Application of neural network and genetic algorithm to powder metallurgy of pure iron

Reihanian, M.; Asadullahpour, S.R.; Hajarpour, S.; Gheisari, Kh.

doi:10.1016/j.matdes.2011.02.049

Cited by 48 publications

(24 citation statements)

References 15 publications

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“…RSM is a collection of mathematical and statistical techniques that are useful for the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response [1]. The Design Expert version 7 software was used to develop the design matrix for conducting the experimentation and same software was used to optimize the process parameters [8].…”

Section: Fabrication By Powder Metallurgymentioning

confidence: 99%

“…Powder metallurgy is the method of producing a component to a net shape or near net shape [1]. Density of the components can be controlled easily through powder metallurgy method when compared to other manufacturing processes [2,3].…”

Section: Introductionmentioning

confidence: 99%

“…Hence, nanoSiC particles can be embedded along with aluminium which is used to manufacture various machine elements like drive shafts, brake rotors, and brake drums in automobiles, for ventral fins and fuel access covers in aircraft to reduce wear. Similarly, nano-Titanium Carbide (TiC) possesses several advantages such as high specific strength, good corrosion resistance, and good wear property [1]. Along with these properties, Titanium Carbide has excellent strength to weight ratio which is particularly in need to the aerospace, chemical, and architectural industries.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the Mechanical Properties of Hybrid Aluminium 7075 Matrix Composite Material Reinforced with SiC and TiC Produced by Powder Metallurgy Method

Devaneyan

Ganesh²,

Senthilvelan

2017

Indian Journal of Materials Science

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Metal matrix composites are widely used in components of various components of industrial equipment because of their superior material properties like high stiffness to weight ratio and high impact strength and fracture toughness while compared to the conventional material. Due to the concepts of high strength to low weight ratio, Al 7075 was extensively applied in aircraft engine and wings. Even if Al 7075 has higher hardness, higher strength, excellent wear resistance, and high-temperature corrosion protection, it is in need of further enhancement of properties for increasing its applicability. This paper presents the mechanical behavior of aluminium 7075 reinforced with Silicon Carbide (SiC) and Titanium Carbide (TiC) through powder metallurgy route. These specimens were produced by powder metallurgy method. The hybrid composite was made by Al 7075 alloy as the matrix with Silicon Carbide and Titanium Carbide as reinforcement. Silicon Carbide and Titanium Carbide are mixed in different weight ratio based on the design matrix formulated through a statistical tool, namely, Response Surface Methodology (RSM). Enhanced mechanical properties have been obtained with 90% of Al 7075, 4% of TiC, and 8% of SiC composition in the composite. Coefficient of friction appears to be more which has been determined by ring compression test.

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Section: Fabrication By Powder Metallurgymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On the Mechanical Properties of Hybrid Aluminium 7075 Matrix Composite Material Reinforced with SiC and TiC Produced by Powder Metallurgy Method

Devaneyan

Ganesh²,

Senthilvelan

2017

Indian Journal of Materials Science

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“…ANNs have been used in many engineering disciplines such as materials [50,[59][60][61][62][63][64], biochemical engineering [65], medicine [66] and mechanical engineering [67][68][69][70][71].…”

Section: Artificial Neural Networkmentioning

confidence: 99%

“…The processes that have more contribution to the evolution are the crossover, based in the selection and reproduction and the mutation. GAs have been applied to a diverse range of scientific, engineering and economic problems [63,67,[216][217][218] due to their potential as optimisation techniques for complex functions. There are four major advantages when applying genetic algorithms to optimisation problems.…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Development of an advanced data analytics model to improve the energy efficiency of haul trucks in surface mines

Soofastaei¹

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Truck haulage is responsible for a majority of cost in a surface mining operation. Diesel fuel, which is costly and has a significant environmental footprint, is used as a source of energy for haul trucks in surface mines. Reducing diesel fuel consumption would lead to a reduction in haulage cost and greenhouse gas emissions. The determination of fuel consumption is complex and requires multiple parameters including the mine, fleet, truck, fuel, climate and road conditions as input. Data analytics is used to simulate the complex relationships between the input parameters affecting the truck fuel consumption. This technique is also used to optimise the input parameters to minimise the fuel consumption without losing productivity or further capital expenditure for a specific surface mining operation.The aim of this research thesis is to develop an advanced data analytics model to improve the energy efficiency of haul trucks in surface mines. The most important controllable parameters affecting fuel consumption are first identified, namely payload, truck speed and total resistance. These parameters are selected based on the results of an online survey. A comprehensive analytical framework is developed to determine the opportunities for minimising the truck fuel consumption. The first stage of the analytical framework includes the development of an artificial neural network model to determine the relationship between truck fuel consumption and payload, truck speed and total resistance. This model is trained and tested using real data collected from some large surface mines in USA and Australia. A fitness function for the haul truck fuel consumption is successfully generated. This fitness function is then used in the second stage of the analytical framework to develop a computerised learning algorithm based on a novel multi-objective genetic algorithm. The aim of this algorithm is to estimate the optimum values of the three effective parameters to reduce the diesel fuel consumption.The following studies are also conducted to enhance the analysis of haul truck fuel consumption.First, a comprehensive investigation of loading variance influence on fuel consumption and gas emissions in mine haulage operation is carried out. Then, a discrete-event model to simulate the effect of payload variance on truck bunching, cycle time and hauled mine materials is developed. The influence of rolling resistance on haul truck fuel consumption in surface mines is investigated.

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Hybrid neural network-based prediction model for tribological properties of polyamide6-based friction materials

2015

Polym. Compos.

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The hybrid neural network employed to predict the tribological properties of solid lubricants reinforced nano-TiO 2 /polyamide6 composites was established based on the back propagation and radial basis function networks, and optimized by adaptive genetic algorithm. With such three factors as material composition, testing loads, and velocities, orthogonal tests were designed and the data obtained was used for training the neural network. The correlation index between the predicted and the experimental values for friction coefficient and ware rate were 0.992 and 0.998, respectively, and 3D plots for the predicted friction coefficient and wear rate as a function of material compositions and testing conditions were established. It shows that the results are in good agreement with the data measured. It is demonstrated that the well-optimized neural network had remarkable capability for modeling concern. POLYM. COMPOS., 38:1705-1711

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Application of neural network and genetic algorithm to powder metallurgy of pure iron

Cited by 48 publications

References 15 publications

On the Mechanical Properties of Hybrid Aluminium 7075 Matrix Composite Material Reinforced with SiC and TiC Produced by Powder Metallurgy Method

On the Mechanical Properties of Hybrid Aluminium 7075 Matrix Composite Material Reinforced with SiC and TiC Produced by Powder Metallurgy Method

Development of an advanced data analytics model to improve the energy efficiency of haul trucks in surface mines

Hybrid neural network-based prediction model for tribological properties of polyamide6-based friction materials

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