from 5 to 10 vol.%. This study uses electrical discharge machining (EDM) to investigate the output response tool wear rate (TWR). Variables in EDM operation were investigated, such as current, pulse on time, and voltage gap. The experiments were designed using the Box–Behnken strategy. Statistical approaches were used to analyse the experiments. At ideal settings for TiB2 concentrations of 5 and 10 vol.%, TWR was 0.2146 and 0.1749 mm3 min-1 and surface roughness was 2.47 and 3.03 µm, respectively. TiB2 is utilized in automobile disc brakes, an industry where components slide against each other. The aluminium alloy-6061/titanium diboride has many applications as a biomaterial and is a good prospect.

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A Soft Computing-Based Analysis of Cutting Rate and Recast Layer Thickness for AZ31 Alloy on WEDM Using RSM-MOPSO

Cited by 35 publications

References 56 publications

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy

Joining of Dissimilar Al and Mg Metal Alloys by Friction Stir Welding

Investigation of Tool Wear Rate during EDM for Aluminium Metal Matrix Composite (5-10% TiB2) Prepared by Squeeze Casting

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