Parametric Optimization of Fused Deposition Modeling using Response Surface MEthodology

Abstract

Fused deposition modeling (FDM) is a process for developing rapid prototype (RP) objects by depositing fused layers of material according to numerically defined cross sectional geometry. The quality of FDM produced parts is significantly affected by various parameters used in the process. This dissertation work aims to study the effect of five process parameters such as layer thickness, sample orientation, raster angle, raster width, and air gap on mechanical property of FDM processed parts. In order to reduce experimental runs, response surface methodology (RSM) based on central composite design is adopted. Specimens are prepared for tensile, flexural, and impact test as per ASTM standards. Empirical relations among responses and process parameters are determined and their validity is proved using analysis of variance (ANOVA) and the normal probability plot of residuals. Response surface plots are analyzed to establish main factor effects and their interaction on responses. Optimal factor settings for maximization of each response have been determined. Major reason for weak strength of FDM processed parts may be attributed to distortion within the layer or between the layers while building the parts due to temperature gradient. Since RP parts are subjected to different loading conditions, practical implication suggests that more than one response must be optimized simultaneously. To this end, mechanical properties like tensile strength, bending strength, and impact strength of the produced component are considered as multiple responses and simultaneous optimization has been carried out with the help of response optimizer. Grey relation has been employed to convert multiple responses into a single response for optimization purpose. It is interesting to note that factor level settings for simultaneous optimization of all responses significantly differ from optimization with single response.