Optimizing the rapid prototyping process by integrating the Taguchi method with the Gray relational analysis

Purpose - The following research seeks to focus on optimizing the fused deposition modeling (FDM) process of RP systems. Design/methodology/approach - Early stages of this study are based on the Taguchi method in establishing rapid prototyping building factors and their various levels. The ultimate tensile strength, dimension accuracy and surface roughness (SR), are analyzed. Through analysis of variance (ANOVA) and contribution approximation, significant building factors of each quality characteristic and optimal factors level combinations of each best quality characteristic are obtained. The main steps are setting the weight for each quality characteristic of the previous Taguchi method, obtaining the estimated multiple building quality characteristics through integrating the Gray theory, and obtaining a set of optimal building factors. Finally, the result is verified by the Gray theory and the technique for order preference by similarity to ideal solution (TOPSIS) evaluation method. Findings - It is proven that optimal multiple quality characteristic combinations of building factors can be obtained by integrating the Gray theory and the Taguchi method. The result is further verified by the TOPSIS evaluation method, showing that the model can acquire multiple building quality characteristics of rapid prototyping. Research limitations/implications - The method is only applied to FDM in this paper but a similar approach could be applied to other RP systems. Practical implications - RP system use is limited by low product strength, bad SR, and the high dimension errors. This research demonstrates how optimizing the FDM process can improve this situation. Originality/value - The originality of this paper lies in optimizing the rapid prototyping process by integrating the Taguchi method with the Gray relational analysis.