Multi-Response Optimization of Mechanical Properties and Quantitative Porosity of A356 Aluminum Alloy Subjected to T6 Heat Treatment Using Response Surface Methodology

Abstract

This study addresses key methodological gaps in prior T6 heat-treatment research on A356 aluminum alloy, namely the ambiguity of treatment-temperature definitions, reliance on perceived (non-quantitative) porosity assessment, incomplete statistical testing across mechanical responses, and the use of single-factor discrete temperature screening instead of a continuous optimization design. A two-factor Central Composite Design (aging temperature 162-183 °C; aging time 2.3-13.7 h) following a fixed solution treatment (540 °C/6 h, water quench) was employed, comprising 13 experimental runs. Responses (tensile strength, hardness, elongation, and quantitative porosity via image analysis and Archimedes density) were modeled using Response Surface Methodology (RSM) and optimized jointly through a composite desirability function. Quadratic regression models were statistically significant (p < 0.001) for all responses. The optimum condition was identified at an aging temperature of 173.2 °C for 7.8 h, yielding a predicted tensile strength of 283.1 MPa, hardness of 93.2 HB, elongation of 10.0%, and porosity as low as 3.1%, confirmed experimentally within 4% deviation. Secondary Dendrite Arm Spacing (SDAS) was quantitatively correlated with both tensile strength and hardness (R² > 0.85). The findings extend existing T6 optimization literature by providing a validated, continuous, multi-response optimization framework with quantitative defect characterization for A356 components.