Multi-response Optimization of Alumina Powder-Mixed WEDM Process Using Taguchi-TOPSIS Approach of Nitinol SMA

2022 ◽  
pp. 359-367
Author(s):  
Rakesh Chaudhari ◽  
Manav Sheth ◽  
Het Patel ◽  
Kishan Fuse ◽  
Izaro Ayesta ◽  
...  
Keyword(s):  
Alumina Powder ◽  
Response Optimization ◽  
Topsis Approach ◽  
Wedm Process

Multi-Response Optimization of Micro-WEDM Process Parameters of Ti49.4-Ni50.6 Shape Memory Alloy for Orthopedic Implant Application

2018 ◽  
Vol 1150 ◽  
pp. 1-21
Author(s):  
Adik M. Takale ◽  
Nagesh K. Chougule ◽  
Preetam H. Selmokar ◽  
M.G. Gawari
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Process Parameters ◽  
Removal Rate ◽  
Orthopedic Implant ◽  
Wire Tension ◽  
Response Optimization ◽  
Micro Wedm ◽  
Wedm Process ◽  
Wire Feed

The present work deals with the optimization of micro-WEDM process parameters for machining Ti49.4-Ni50.6 shape memory alloy (SMA) for orthopedic implant application. Effect of micro-WEDM parameters viz. Gap voltage, capacitance, wire feed and wire tension on the response variables such as material removal rate, surface roughness, kerf width and dimensional deviation is determined. As Ti-Ni SMA has fascinating properties and bio-compatibility, have been considered for present work. Nine experiments have been performed on micro-WEDM based on an orthogonal array of Taguchi method. Subsequently, the grey relational analysis (GRA) method is applied to determine an optimal set of process parameters. It is observed that optimized set of parameters A3B3C3D1 viz. 140 V gap voltage, 0.4 µF capacitance, wire feed 30 µm/sec and 30% of wire tension determined by using GRA offers maximum MRR and minimum SR, KW and DD. From the Analysis of Variance, it is seen that the process parameter capacitance is the most significant parameter for multi-response optimization with a percentage contribution of 77.91%. Young’s modulus also checked for biocompatibility. Also, SEM images are taken to confirm the results offering better surface quality. Heat treatment process like annealing is found to be the most suitable to recover shape memory effect of WEDMed samples.

Multi-Response Optimization of CNC WEDM Process Parameters for Machining Titanium Alloy Ti 6AI-4V Using Response Surface Methodology (RSM)

2014 ◽  
Vol 541-542 ◽  
pp. 354-358 ◽  
Author(s):  
C. Nandakumar ◽  
B. Mohan
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Titanium Alloy ◽  
Response Surface ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Response Optimization ◽  
Wedm Process

This research deals with the multi-response optimization of CNC WEDM process parameters for machining titanium alloy Ti 6AI-4V using Response Surface Methodology (RSM) to achieve higher Material Removal Rate (MRR) and lower surface roughness (Ra). The process parameters of CNC WEDM namely pulse-on time (TON), pulse-off time (TOFF) and wire feed rate (WF) were optimized to study the responses in terms of material removal rate and surface roughness. The surface plot and the contour plots were generated between the process parameters and the responses using MINITAB software. The results show that the Response surface methodology (RSM) is a powerful tool for providing experimental diagrams and statistical-mathematical models to perform the experiments appropriately and economically.

Multi Response Optimization of Submerged Friction Stir Welding Process Parameters Using TOPSIS Approach

2015 ◽  
Author(s):  
Senthil Kumar Velukkudi Santhanam ◽  
Lokesh Rathinaraj ◽  
Rathinasuriyan Chandran ◽  
Shankar Ramaiyan
Keyword(s):  
Friction Stir Welding ◽  
Process Parameters ◽  
Welding Process ◽  
Fusion Welding ◽  
Friction Stir ◽  
Friction Stir Welding Process ◽  
Response Characteristics ◽  
Response Optimization ◽  
Topsis Approach ◽  
Tool Pin

Friction stir welding (FSW) is a solid-state welding process which is used to join high-strength aircraft aluminum alloys and other metallic alloys which are difficult to weld by conventional fusion welding. In this paper, AA6063-O alloy of 6mm thickness was taken and friction stir welded under the water in order to improve the joint properties. The process parameters considered as rotational speed, welding speed and tool pin profiles (cylindrical, threaded and tapered) are optimized with multi response characteristics including hardness, tensile strength and % elongation. In order to solve a multi response optimization problem, the traditional Taguchi approach is insufficient. To overcome this constraint, a multi criteria decision making approach, namely, techniques for order preference by similarity to ideal solution (TOPSIS) is applied in the present study [13]. The optimal result indicates that the multi response characteristics of the AA6063-O during the submerged friction stir welding process can be enhanced through the TOPSIS approach. The Analysis of Variance (ANOVA) was carried out to investigate the significant parameter for the submerged friction stir welding process. The mechanical properties of the submerged FSW are compared with normal FSW joints.

scholarly journals Multi-response optimization for Nimonic alloy miniature gear fabrication using wire electrical discharge machining

2020 ◽  
Vol 12 (10) ◽  
pp. 168781402096758
Author(s):  
Tina Chaudhary ◽  
Arshad Noor Siddiquee ◽  
Arindam Kumar Chanda ◽  
Mustufa Haider Abidi ◽  
Abdulrahman Al-Ahmari
Keyword(s):  
Surface Roughness ◽  
Ethylene Glycol ◽  
Process Parameters ◽  
Dielectric Fluid ◽  
Alumina Powder ◽  
Response Factors ◽  
Machining Time ◽  
Wire Tension ◽  
Demineralized Water ◽  
Response Optimization

Generally, gear is an essential component in various electro-mechanical devices, but its manufacturing at the micro-level is challenging. The non-conventional manufacturing processes, such as electro-discharge machining (EDM), is suitable in gear fabrication. Although miniature gears have strict accuracy requirements, the optimization of the EDM process parameters, especially for advanced materials and alloys, is critical. In this paper, Nimonic alloy miniature gears are manufactured using wire-EDM and the effect of process parameters, such as peak current, pulse-off (POFF) time, pulse-on (PON) time, wire tension, and dielectric fluid on the response factors are analyzed. The primary response factors, such as surface roughness, machining time, material removal rate, kerf width (KW), surface microhardness, and depth of microhardness are considered. Also, different dielectric fluids are prepared, which include ethylene glycol mixed demineralized water, oxygen mixed demineralized water, ethylene glycol and alumina powder mixed demineralized water, and ethylene glycol alumina powder and oxygen mixed demineralized water. Furthermore, the effect of process parameters on the multi-response using Pareto ANOVA has been analyzed. The results demonstrate that ethylene glycol mixed demineralized water, as a dielectric fluid, is the most influencing parameter to reduce the surface roughness, machining time, KW, and improve micro-hardness. Thus, dielectric fluid is an essential factor obtained from multi-response optimization followed by peak current, POFF time, wire tension, and PON time.

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