Parametric Optimization of WEDM on α-β Titanium Alloy using Desirability Approach

Srinivasarao, G.; D, None Suneel

doi:10.1016/j.matpr.2017.11.476

Cited by 12 publications

(5 citation statements)

References 15 publications

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“…The perturbation plot also reveals the same results as ANOVA for Sr As the T ON increases, the SR increases, Due to more discharge energy, more area is affected; hence the SR deteriorates. At the same time, Toff and SV have little effect on SR [33]. The SR decreases as the Toff increases due to the longer flushing time.…”

Section: Doe Analysis Of Srmentioning

confidence: 92%

“…Increasing the SV increases the MRR, and further increasing the SV decreases the MRR. So, machining can be done very quickly (no wire breaks) at some optimum value of SV and increases the MRR due to good discharge energy [33].…”

Section: Doe Analysis Of Mrrmentioning

confidence: 99%

“…At the same time, MRR and SR were chosen as responses. They found that the optimized MRR 2.78066 mm 3 min −1 and SR 1.292 micro-meters achieve on the TON 108 μS, Toff 51 μS, Ip 12 A, Vs 51 V, and WFR at 15 m min −1 [33].…”

Section: Introductionmentioning

confidence: 98%

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Comparison of priori and posteriori approach of multi-objective optimization for WEDM on Ti6Al4V alloy

Jain

Parashar

2022

Mater. Res. Express

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Titanium alloys are known to have some excellent properties, such as good biocompatibility, good fatigue resistance and high strength to weight ratio. Due to these properties, Ti6Al4V alloy is widely used in the biomedical field, aerospace and automobile industries. In this article, pulse on-time (TON), pulse off time (TOFF), and servo voltage (SV) were selected as process parameters for wire electric discharge machining (WEDM) on Ti6Al4V alloy. The material removal rate (MRR) and surface roughness (SR) were determined as responses. MRR and SR have been equated by a central composite design (CCD: a response surface method technique). Then multi-objective Artificial Bee Colony optimization (MO-ABC) with Gray relational analysis (GRA) was selected as a priori approach for multi-objective optimization. Also, a multi-objective grasshopper optimization algorithm (MO-GOA) has been chosen as a posterior approach for optimization. These two algorithms have been tested on various iterations and populations. Based on the elapsed time, it has been found that the priori approach of multi-objective optimization is better than the posterior approach of multi-objective optimization. When comparing these algorithms based on the results, it is obtained that the posterior approach gives a better combination of multiple results. The major outcome of the research is that the priori method is quick, while the posterior approach produces many promising solutions.

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Section: Doe Analysis Of Srmentioning

confidence: 92%

Section: Doe Analysis Of Mrrmentioning

confidence: 99%

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Comparison of priori and posteriori approach of multi-objective optimization for WEDM on Ti6Al4V alloy

Jain

Parashar

2022

Mater. Res. Express

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“…The influence of the process parameters on multiple outcomes such as MRR and SR were obtained using the 3D surface plots. Also, desirability function technique is used for finding optimum input process variables while machining α-β Titanium Alloy 7 .…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization in WEDM Process of Titanium Alloy (Ti-3Al-2.5V-2.0WC) using Desirability Approach

Muthusamy,

Ponnusamy,

Karthikeyan

et al. 2023

jmmf

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Recently, Titanium alloy (Ti-3Al-2.5V) reinforced with Tungsten Carbide (Ti-3Al-2.5V-2.0WC) developed using the microwave sintering process has plays a major role in mining industry. It has very good mechanical property and corrosion resistance. Due to its better strength and high melting point, it is difficult to machine in conventional machining process. Therefore, WEDM process give the solution to cut this high strength material in an effective manner. In this present work, the WEDM input variables such as Servo Voltage (SV), Pulse Time - On (PT-ON), Pulse Time – Off (PT-OFF) and Cutting Speed Percentage (CSP) are considered. L09 Orthogonal Array Matrix (OAM) is considered for experimental work. The output variables like Material Removal Rate (MRR) and Surface Roughness (SR) are considered to obtained the quality machining process. Multi objective optimization technique like Taguchi-Desirability Approach method is implemented to find the optimum input variables. The Improvement of MRR from 0.05978 g/min to 0.06420 g/min and SR from 3.812 μm to 3.452 μm are obtained using Desirability Approach.

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“…With the rapidly growing use of WEDM process for machining newer and advanced engineering materials, an ardent need is thus acknowledged for development and deployment of an innovative approach for studying the impacts of varied process parameters on the responses and identifying the parametric mix leading to optimization of WEDM process. From the review of the contemporary literature (Kumar et al, 2013;Lal et al, 2015;Dabade and Karidkar et al, 2016;Lusi et al, 2016;Manjaiah et al, 2016;Arikatla et al, 2017;Ramanan and Elangovan, 2018;Devarajaiah and Muthumari, 2018;Vignesh and Ramanujam, 2018;Srinivasarao and Suneel, 2018;Nayak et al, 2018), it has been revealed that determination of the optimal parametric mixes for WEDM processes has already caught the attention of the past researchers, and numerous multi-objective optimization techniques, like grey-Taguchi method, desirability function approach, technique for order of preference by similarity to ideal solution (TOPSIS), evolutionary algorithms etc. have been applied.…”

Section: Introductionmentioning

confidence: 99%

Management and Production Engineering Review

Dandge,

Chakraborty

2021

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Wire electrical discharge machining (WEDM) is a non-conventional material-removal process where a continuously travelling electrically conductive wire is used as an electrode to erode material from a workpiece. To explore its fullest machining potential, there is always a requirement to examine the effects of its varied input parameters on the responses and resolve the best parametric setting. This paper proposes parametric analysis of a WEDM process by applying non-parametric decision tree algorithm, based on a past experimental dataset. Two decision tree-based classification methods, i.e. classification and regression tree (CART) and Chi-squared automatic interaction detection (CHAID) are considered here as the data mining tools to examine the influences of six WEDM process parameters on four responses, and identify the most preferred parametric mix to help in achieving the desired response values. The developed decision trees recognize pulse-on time as the most indicative WEDM process parameter impacting almost all the responses. Furthermore, a comparative analysis on the classification performance of CART and CHAID algorithms demonstrates the superiority of CART with higher overall classification accuracy and lower prediction risk.

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Parametric Optimization of WEDM on α-β Titanium Alloy using Desirability Approach

Cited by 12 publications

References 15 publications

Comparison of priori and posteriori approach of multi-objective optimization for WEDM on Ti6Al4V alloy

Comparison of priori and posteriori approach of multi-objective optimization for WEDM on Ti6Al4V alloy

Multi-Objective Optimization in WEDM Process of Titanium Alloy (Ti-3Al-2.5V-2.0WC) using Desirability Approach

Management and Production Engineering Review

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