Investigation of Material Removal Rate and Tool Wear Rate in Spark Erosion Machining of Al-Fe-Si Alloy Composite Using Taguchi Coupled TOPSIS Approach

Alagarsamy, S.V.; Raveendran, P. Saji; Ravichandran, M.

doi:10.1007/s12633-020-00596-x

Cited by 18 publications

(4 citation statements)

References 28 publications

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“…The predicted result of the output responses are calculated by using equation (9). 31 where, η pre predicted value of response, η m total mean value of response, η i is response mean value at the optimum level and k number of control parameters. Table 9 shows the predicted and experimental result of the output responses at the optimal range of control parameters obtained by Taguchi and TOPSIS method.…”

Section: Resultsmentioning

confidence: 99%

“…TOPSIS method was introduced by Hwang and Yoon, in which main aspect is to indicate the best alternatives having shortest distance from the positive ideal solution and farthest from the negative ideal solution. 31 The positive ideal solution is a solution that tries to maximize the profit criteria and minimizes the cost criteria, whereas negative ideal solution maximizes the cost criteria and minimizes the profit criteria. The given steps are employed by TOPSIS method for the selection of best alternative from among these available alternatives is as follows,…”

Section: Methodologies and Implementationmentioning

confidence: 99%

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Prediction of tribological performance of AA8011/wt.%ZrO₂ based composites fabricated by stir casting route

Vinoth¹,

Alagarsamy²,

Meignanamoorthy³

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part E:

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Aluminium alloy composites are most popular owing to their versatile applications like high performance parts in aerospace, automotive and marine industries. The intent of current research work is, to predict the optimal parameters for dry sliding wear behaviour of AA8011 matrix composites by using multi attribute decision making method. The varying proportions of zirconia (ZrO2) particles filled composites such as AA8011-5 wt.% ZrO2, AA8011-10 wt.% ZrO2 and AA8011-15 wt.% ZrO2 were synthesized through stir casting method. The microstructure of the proposed composites taken by scanning electron microscopy (SEM), and it was ensure the presence of reinforcement particles homogeneously distributed within the matrix alloy. The produced composites were subjected to conduct the dry sliding wear test by using pin-on-disc test rig. During the experiments, four wear control parameters with three levels namely, reinforcement (5 wt.%, 10 wt.% and 15 wt.%), applied load (9.81 N, 19.62 N and 29.43 N), sliding velocity (0.94 m/s, 1.88 m/s and 3.76 m/s) and sliding distance (1000 m, 1500 m and 2000 m) were used. A Taguchi coupled TOPSIS method was employed to predict the multiple responses such as wear rate (WR) and coefficient of friction (COF) of produced composites. Experimental result has been observed that, the reinforcement content was the most remarkable parameter on WR and COF with contribution of 55.06%, subsequently by applied load and sliding velocity with contribution of 26.32% and 12.84% respectively. The worn out surfaces of the tested composite was investigated through SEM analysis.

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Section: Resultsmentioning

confidence: 99%

Section: Methodologies and Implementationmentioning

confidence: 99%

Prediction of tribological performance of AA8011/wt.%ZrO₂ based composites fabricated by stir casting route

Vinoth¹,

Alagarsamy²,

Meignanamoorthy³

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part E:

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“…The significant influence of current intensity on response indicators compared to other parameters was reported. Alagarsamy et al [22] studied the impact of process variables namely electrode material and pulse controlling parameters on EWR and MRR . They also determined the optimum condition for maximum MRR and minimum EWR using TOPSIS method.…”

Section: Introductionmentioning

confidence: 99%

Experimental study on surface characteristics in μED milling of Al6063%-5%B4C-5%ZrSiO₄ composite using TOPSIS method

Narasimmalu¹,

Ramabalan²

2022

Surf. Topogr.: Metrol. Prop.

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Al6063 composites are widely used in automobile, aerospace and biomedical industries due to their excellent mechanical properties. Machining of micro channels in composites is difficult for conventional machining process due to presence of hard reinforcement. Materials with base metal. Micro Electrical discharge (µED) milling is popular micromachining technique for machining simple, intricate shapes and microchannels on any conductive material. However, it a slow machining process, the identification of optimum condition has become wide research area in µEDM. The present work aims to study the influence of process variables namely voltage, spindle speed and threshold on machining characteristics of µED milling of Hybrid Metal Matrix Composites (HMMCs). Experimental trials are carried out with copper electrode at different parametric condition. Al6063-5%B4C-5%ZrSiO4 composite was fabricated using stir casting method and experimental runs were designed using general full factorial method. The significant parameters are identified using Analysis of Variance (ANOVA) and the ideal machining conditions for multi-response are determined using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The morphology of machined surface with best and worst conditions is examined using SEM. Results indicated that the voltage and threshold are the influencing parameters for considered response indicators. Recast layer thickness seems to be low with best machining conditions as compared to worst conditions. Increase in voltage and threshold increases the Material Removal Rate (MRR) and decreases the Electrode Wear Rate (EWR). Surface finish is better when the lower order of capacitance and voltage is used. MRR is increased by 48% with best machining conditions compared to worst machining condition.

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“…e smallest distance from the positive ideal solution (PIS) and the greatest distance from the negative ideal solution (NIS) are used to rank the options. TOPSIS explores the ranges of both PIS and NIS, ranking candidates based on their relative proximity and combining the two distance measurements [25]. Taguchi's DoE was combined with the TOPSIS to identify the processing parameters for milling the Inconel 625 alloy.…”

Section: Introductionmentioning

confidence: 99%

Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant

Mohanraj

Radhika

Nanda

et al. 2022

Advances in Materials Science and Engineering

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Productivity and cost-effectiveness are essential components of any long-term manufacturing system. While quantity and quality are linked to productivity, the economy focuses on energy-efficient processes that produce a high output-to-input ratio. Hard-to-cut materials have always been difficult to machine because of more significant tool wear and power losses. Inconel 625 is a hard material used in aerospace and underwater applications and is milled using biolubricants with nanoparticles. Palm oil is considered a biolubricant, and titanium dioxide (TiO2) and copper oxide (CuO) are selected as nanoparticles. When the combination of biolubricants and nanoparticles is added to the workpiece’s surface, it enhanced some properties while machining. Experiments involving four factors with four levels were carried out using the Taguchi design of experiments (DoE). The feed, depth of cut, speed, and coolant with nanoparticle additives were all factors. The responses were surface roughness, spindle vibration along X, Y, and Z axes, and material removal rate. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to alter the multiresponse optimization problem to a single-response optimization problem. The S/N of TOPSIS closeness coefficients was calculated, and the optimal machining conditions were determined. Surface roughness, material removal rate, and spindle vibration were reduced by 3.10%, 6.14%, 7.54% (Vx), and 6.78% (Vz), respectively, due to the TOPSIS optimization.

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Investigation of Material Removal Rate and Tool Wear Rate in Spark Erosion Machining of Al-Fe-Si Alloy Composite Using Taguchi Coupled TOPSIS Approach

Cited by 18 publications

References 28 publications

Prediction of tribological performance of AA8011/wt.%ZrO₂ based composites fabricated by stir casting route

Prediction of tribological performance of AA8011/wt.%ZrO₂ based composites fabricated by stir casting route

Experimental study on surface characteristics in μED milling of Al6063%-5%B4C-5%ZrSiO₄ composite using TOPSIS method

Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant

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Investigation of Material Removal Rate and Tool Wear Rate in Spark Erosion Machining of Al-Fe-Si Alloy Composite Using Taguchi Coupled TOPSIS Approach

Cited by 18 publications

References 28 publications

Prediction of tribological performance of AA8011/wt.%ZrO2 based composites fabricated by stir casting route

Prediction of tribological performance of AA8011/wt.%ZrO2 based composites fabricated by stir casting route

Experimental study on surface characteristics in μED milling of Al6063%-5%B4C-5%ZrSiO4 composite using TOPSIS method

Parameter Optimization and Machining Performance of Inconel 625 with Nanoparticles Dispersed in Biolubricant

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Prediction of tribological performance of AA8011/wt.%ZrO₂ based composites fabricated by stir casting route

Prediction of tribological performance of AA8011/wt.%ZrO₂ based composites fabricated by stir casting route

Experimental study on surface characteristics in μED milling of Al6063%-5%B4C-5%ZrSiO₄ composite using TOPSIS method