Enhancing the quality of AZ31/10% SiC composite: optimization of ultrasonic squeeze casting parameters for enhanced hardness and structural integrity.
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| Title: | Enhancing the quality of AZ31/10% SiC composite: optimization of ultrasonic squeeze casting parameters for enhanced hardness and structural integrity. |
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| Authors: | Edlabadkar, Ajinkya P.1 (AUTHOR) ajinkyae@gmail.com, Packkirisamy, Vignesh2 (AUTHOR), Laxmaiah, Gundagani3 (AUTHOR), Kumar, Annam Sunny4 (AUTHOR), Subashini, Kasivisvanathan5 (AUTHOR) |
| Source: | Metallurgical Research & Technology. 2025, Vol. 122 Issue 1, p1-13. 13p. |
| Subjects: | Squeeze casting, Multi-objective optimization, Response surfaces (Statistics), Ultrasonic waves, Analysis of variance, Aluminum composites |
| Abstract: | AZ31 alloys are gaining considerable research interest owing to their commendable applications in automobile and aerospace applications because of their high strength-to-weight ratio to reduce the overall weight of the vehicle. However, these alloys are more susceptible to porosity and material shrinkage during casting, which in turn results in poor mechanical behavior. Ultrasonic-assisted squeeze casting is a non-traditional casting technique that involves the application of ultrasonic waves to distribute the reinforced particles homogenously in the melt, improving the integrity of the alloy composites by reducing agglomeration. While various materials have demonstrated the efficacy of these processing techniques, their potential for casting AZ31/10% SiC alloy composites remains unexplored. The present work aims to investigate the impact of three major process parameters, namely ultrasonic power (UP), squeeze time (ST), and stirring speed (SS), on the responses of porosity and microhardness, using the response surface methodology (RSM) central composite design (CCD) approach. The analysis of variance (ANOVA) technique is used to determine the most significant process parameter and to check the model's adequacy. The analysis indicates that ultrasonic power has the highest F-value and is the most influential factor on porosity and microhardness. Microstructural studies reveal the composites' structural morphology. Apart from identifying the optimal individual process parameters, the desirability approach was also deployed to carry out the multi-objective optimization. Further, empirical models were developed, and confirmatory tests were performed to validate the models. The observed confirmatory results indicate that the developed models have a good prediction tendency. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | AZ31 alloys are gaining considerable research interest owing to their commendable applications in automobile and aerospace applications because of their high strength-to-weight ratio to reduce the overall weight of the vehicle. However, these alloys are more susceptible to porosity and material shrinkage during casting, which in turn results in poor mechanical behavior. Ultrasonic-assisted squeeze casting is a non-traditional casting technique that involves the application of ultrasonic waves to distribute the reinforced particles homogenously in the melt, improving the integrity of the alloy composites by reducing agglomeration. While various materials have demonstrated the efficacy of these processing techniques, their potential for casting AZ31/10% SiC alloy composites remains unexplored. The present work aims to investigate the impact of three major process parameters, namely ultrasonic power (UP), squeeze time (ST), and stirring speed (SS), on the responses of porosity and microhardness, using the response surface methodology (RSM) central composite design (CCD) approach. The analysis of variance (ANOVA) technique is used to determine the most significant process parameter and to check the model's adequacy. The analysis indicates that ultrasonic power has the highest F-value and is the most influential factor on porosity and microhardness. Microstructural studies reveal the composites' structural morphology. Apart from identifying the optimal individual process parameters, the desirability approach was also deployed to carry out the multi-objective optimization. Further, empirical models were developed, and confirmatory tests were performed to validate the models. The observed confirmatory results indicate that the developed models have a good prediction tendency. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 22713646 |
| DOI: | 10.1051/metal/2024108 |
