Abstract
Although many major foundries use software, such as ProCAST TM and MagmaSOFT TM , to simulate filling and solidification of castings for process design, a number of the required input parameters (such as material properties and boundary conditions) are not well known. This has motivated the need for an optimization tool that uses an inverse modeling approach to determine these parameters, given appropriate experimental measurements. This article describes optimization strategies that have been used to tune computational models to plant conditions. These models are then used in a second phase of optimization that improves the operation of the casting plant thereby playing a major role in reducing costs and improving productivity and quality of cast products.