OPTIMIZATION OF PROCESS PARAMETERS IN FUSED DEPOSITION MODELING USING WEIGHTED PRINCIPAL COMPONENT ANALYSIS

Abstract

Fused deposition modeling (FDM) is a process by which functional parts can be produced rapidly through deposition of fused layers of material according to a numerically defined cross-sectional geometry. Literature suggests that process parameters largely influence on quality characteristics of rapid prototyping (RP) parts. A functional part is subjected to different loading conditions in actual practice. Therefore, process parameters need to be determined in such a way that they collectively optimize more than one response simultaneously. To address this issue, effect of important process parameters viz., layer thickness, orientation, raster angle, raster width, and air gap have been studied. The responses considered in this study are mechanical property of FDM produced parts such as tensile, bending and impact strength. The multiple responses are converted into a single response using principal component analysis (PCA) so that influence of correlation among the responses can be eliminated. Resulting single response is nothing but the weighted sum of three principal components that explain almost hundred percent of variation. The experiments have been conducted in accordance with Taguchi's orthogonal array to reduce the experimental runs. The results indicate that all the factors such as layer thickness, orientation, raster angle, raster width and air gap and interaction between layer thickness and orientation significantly influence the response. Optimum parameter settings have been identified to simultaneously optimize three responses. The mechanism of failure is explained with the help of SEM micrographs.