Trade-off among mechanical properties and energy consumption in multi-pass friction stir processing of Al7075 alloy employing neural network–based genetic optimization

Hussain, G.; Ranjbar, Mostafa; Hassanzadeh, Saïna

doi:10.1177/0954405415569817

Cited by 18 publications

(10 citation statements)

References 32 publications

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“…The processing zones using FSP were prone to defects such as crack, voids and air bubbles because of insufficient or excess heat input. 24 Saeedy et al 25 found that the heat input was proportional to the inverse of traverse speed. Increasing the transverse speed would decrease the maximum temperature and the amount of molten material inside the processed zone but increase the heating and cooling rates.…”

Section: Methodsmentioning

confidence: 99%

“…As a complex process, FSP included non-uniform material flow. 24 The character of the processed zone was affected by the tool parameter and process parameter which dictated the overall heat input. In FSP, the ''processing time,'' the time during which the material has undergone the thermalmechanical influence, was influenced by transverse speed.…”

Section: Morphology Analysesmentioning

confidence: 99%

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Investigations into the mechanical, morphological and thermal analyses of friction stir processing of high-density polyethylene composites

Gao

Shen

2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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The aim of this work is to fabricate the high-density polyethylene-copper composites by submerged friction stir processing at different traverse speeds. The scanning electron microscopy is used to analyze the distribution of microstructure and particles. The experimental results indicated that the macrostructure morphology, microstructure and tensile strength vary depending on the traverse speed. Compared with the pure high-density polyethylene, Cu-filled polymer composites showed lower tensile strength and higher microhardness. The maximal values of the tensile strength and microhardness were achieved at traverse speeds of 30 and 15 mm/min, respectively. The thermal properties of Cu-filled high-density polyethylene composites were studied by differential scanning calorimetry. The crystalline content of the composites was decreased due to the addition of copper. From the experimental tests, it can be concluded that submerged fiction stir processing has a great potential for producing polymer-metal composites.

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Section: Methodsmentioning

confidence: 99%

Section: Morphology Analysesmentioning

confidence: 99%

Investigations into the mechanical, morphological and thermal analyses of friction stir processing of high-density polyethylene composites

Gao

Shen

2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…The optimization can be performed either employing statistical techniques or artificial intelligence algorithms. It has been shown in previous studies for similar tasks that the results of statistical techniques have not been so promising, for instance in mechanical [22] and civil engineering [23], among others. In these cases, using an AI-based technique such as artificial neural network (ANN) [24] or support vector regression (SVR) [25] has shown better results.…”

Section: Contributionsmentioning

confidence: 99%

Artificial neural network modelling and optimization of elastic and an-elastic spring back in polymer parts produced through ISF

Hussain

Rahman

2021

Int J Adv Manuf Technol

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Traditional polymer processing techniques results in thermal degradation of the desired mechanical properties of a component. Incremental sheet forming (ISF), an innovative flexible cold forming process, can avoid this issue. However, this type of cold processing suffers from serious drawback of spring back due to elastic recovery. Therefore, process control is mandatory to achieve the desired part accuracy. This requires employment of a conducive set of process parameters, thereby turning this into an optimization problem. Using statistical techniques, though beneficial, does not result in an acceptable mean squared error (MSE). In this paper, we explore the use of machine learning methods for error prediction and parameter optimization. Particularly, we propose to use the combination of genetic algorithm and artificial neural network hybrid model for optimized set of parameters that result in a greedy minimized shape error. Experiments on Polypropylene sheet show that the proposed approach results in better optimization compared to statistical technique in minimizing the MSE.

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“…5 As far as the welding of metals is concerned, friction stir welding (FSW) is receiving more and more interest owing to the energy efficiency, environmental friendliness and versatility that make this process a promisingly ecologic and 'green' technology. [6][7][8][9][10] It is thought that FSW consumes less energy as compared with fusion welding technologies due to the lower temperatures involved and the solid-state nature of the process. [11][12][13][14][15] Heurtier et al found that the heat inputs for gas metal arc welding (GMAW) and gas tungsten arc welding (GTAW) are 2 and 1.5 times higher than that for FSW, respectively.…”

Section: Introductionmentioning

confidence: 99%

Comparison among the environmental impact of solid state and fusion welding processes in joining an aluminium alloy

Ciarapica

Forcellese

Simoncini

2019

Proceedings of the Institution of Mechanical Engineers, Part B:

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The life-cycle assessment methodology was used to evaluate the environmental impact of friction stir welding of AA5754-H114 aluminium alloy sheets. Other works in literature considered the environmental impact of friction stir welding, but in this study the influence of different process parameters on midpoint category impacts were analysed. Friction stir welding was performed under different values of rotational and welding speeds. Moreover, pin tool wear and mechanical properties of joints were also evaluated. The pre- and post-processing stages were also considered. Raw materials, energy and all inputs associated with each stage of product life cycle were collected and evaluated to analyse the environmental impact index. The results showed that, irrespective of the rotational speed, the lowest welding speed investigated leads to the highest energy consumption and, consequently, to the highest values of the midpoint category impact. On the contrary, at the highest welding speed, the environmental impact assumes the lowest values. By concerning the rotational speed, its effect on the midpoint category impact is strongly reduced compared with the one given by the welding speed. A performance index, obtained by considering both the midpoint category impact and ultimate tensile strength of the joints, was also defined. Finally, the environmental sustainability of friction stir welding was compared with two different fusion welding technologies, namely gas tungsten arc welding and laser beam welding. The results showed that friction stir welding was characterized by midpoint category impacts much lower than those of the gas tungsten arc welding, while such discrepancies decreased with the laser beam welding.

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Trade-off among mechanical properties and energy consumption in multi-pass friction stir processing of Al7075 alloy employing neural network–based genetic optimization

Cited by 18 publications

References 32 publications

Investigations into the mechanical, morphological and thermal analyses of friction stir processing of high-density polyethylene composites

Investigations into the mechanical, morphological and thermal analyses of friction stir processing of high-density polyethylene composites

Artificial neural network modelling and optimization of elastic and an-elastic spring back in polymer parts produced through ISF

Comparison among the environmental impact of solid state and fusion welding processes in joining an aluminium alloy

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