Multi-response optimization of hot extrusion process parameters using FEM and Grey relation based Taguchi method

Jajimoggala, Sarojini; Dhananjay, Routhu; Lakshmi, V. V. K.; Shabana,

doi:10.1016/j.matpr.2019.06.316

Cited by 11 publications

(5 citation statements)

References 17 publications

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“…In general, the results obtained in this paper are consistent with experimental findings and previous numerical studies reported in the literature [19,[42][43][44][45]. Furthermore, experimental studies are planned to validate this numerical approach and provide better insight into the process.…”

Section: Discussionsupporting

confidence: 89%

Selection of Die Material and Its Impact on the Multi-Material Extrusion of Bimetallic AZ31B–Ti6Al4V Components for Aeronautical Applications

2021

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This paper investigates the effect that the selection of the die material generates on the extrusion process of bimetallic cylindrical billets combining a magnesium alloy core (AZ31B) and a titanium alloy sleeve (Ti6Al4V) of interest in aeronautical applications. A robust finite element model is developed to analyze the variation in the extrusion force, damage distribution, and wear using different die materials. The results show that die material is a key factor to be taken into account in multi-material extrusion processes. The die material selection can cause variations in the extrusion force from 8% up to 15%, changing the effect of the extrusion parameters, for example, optimum die semi-angle. Damage distribution in the extrudate is also affected by die material, mainly in the core. Lastly, die wear is the most affected parameter due to the different hardness of the materials, as well as due to the variations in the normal pressure and sliding velocity, finding critical values in the friction coefficient for which the die cannot be used for more than one forming stage because of the heavy wear suffered. These results can potentially be used to improve the efficiency of this kind of extrusion process and the quality of the extruded part that, along with the use of lightweight materials, can contribute to sustainable production approaches.

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Section: Discussionsupporting

confidence: 89%

Selection of Die Material and Its Impact on the Multi-Material Extrusion of Bimetallic AZ31B–Ti6Al4V Components for Aeronautical Applications

2021

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“…The statistical significance of the process parameters was carried out through Analysis of Variance (ANOVA). The degree of significance of die angle was found to be highest followed by ram speed and coefficient of friction [8] . The investigation on sensitivity analysis of die structural and process parameters in porthole die extrusion of magnesium alloy tube was carried out using the Taguchi method.…”

Section: Data Descriptionmentioning

confidence: 89%

Dataset for deformation behavior of pure titanium grade 2 materials during continuous extrusion

et al. 2022

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“…Despite the level of successes recorded with the utilization of the Taguchi optimization method, it still exhibits the inherent limitation of single response optimization associated with every other DOE method. In order to circumvent this drawback when confronted with multiple response problems, the Taguchi method is usually integrated into some numerical and analytical techniques to achieve multiple response optimization [39][40][41][42][43][44][45][46]. However, most of the developed numerical and analytical techniques for Taguchi multiple response optimization present modest results due to their inherent shortcomings [47], which poses a huge setback to the wide acceptance of the Taguchi optimization method.…”

Section: Taguchi Optimization Methodsmentioning

confidence: 99%

Variable returns to scale DEA—Taguchi approach for ternary additives optimization in expansive soil subgrade enhancement

Ikeagwuani

Nwonu

2021

Geo-Engineering

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In this study, variable returns to scale (VRS) data envelopment analysis was integrated into the Taguchi approach to optimize ternary additives for expansive soil enhancement. The ternary additives selected were sawdust ash (SDA), quarry dust (QD) and ordinary Portland cement (OPC). The additives were set as the input variables while multiple responses obtained from the experiments performed with the Taguchi orthogonal array were set as the output variables. Each row in the orthogonal array were defined as a decision making unit (DMU) in the optimization process and output-oriented VRS model was used to obtain the efficiency score for each DMU. Next, benevolent formulation was utilized to obtain the multipliers for the inputs and outputs which were subsequently used to determine the cross efficiency scores for each DMU. The cross-efficiency scores were used to construct the cross-efficiency matrix. Thereafter, the mean cross-efficiency score (MCES) was determined for each DMU. Parameter level that maximizes the MCES was chosen as the optimal level for that parameter. Optimum combination of additives was found at A6 B2 C3. Lastly, confirmatory experiments performed by blending the soil with the optimum combination of additives showed the effectiveness of this method in the enhancement of expansive soil properties.

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Multi-response optimization of hot extrusion process parameters using FEM and Grey relation based Taguchi method

Cited by 11 publications

References 17 publications

Selection of Die Material and Its Impact on the Multi-Material Extrusion of Bimetallic AZ31B–Ti6Al4V Components for Aeronautical Applications

Selection of Die Material and Its Impact on the Multi-Material Extrusion of Bimetallic AZ31B–Ti6Al4V Components for Aeronautical Applications

Dataset for deformation behavior of pure titanium grade 2 materials during continuous extrusion

Variable returns to scale DEA—Taguchi approach for ternary additives optimization in expansive soil subgrade enhancement

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