Modeling of WEDM Parameters while Machining Mg-SiC Metal Matrix Composite

Tapadar, J; Thakur, Raj; Chetia, Pulakesh; Tamang, S. K.; Samanta, Soma

doi:10.14716/ijtech.v8i5.870

Cited by 8 publications

(2 citation statements)

References 5 publications

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“…In addition to these properties with WEDM, job with complex geometry and dimension can also be manufactured which is not possible in other non-traditional manufacturing process [6]. But in comparison the time taken to process the job is more than other methods [7]. Therefore, there is a high demand to develop a predictive model for forecasting the performance parameters for machining of Al5083/B 4 C composite by WEDM.…”

Section: Literature Reviewmentioning

confidence: 99%

Modelling and optimizing performance parameters in the wire-electro discharge machining of Al5083/B4C composite by multi-objective response surface methodology

Singh

Hussain

Dash

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

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Composite is an artificial multiphase material that constituent phases which are chemically dissimilar and separated by a distinct interface. As a result of such anisotropic and non-homogeneous formation machining of composites is a strenuous task. Therefore, the need arose for formulating a stable predictive model. The comprehensive intention of this study is to develop a highly robust and stable predictive soft-computing model for forecasting the machining performance of Al-5083 alloy reinforced with B 4 C particles (Al5083/B 4 C). The study mostly emphasize on selecting the best machining parameters among the conducted experiments and evaluating the optimal machining parameters for Al5083/B 4 C composite in wireelectro discharge machin. The paper is an integration of equally weighted experimental as well as computational study. In the experimental part of the study, 5 different specimen of Al5083/B 4 C is prepared by the ex situ technique through stir casting process. The experimental part includes design of experiment by Taguchi's method. The computational part of the study comprised of three different stages. The first stage involves the mathematical modelling of the performance measures and statistical scrutiny of the models. In the second stage, the best machining parameters are selected based on the fuzzy IFthen rules. The final stage of the manuscript is the trade-off analysis conducted to obtain the optimal machining parameters. In order to test the robustness of the formulated model an experimental validation is carried out at the optimal machining combination. The error calculated from the comparison is within the range of 2-5% which justifies the objective of the study.

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Section: Literature Reviewmentioning

confidence: 99%

Modelling and optimizing performance parameters in the wire-electro discharge machining of Al5083/B4C composite by multi-objective response surface methodology

Singh

Hussain

Dash

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

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show abstract

“…Figure 1 (a) Machined shape error; and (b) Traditional process to improve machining accuracy Acc/Dec characteristics vary depending on the machine tool, control generation, and machining conditions like feed rate (Sulaiman et al, 2022;Tapadar et al, 2017;Sodemann et al, 2011;Shih, Chen, and Lee, 2004;Matsubara, 2004;Schmitz and Ziegert, 2000). There are many techniques that offer some solutions to feed rate control (Yuwen et al, 2022;Yang and Altintas, 2015;Sencer, Ishizaki, and Shamoto, 2015;Yau and Kuo, 2001).…”

Section: Introductionmentioning

confidence: 99%

Prediction of Actual Toolpath and Enhancement of the Toolpath Accuracy Based on Identification of Feedrate Change Characteristics of Machine Tool

Dat,

Phuc

2024

IJTech

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Recently, the toolpath generation for high-speed machining of curved surfaces has become a non-trivial task. The approximated linear segments (G01-based) are widely used in commercial computer-aided manufacturing (CAM) systems. Due to the machine tool's acceleration/deceleration (Acc/Dec) control characteristics, there is a difference between the actual feed rate, the toolpath, and the commanded values when machining with CNC machine tools. This leads to the toolpath trajectory error. In addition, the cutting force applied to the cutting tool causes tool deflection. These factors cause errors between the designed and machined surfaces. In order to, therefore, predict the machined surface shape of a workpiece, it is necessary to predict the actual toolpath trajectory. The main objective of this study is to predict the actual toolpath trajectory by modeling the speed change. Furthermore, several toolpath generation methods in the postprocessing level are proposed to reduce the error between the actual toolpath and the commanded toolpath. The effectiveness and reliability of the methods are verified by experimental results.

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Experimental Investigation and Optimization of Wire Electrical Discharge Machining for Surface Characteristics and Corrosion Rate of Biodegradable Mg Alloy

Ahuja

Batra

Kumar

2020

J. of Materi Eng and Perform

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Modeling of WEDM Parameters while Machining Mg-SiC Metal Matrix Composite

Cited by 8 publications

References 5 publications

Modelling and optimizing performance parameters in the wire-electro discharge machining of Al5083/B4C composite by multi-objective response surface methodology

Modelling and optimizing performance parameters in the wire-electro discharge machining of Al5083/B4C composite by multi-objective response surface methodology

Prediction of Actual Toolpath and Enhancement of the Toolpath Accuracy Based on Identification of Feedrate Change Characteristics of Machine Tool

Experimental Investigation and Optimization of Wire Electrical Discharge Machining for Surface Characteristics and Corrosion Rate of Biodegradable Mg Alloy

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