Abstract
A majority of automobile wheel market is occupied by aluminium alloys because of numerous advantages, one of which includes light weight. Most of these Aluminium alloy wheels are cast using Low Pressure Die Casting process. However this process results in several defects in the wheel rims, majority of which are due to shrinkage porosity. The presence of such defects reduce the fatigue life of wheels as they act as high-stress zones. Hence, it is paramount to understand the possible defects with their location and intensity and minimize it. One possible way is to perform a multi-physics simulation of filling and solidification process and estimate the defect location and intensity. However minimizing these defects, calls for a highly non-linear space Multi-disciplinary Design Optimization (MDO) problem. Existing techniques such as full factorial analysis may not be computationally efficient when it comes to contribution from large number of parameters. Shrinkage porosity is affected by various process parameters like cooling channels flow rate, delay and duration of flow, mold pre-heat temperatures, pressure cycle of molten metal, alloy composition, etc. The current research focuses on development of an efficient approach to solve a MDO problem in LPDC process of AlSi7Mg0.3 alloy wheel rim. The work specifically deals with minimizing the shrinkage porosity by optimizing the cooling channel parameters like delay and duration. This can also be extended for other parameters like flow rates, pre-heat temperatures, pressure cycle, etc.
Published Version
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