Optimization of machining parameters in turning of Al-SiC-Gr hybrid metal matrix composites using grey-fuzzy algorithm

Suresh, P.; Marimuthu, K.; Ranganathan, S.; Rajmohan, T.

doi:10.1016/s1003-6326(14)63412-9

Cited by 167 publications

(56 citation statements)

References 26 publications

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“…His work suggested that 40% of the reinforced particles contribute to the abrasion at the chipetool interface. Suresh et al [9] has attempted to find the optimal level of machining parameters for multi performance characteristics in turning of Al/SiC/Gr hybrid composites using a greyefuzzy algorithm. They reported that 10% reinforced SiC and Gr reinforced hybrid composites provide better machinability when compared with 5% and 7.5% of SiCeGr composites.…”

Section: Introductionmentioning

confidence: 99%

Effect of reinforcement on the cutting forces while machining metal matrix composites–An experimental approach

Shoba

Ramanaiah

Rao

2015

Engineering Science and Technology, an International Journal

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a b s t r a c tHybrid metal matrix composites are of great interest for researchers in recent years, because of their attractive superior properties over traditional materials and single reinforced composites. The machinabilty of hybrid composites becomes vital for manufacturing industries. The need to study the influence of process parameters on the cutting forces in turning such hybrid composite under dry environment is essentially required. In the present study, the influence of machining parameters, e.g. cutting speed, feed and depth of cut on the cutting force components, namely feed force (F f ), cutting force (F c ), and radial force (F d ) has been investigated. Investigations were performed on 0, 2, 4, 6 and 8 wt% Silicon carbide (SiC) and rice husk ash (RHA) reinforced composite specimens. A comparison was made between the reinforced and unreinforced composites. The results proved that all the cutting force components decrease with the increase in the weight percentage of the reinforcement: this was probably due to the dislocation densities generated from the thermal mismatch between the reinforcement and the matrix. Experimental evidence also showed that built-up edge (BUE) is formed during machining of low percentage reinforced composites at high speed and high depth of cut. The formation of BUE was captured by SEM, therefore confirming the result. The decrease of cutting force components with lower cutting speed and higher feed and depth of cut was also highlighted. The related mechanisms are explained and presented.

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Section: Introductionmentioning

confidence: 99%

Effect of reinforcement on the cutting forces while machining metal matrix composites–An experimental approach

Shoba

Ramanaiah

Rao

2015

Engineering Science and Technology, an International Journal

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“…The use of grey-based fuzzy method will considerably improve the performance of machining. The grey fuzzy approach has momentous influence on the enhancement of machining performance and accuracy of outcomes (Ahilan et al, 2009;Das et al, 2014;Lin et al, 2000;Pandey and Panda, 2014;Suresh et al, 2014;Guo et al, 2017). So the adoption of the grey theory with any of the artificial intelligence decision making tools will help to improve the desired performance measures.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Spark Erosion Machining Process Parameters using Hybrid Grey Relational Analysis and Artificial Neural Network Model

Manikandan¹,

Raju²,

Palanisamy³

et al. 2019

IJMMM

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Hastealloy C276 is hard to machine superalloy and extensively used in various engineering applications. It possess good strength and lower thermal conductivity which results in decreased tool life and poor machinability by conventional machining. Advanced machining processes have developed to overcome these difficulties and claimed as an alternative methods. Electrical Discharge Machining (EDM) is one of the advanced method used for machining of hard materials. This article details an investigation on EDM process and development of hybrid Grey ANN model. Taguchi method and ANOVA are used for designing the experiments and statistical analysis respectively. Grey Relational Analysis is adopted for determining the Grey Relational Grade (GRG) to represent the multi aspect optimization model and a

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“…Joardar et al [15] formed experimental mathematical model equations using response surface methodology for analyzing the effect of turning parameters on stir cast LM6/ SiC AMC. Suresh et al [16] found out optimum turning parameters for LM25/5-10 wt% (SiC + Gr) AMCs by applying gray fuzzy logic. Shoba et al [17] noticed a considerable reduction in residual stress of turned surface compared to as cast A356/0-8 wt% (SiC + RHA) hybrid AMCs.…”

Section: Introductionmentioning

confidence: 99%

Predicting the effect of machining parameters on turning characteristics of AA7075/TiB2 in situ aluminum matrix composites using empirical relationships

Pugazhenthi

Dinaharan

Kanagaraj

et al. 2018

J Braz. Soc. Mech. Sci. Eng.

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Aluminum matrix composites (AMCs) are difficult to machine due to increased tool wear. AA7075/(0-12 wt%) TiB 2 in situ AMCs were prepared and turned in a modified conventional lathe using polycrystalline diamond cutting tool. A central composite rotatable design comprising of four process parameters and five levels was utilized to limit the actual experiments required for prediction. The turning parameters such as cutting speed, feed rate, depth of cut and TiB 2 particulate content were counted as variables for the experiments. Two empirical relationships were formed for the prediction of the outcome of variable parameters on cutting force and surface roughness. The cutting force showed a downward trend with an increase in cutting speed and TiB 2 content. The advancement in feed rate and depth of cut increased the requirement of cutting force. The predicted trends were correlated with the morphology of the tool rake face and the turned surface. The development of builtup edge increased the cutting force requirement and reduced the surface finish due to deposition on the newly turned surface.

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Optimization of machining parameters in turning of Al-SiC-Gr hybrid metal matrix composites using grey-fuzzy algorithm

Cited by 167 publications

References 26 publications

Effect of reinforcement on the cutting forces while machining metal matrix composites–An experimental approach

Effect of reinforcement on the cutting forces while machining metal matrix composites–An experimental approach

Optimization of Spark Erosion Machining Process Parameters using Hybrid Grey Relational Analysis and Artificial Neural Network Model

Predicting the effect of machining parameters on turning characteristics of AA7075/TiB2 in situ aluminum matrix composites using empirical relationships

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