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Evaluation of surface quality and mechanical properties of squeeze casted AA2026 aluminum alloy using response surface methodology.
- Source :
-
International Journal of Advanced Manufacturing Technology . Aug2019, Vol. 103 Issue 9-12, p4041-4054. 14p. 4 Diagrams, 7 Charts, 6 Graphs. - Publication Year :
- 2019
-
Abstract
- Aluminum–copper alloys are widely employed in automobile and aerospace industries owing to their marvelous mechanical and physical attributes. But the major hindrance in their application is that these materials are more susceptible to casting defects such as porosity, hot tears, and shrinkage occurring during solidification. The said issues have a negative impact on the mechanical properties of the casted materials and thus limit their use. Squeeze casting is a promising choice for these materials that has an ability to manufacture near-net shape parts with superior surface finish and better mechanical properties. Although, the potential of this method is tested for a variety of materials, but its capability for casting AA2026 alloy is yet to be comprehensively explored which is the primary focus of this research. Three key parameters of squeeze casting process, namely squeeze pressure, die temperature, and pouring temperature are selected for investigating their influence on surface roughness, ultimate tensile strength, and hardness using response surface methodology. Experimental results are analyzed using analysis of variance to find the control factor's significance and adequacy of models. It has been found that squeeze pressure is the most influencing parameter for surface roughness whereas for ultimate tensile strength and hardness, pouring temperature is the major contributing factor. SEM analysis is carried out to reveal the micro-details of the fractured samples. In addition to finding optimal ranges of control variables (using contour plot analysis) for each response individually, a multi-response optimization has also been carried out using desirability approach. Furthermore, mathematical models are also developed and validated through confirmatory tests. The results of confirmatory runs depict that the proposed models have a high degree of prediction accuracy. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02683768
- Volume :
- 103
- Issue :
- 9-12
- Database :
- Academic Search Index
- Journal :
- International Journal of Advanced Manufacturing Technology
- Publication Type :
- Academic Journal
- Accession number :
- 137794893
- Full Text :
- https://doi.org/10.1007/s00170-019-03836-6