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

Abstract

Abstract 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 the multiple quality attributes of the castings at every experimental trials, (2) calculate the comprehensive quality score (CQS) values of the experimental trials using some MADM methods, (3) calculate the final CQS (FCQS) values of the experimental trials by integrating the CQS values from some MADM methods (Integrated MADM method), (4) calculate the mean FCQS values of the casting process parameters at the different levels, (5) calculate the 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. The proposed methodology is applied to optimize the casting process parameters and assess their influences for A356 aluminum alloy sand casting to illustrate its effectiveness. The methodology could be widely used to many practical casting process optimization problems.