Use of the grey-Taguchi method to optimise the micro-electrical discharge machining (micro-EDM) of Ti-6Al-4V alloy

Lin, Mao Yong; Tsao, Chao Jung; Huang, Hsin‐Hsiang; Wu, Congcong; Hsu, Cheng-Ying

doi:10.1080/0951192x.2014.880946

Cited by 37 publications

(22 citation statements)

References 21 publications

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“…Muthuramalingam and Mohan [13] machined SS 201 through EDM and established the importance of peak current. Lin et al [14] conducted experiments on Ti-6Al-4V alloy through Micro-EDM and studied the influence of process parameters and gaps using the grey relational analysis (GRA)-Taguchi technique. The use of the GRA with Taguchi technique yields better results for tool electrode wear and overcut.Based on the above literature, the characteristics of EDM for machining holes on Inconel 718 are influenced by various input parameters.…”

Section: Method Considering Multi-responses Such As Machining Rate mentioning

confidence: 99%

Analysis of EDM Process Parameters on Inconel 718 Using the Grey-Taguchi and Topsis Method

Yuvaraj¹,

Suresh²

2019

SV-JME

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Nickel-based superalloys are gaining importance for their growing usage in aerospace industries. Amidst the various advanced machining processes, electro discharge machining (EDM) is considered to be an important one for its ability to machine materials irrespective of its intrinsic properties. In this study, Inconel 718 is considered as a work material, and an L18 orthogonal array (OA) experimental plan is utilized to machine the work material. The influential factors, which affect the EDM performance characteristics, are identified using analysis of variance (ANOVA). Not much work has been done regarding using grey-Taguchi technique for order of preference by similarity to ideal solution (TOPSIS) methods, although these methods can be easily applied for multi-objective optimization. These methods provide the best results with the available sparse data. The best combination of machining factors is determined using grey-Taguchi and TOPSIS methods. Based on the conducted experiments, voltage (V) and pulse off-time (t_off) show a notable contribution on output performance. The optimal combination of input parameter through grey-Taguchi is found to be 10 A, 30 V, 200 μs, and 20 μs respectively, for the EDM parameters: current (I), V, pulse on-time (t_on) and t_off for improved response. Moreover, the best parameter setting (I = 10 A, V = 30 V, t_on =100 μs and t_off = 20 μs) is identified using the TOPSIS method for the performance measures machining rate (MR), tool wear rate (TWR), overcut (OC), and taper overcut (TOC). Further tool wear behaviour is also studied through scanning electron microscope (SEM) images by varying the voltage.

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Section: Method Considering Multi-responses Such As Machining Rate mentioning

confidence: 99%

Analysis of EDM Process Parameters on Inconel 718 Using the Grey-Taguchi and Topsis Method

Yuvaraj¹,

Suresh²

2019

SV-JME

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“…By using the mean of grey relational grades of all parameters at different levels of all control factors and the difference between the maximum and the minimum value of the grey relational grades, the authors concluded that in micro-EDM drilling of Ti 6 Al 4 V alloy the most important parameters are, in the order, voltage (lower level), current (middle level), pulse width (higher level) and frequency (lower level). Lin et al(2015) combined Grey Relational analysis and Taguchi methods to optimize the input parameters Peak Current(A) {0.3, 0.5, 1}, Pulse on time(μs) {6, 13, 25}, Pulse off time(μs) {3, 6, 13}, and gap Voltage (V) {30, 35, 40},based on L9 design of experiment. They wanted to demonstrate that the use of the Grey-Taguchi method results in clear improvements in quality characteristics related to the single use of Taguchi method.…”

Section: Grey Relational Analysis-taguchi Methodsmentioning

confidence: 99%

Optimization of Micro-Electrical Discharge Machining Parameters of Ti6AL4V Component: A Mapping Study

Apostolopoulou¹,

Al-Juboori²

2019

JMR

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The micro-Electrical Discharge Machining (micro-EDM) is a non-conventional machining process which utilizes electro-thermal, non-contact effects to remove material from the workpiece. Micro-EDM is controlled by many machining parameters and its accuracy is evaluated by performance measures. It is employed when high accuracy and precision are required, especially when difficult-to-machine materials, like titanium alloy Ti6Al4V, are involved. Given the tremendous applications of Ti6Al4V in biomedical devices, automotive, aerospace and microelectromechanical systems, it is valuable to examine thoroughly the micro-EDM of Ti6Al4V component. This work reports a systematic mapping study of 36 papers published in journals and proceedings of conferences in the nearly two decades 2000-2018. First, we divide the papers into categories according to the various optimization techniques applied for the enhancement of micro-EDM machining process of Ti6Al4V component. Then, we discuss the techniques most used and give insight into the current research trends in micro-EDM. Accompanying comments about the use of the mentioned studies for teaching purposes may be of considerable interest for educators.

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“…removal rate of materials and roughness of the surface by selecting principal component analysis (PCA). Lin et al (2015) optimized multiple quality characteristics viz material removal rate, overcut and electrode depletion for achieving an improved surface roughness excellence of a Ti-6Al-4V alloy using micro electrical discharge machining. Selvaraj el al.…”

Section: Review Of Literaturementioning

confidence: 99%

Optimization of turning parameters of Aluminum 6351 T6 using Taguchi decision making technique

Ahmed¹,

Arora²

2017

10.5267/j.ijdns

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Turning is the utmost elementary process among several CNC machine tool operations which is a versatile, efficient and widely used in industries including mechanical, aerospace and automotive sectors. Most frequently the manufacturing industries face the problem of cutting down the production cost without any oblation in the quality of products. Selection of process parameter is essential for assuring a quality product. Convenient choice of the cutting conditions, parameters and tools for the maximum Material removal rate (MRR) and surface finish needs a sophisticated approach adopting mathematical and statistical models as well as experimental method. Taguchi's method is a very compelling tool to optimize the process variables. The intention of the present study is to determine surface roughness (Ra) and MRR which are key responses to justify the quality of turning operation. Four process parameters have been selected viz. Nose radius (NR), depth of cut (DOC), feed rate (FR) and spindle speed or cutting speed (CS) that influences these responses. During machining operations, the influence of the process parameters and their interaction have been analyzed using a statistical tool ANOVA. Aluminum alloy is widely acceptable by industries owing to its good strength to weight ratio, high resistance to corrosion, malleability and excellent resistance during elevated temperatures.

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Use of the grey-Taguchi method to optimise the micro-electrical discharge machining (micro-EDM) of Ti-6Al-4V alloy

Cited by 37 publications

References 21 publications

Analysis of EDM Process Parameters on Inconel 718 Using the Grey-Taguchi and Topsis Method

Analysis of EDM Process Parameters on Inconel 718 Using the Grey-Taguchi and Topsis Method

Optimization of Micro-Electrical Discharge Machining Parameters of Ti6AL4V Component: A Mapping Study

Optimization of turning parameters of Aluminum 6351 T6 using Taguchi decision making technique

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