Multi-attribute optimization and influence assessment methodology of casting process parameters combined with integrated MADM and Taguchi method

Many practical casting process optimization problems are ascribable to multi-attribute optimization problems with multiple conflicting quality attributes. This paper proposes a reasonable multi-attribute optimization and influence assessment methodology of casting process parameters combined with integrated multi-attribute decision-making (MADM) and Taguchi method. The proposed methodology consists of the following steps: (1) design experiment arrangement based on Taguchi orthogonal array, and measure multiple quality attributes of castings at every experimental trials, (2) calculate comprehensive quality score (CQS) values of the experimental trials using some MADMs, (3) calculate final CQS (FCQS) values of the experimental trials by integrating the CQS values from some MADMs using integrated MADM, (4) calculate mean FCQS values of the casting process parameters at different levels, (5) calculate ranges of mean FCQS values and influence indices of the casting process parameters, and (6) determine optimal casting process parameters to maximize the comprehensive quality of the castings. To demonstrate its usage and effectiveness, it is applied to one illustration example to determine optimal four casting process parameters such as pouring temperature (PT), degasser amount (DA), holding time (HT) and mould type (MT) for optimizing three quality attributes such as density of casting (D), ultimate tensile strength (UTS) and elongation to fracture (Ef) of A356 Al alloy sand castings. The proposed methodology could be widely applied to not only casting process optimization but also various advanced manufacturing process optimization problems.