Evaluation of power consumption and MRR in WEDM of Ti–6Al–4V alloy and its simultaneous optimization for sustainable production

Devarajaiah, Devarasiddappa; Chandrasekaran, M.

doi:10.1007/s40430-018-1318-y

Cited by 61 publications

(26 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Titanium and inconel alloys are found suitable for service environment having extreme temperature and pressure due to their excellent corrosion and oxidation-resistant property, high specific strength and high strength-to-weight ratio [7,8]. Conventional machining of Ti6Al4V alloy is found difficult due to poor thermal conductivity and high chemical reactivity as a result of which chips may get welded to tool face resulting in built-up edge and poor surface finish [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation and parametric optimization for minimizing surface roughness during WEDM of Ti6Al4V alloy using modified TLBO algorithm

Devarasiddappa

Chandrasekaran

Arunachalam

2020

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

Wire-cut electrical discharge machining (WEDM) is a widely used non-contact machining process used to cut difficultto-machine materials such as titanium, nickel and inconel alloys. WEDM is famous for producing components in diverse engineering applications, including automotive, marine, space, medical sectors with the highest accuracy and consistency. In this paper, experimental investigation on surface roughness (SR) of Ti6Al4V alloy employing WEDM process is presented using Taguchi L 16 experimental plan by varying four process variables, viz., pulse on time (T on), pulse off time (T off), current (I) and wire speed (WS) at four different levels. The novelty of the present work is minimization of surface roughness (SR) in WEDM of Ti6Al4V alloy employing reusable wire technology during experimental work and optimizes the problem with modified teaching-learning-based optimization (M-TLBO) algorithm. A novel technique for fitness curve fitting is also illustrated to obtain global optima for minimization of SR. Results showed that SR decreased by 2.65% at optimal parameter setting T on = 13 µs, T off = 10 µs, I = 1 A and WS = 850 rpm and global optima is obtained as 3.749 µm. Pulse on time (44.06%) and current (28.69%) are recognized as the most dominant process variables affecting SR followed by pulse off time (15.80%) and wire speed (7.47%). Surface morphology study of machined Ti alloy using SEM images showed that smoother surface is obtained at lower settings of pulse on time and current. The proposed M-TLBO algorithm is found to be highly accurate and consistent during several runs conducted with mean fitness value and standard deviation recorded as 3.751 µm and 0.006417, respectively.

show abstract

Section: Introductionmentioning

confidence: 99%

Experimental investigation and parametric optimization for minimizing surface roughness during WEDM of Ti6Al4V alloy using modified TLBO algorithm

Devarasiddappa

Chandrasekaran

Arunachalam

2020

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…Desirability function analysis is a statistical technique used for multi-objective optimization where the objective is to ensure that all the quality characteristics are between 0 and 1 [28]. The individual desirability is, in turn, converted into composite desirability which is calculated from the combination of each response variable processed through a geometric mean of each pair of the response variables [29].…”

Section: Multi-objective Optimizationmentioning

confidence: 99%

Machinability Studies and Optimization of AA 6082/Fly Ash/Carbonized Eggshell Matrix Composite

Ononiwu¹,

Ozoegwu²,

Madushele³

et al. 2021

RCMA

View full text Add to dashboard Cite

Machinability studies of aluminium matrix composites (AMCs) is a necessary investigation required to understand their behaviour during machining to produce components effectively and efficiently. This established need has led to the investigation into the machinability of AA 6082 reinforced with 2.5 wt.% fly ash and 2.5 wt.% carbonized eggshell fabricated via stir casting. The studied machinability indices were material removal rate (MRR), cutting temperature, built-up edges (BUE) formation and chip morphology while the selected inputs were cutting speed (100 mm/min, 200 mm/min, 300 mm/min), feed (0.1 mm/rev, 0.2 mm/rev, 0.3 mm/rev) and depth of cut (0.5 mm, 1 mm, 1.5 mm). For the experimental design, the L9 orthogonal array was preferred to create 9 experimental runs. The analysis of the built-up edges showed that it increased at lower cutting speeds and increased feed and depth of cut. The examination of the produced chips after each experimental run showed the presence of c-shaped, helically shaped and ribbon-shaped chips. The analysis of variance (ANOVA) for both MRR and cutting temperature indicated that the depth of cut was the most influential factor on both responses. Multi-objective optimization using desirability function analysis showed that the optimum combination of parameters was 300 mm/min, 0.2 mm/rev and 1.0 mm for the cutting speed, feed and depth of cut respectively. The ANOVA of the composite desirability indicated that the cutting speed was the most contributing factor.

show abstract

“…According to (Ghodsiyeh et al, 2012), the significant parameter is peak current which influences MRR. (Devarajaiah and Muthumari (2018) investigated the effect of interactions for different combinations of pulse-on-time, pulse-off-time, current and wire speed on the material removal rate. It was noted that the increase of wire speed and current increases the MRR but the pulse-off time does not influence it significantly.…”

Section: Materials Removal Rate (Mmr)mentioning

confidence: 99%

Methods and variables in Electrical discharge machining of titanium alloy – A review

Pramanik

Basak

Littlefair

et al. 2020

Heliyon

View full text Add to dashboard Cite

Evaluation of power consumption and MRR in WEDM of Ti–6Al–4V alloy and its simultaneous optimization for sustainable production

Cited by 61 publications

References 21 publications

Experimental investigation and parametric optimization for minimizing surface roughness during WEDM of Ti6Al4V alloy using modified TLBO algorithm

Experimental investigation and parametric optimization for minimizing surface roughness during WEDM of Ti6Al4V alloy using modified TLBO algorithm

Machinability Studies and Optimization of AA 6082/Fly Ash/Carbonized Eggshell Matrix Composite

Methods and variables in Electrical discharge machining of titanium alloy – A review

Contact Info

Product

Resources

About