Strain hardening analysis and modelling for sintered Al-Cu-TiC preforms with varying process parameters during cold upsetting

Jeevanantham, A.K.; Seenivasagam, Devi Rengamani; Ananthanarayanan, Rajeshkannan

doi:10.1016/j.jmrt.2020.08.065

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…While these primary processes play a crucial role in shaping the mechanical performance of the produced preforms, there is a notable oversight in addressing secondary operations in PM. Secondary operations, including cold or hot working of PM materials through forging, rolling, and extrusion, have the potential to further enhance mechanical properties, such as improving workability characteristics in secondary forming operations (e.g., stress formability index (β), strain hardening exponent (n), and strength coefficient (K)) [67][68][69][70]. The optimization of these response parameters is instrumental in establishing the working limits of PM materials.…”

Section: Discussionmentioning

confidence: 99%

Optimization methods in powder metallurgy for enhancing the mechanical properties: a systematic literature review

Lingam,

Ananthanarayanan,

Jeevanantham

et al. 2024

Eng. Res. Express

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Powder metallurgy offers several advantages over traditional manufacturing methods, such as improved material utilization and waste reduction. The powder metallurgy process involves four primary steps, metal powder preparation, mixing, compaction, and sintering, followed by secondary operations such as forging, rolling, and extrusion. However, existing studies have predominantly focused on refining the primary processes, neglecting secondary processes that could further enhance mechanical properties. A systematic literature review following the Preferred Reporting Items for Systematic Review and Meta-Analysis method identified twenty-three relevant articles over a ten-year period, highlighting three main optimization methods, that are, the Taguchi method, Taguchi-based Grey Relational Analysis, and Response Surface Methodology. These methods effectively reduce experimental trials and optimize key parameters like compaction pressure and weight percentage, which significantly influence mechanical properties. The review emphasizes the key powder metallurgy process parameters that have a significant impact on mechanical properties, becoming the primary targets for optimization. It offers a focused examination of which process parameters require thorough investigation for optimization and the suitable optimization method to achieve optimal outcomes, whether for single or multiple responses, thereby enhancing the manufacturing process. However, inconsistencies in parameter significance across studies indicate the material-dependent nature of powder metallurgy materials. The review also identifies a gap in the literature regarding secondary process optimization and comparative analyses of optimization methods. Future research should explore optimizing secondary processes in powder metallurgy, conduct comparative studies of different optimization methods, and develop novel approaches for optimization to further enhance mechanical properties and process efficiency.

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Section: Discussionmentioning

confidence: 99%

Optimization methods in powder metallurgy for enhancing the mechanical properties: a systematic literature review

Lingam,

Ananthanarayanan,

Jeevanantham

et al. 2024

Eng. Res. Express

Self Cite

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“…A graphite stirrer is used to mix the matrix and reinforcements by rotating the stirrer with rpm of 500-600 rpm [17]. Due to the vortex flow of the matrix, reinforcements are mixed uniformly which avoids any air pockets from being trapping which forms voids and pores after cooling [18]. The optimum combination of matrix and reinforcement decides the wear rate which can be examined using an optical microscope for achieving negligible pores, voids in the composite [17].…”

Section: Introductionmentioning

confidence: 99%

Dry Sliding Friction and Wear Behavior of LM13/Zircon/Carbon (HMMC’s): An Experimental, Statistical and Artificial Neural Network Approach

Ravitej¹,

Mohan²,

Ananthaprasad³

2022

Tribol. Ind.

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Dual reinforcement in composite materials leads to the betterment of properties. In the present research, zircon is added from a range of 0 wt. % to 12 wt. % in the steps of 3 wt. % by maintaining constant 3 wt. % graphite powder in addition to the aluminum alloy (LM13) matrix. Reinforcements are preheated at 250°C to remove moisture content and are dispersed in the molten aluminum alloy (LM13) by stir casting process where copper chills are kept at one end of the mold to enable unidirectional solidification. Wear properties are evaluated using pin on disc experiment. Design of the experiment (DOE) is done using Taguchi's (L25) orthogonal array to assess the effect of (a) applied load (b) sliding speed (c) track radius/sliding distance (d) zircon content on wear loss/volume loss, coefficient of friction (COF)and wear rate. It is observed that wear rate and wear loss are proportional to the applied load, sliding speed and track radius COF is inversely proportional to the same. Wear rate decreases with the addition of zircon up to 9 wt. % and then increases at 12 wt. %. Statistical analysis is done using Minitab software where SN ratio, probability, ANOVA, and a regression model are analyzed. Obtained experimental wear properties are validated using artificial neural networks (ANN) by training the neurons where good agreement is obtained (R 2 = 0.98). Present research encapsulates the effect of different wear parameters like applied load, sliding speed, and sliding distance on the wear rate of LM13/zircon/C (hybrid metal matrix composites), and experimental wear results are correlated with artificial neural network (ANN) by training the algorithm.

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Numerical and experimental investigations of built orientation dependent Johnson–Cook model for selective laser melting manufactured AlSi10Mg

Aktürk

Boy

Gupta

et al. 2021

Journal of Materials Research and Technology

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Strain hardening analysis and modelling for sintered Al-Cu-TiC preforms with varying process parameters during cold upsetting

Cited by 4 publications

References 19 publications

Optimization methods in powder metallurgy for enhancing the mechanical properties: a systematic literature review

Optimization methods in powder metallurgy for enhancing the mechanical properties: a systematic literature review

Dry Sliding Friction and Wear Behavior of LM13/Zircon/Carbon (HMMC’s): An Experimental, Statistical and Artificial Neural Network Approach

Numerical and experimental investigations of built orientation dependent Johnson–Cook model for selective laser melting manufactured AlSi10Mg

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