Experimental analysis of magneto rheological abrasive flow finishing process on AISI stainless steel 316L

Kathiresan, S.; Mohan, B.

doi:10.1080/10426914.2017.1279317

Cited by 37 publications

(14 citation statements)

References 23 publications

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“…This research not only set up predictive models of material removal rate(MRR) and surface roughness but also figured out optimal process parameters affecting desired values by the experimental approach and firefly algorithm. On the basis of a developed mathematical model, there was a good agreement between observed and predicted results [9,10]. Jayant and Jain attempted to perform numerical analysis of magnetic flux density, flow characteristics, and MRR which affected the ultra-fine finished surface of an asymmetric medical implant in the MRAFF process for predicting the final surface state accurately.…”

Section: Introductionmentioning

confidence: 98%

The Effect of Abrasive Particles Movement on Deburring Effectiveness in REMF Process by using Explicit Dynamic Simulations

Lee¹,

Lee²,

Kwak³

2021

Preprint

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The main aim of this study was to suggest rotating electro-magnetic finishing(REMF) which had the capability to yield ultra-fine finished surface in micro-meter level with high productivity in a short time. The performance of the REMF process was primarily dependent upon magnetic and impact energy by the physical properties of a particle, particle velocity, and impact angle. Therefore, in this study, numerical simulations were conducted by explicit dynamic analysis to verify the effect of both single and multiple abrasive media impact characteristics on a deburring area of the machined surface. Based on the observed results and Pareto analysis, it was found that the overall weight of the particles was the most significantly affected for burr reduction, and deburring area was proportional to the increasing impact angle as well. In addition, to estimate the relationship between process factors and output variable and determine the optimum condition for burr reduction, a second-order polynomial model was developed by adopting a response surface methodology. As a result, the predictive model agreed with numerical analyzed results with 84.4% of the accuracy rate. The optimized deburring area was 2.27mm2 at 1,800rpm of rotational velocity, 0.7mm of particle diameter, and 2.0kg of total particle weight. It was founded to be similar to the maximum deburring area, about 2.37mm2, obtained from the simulations at the same condition.

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Section: Introductionmentioning

confidence: 98%

The Effect of Abrasive Particles Movement on Deburring Effectiveness in REMF Process by using Explicit Dynamic Simulations

Lee¹,

Lee²,

Kwak³

2021

Preprint

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“…It should be noted that AFM is found under a variety of process-assisted alternatives such as ultrasonic-assisted AFM [5], magnetic abrasivesassisted AFM [6], and electrochemical-aided abrasive flow finishing (ECA2FM) [7] to name a few. Other important advances in abrasive machining techniques forming a research perspective are presented in references [8][9][10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Abrasive Flow Nano-Finishing Processes by Adopting Artificial Viral Intelligence

Fountas

Vaxevanidis

2021

JMMP

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This work deals with the optimization of crucial process parameters related to the abrasive flow machining applications at micro/nano-levels. The optimal combination of abrasive flow machining parameters for nano-finishing has been determined by applying a modified virus-evolutionary genetic algorithm. This algorithm implements two populations: One comprising the hosts and one comprising the viruses. Viruses act as information carriers and thus they contribute to the algorithm by boosting efficient schemata in binary coding to facilitate both the arrival at global optimal solutions and rapid convergence speed. Three cases related to abrasive flow machining have been selected from the literature to implement the algorithm, and the results corresponding to them have been compared to those available by the selected contributions. It has been verified that the results obtained by the virus-evolutionary genetic algorithm are not only practically viable, but far more promising compared to others as well. The three cases selected are the traditional “abrasive flow finishing,” the “rotating workpiece” abrasive flow finishing, and the “rotational-magnetorheological” abrasive flow finishing.

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“…The microstructure examination showed the abrasive cutting marks in this process. Kathiresan and Mohan [5] optimized parameters in finishing of AISI stainless steel 316 L to a nano-level with the help of MRAFF process. RSM was employed to optimize SR and MRR.…”

Section: Introductionmentioning

confidence: 99%

Mechanism of Material Removal in Magneto Abrasive Flow Machining

Singh

Singh²,

Singh

2021

Lecture Notes in Mechanical Engineering

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The material removal in finishing of precision parts and hard to reach regions comprises a standout amongst the most demanding and costly stages in a manufacturing process. The magnetic abrasive flow machining (MAFM) is one of the non-traditional machining techniques which can successfully manage these problems. The MAFM process provides excellent surface finish at comparative low cost. The objective of the present investigation has been to understand the mechanism of the material removal (MR) and roughness improvement rate (RIR) in MAFM on a non-magnetic, soft and ductile workpiece. Finishing fluid in this study contains iron particles as magnetic bonders and diamond particles as abrasive part in different mesh size. Experimentation was conducted on aluminum tubes to investigate the effect of the key parameters on the MR and RIR and was designed in central composite design (CCD) of response surface methodology (RSM). It has been found that magnetic flux density (MFD) and number of cycles have impact on material removal and surface roughness. Based on experimental results, regression analysis of MR and RIR has been performed. This analysis has been used to predict MR and RIR compared with the experimentally obtained results. Both were found in close agreement. Finished surfaces were also examined using the scanning electron microscope (SEM) to get the knowledge for the fine surface texture produced by MAFM.

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Experimental analysis of magneto rheological abrasive flow finishing process on AISI stainless steel 316L

Cited by 37 publications

References 23 publications

The Effect of Abrasive Particles Movement on Deburring Effectiveness in REMF Process by using Explicit Dynamic Simulations

The Effect of Abrasive Particles Movement on Deburring Effectiveness in REMF Process by using Explicit Dynamic Simulations

Optimization of Abrasive Flow Nano-Finishing Processes by Adopting Artificial Viral Intelligence

Mechanism of Material Removal in Magneto Abrasive Flow Machining

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