Abstract
Among many Additive Manufacturing (AM) technique, extrusion base AM technique is very popular. Though AM techniques have lot of advantages, Fused Filament Fabrication (FFF) falls shorts in strength criteria due to anisotropic behavior. In order to understand the behavior process parameters like liquefier temperature, raster angle and layer height are considered to study their effect on tensile strength. For experimental purpose, specimens are manufactured and are tested as per ASTM D638. For the experimental design purpose, Taguchi design of experiment methodology is considered in the present study. In order to predict the tensile strength as a function of FFF process parameters an adaptive neuro-fuzzy interface system (ANFIS) has been developed. A model has been designed that has the learning abilities of an artificial neural network and fuzzy interface. From the experimental data the a set of rules have been generated and are then tested for its validity. From the ANFIS system, the results show that higher tensile strength is obtained at higher liquefier temperature, lower raster angle and higher layer height. ANFIS prediction values shows greater agreement with experimental results with mean error ∼ 2%.
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