Modeling and experimental validation of part-level thermal profile in fused filament fabrication

Part design and process parameters directly influence thespatiotemporal distribution of temperature and associated heattransfer in parts made using additive manufacturing (AM)processes. The temporal evolution of temperature in AM parts istermed herein as thermal profile or thermal history. The thermalprofile of the part, in turn, governs the formation of defects, suchas porosity and shape distortion. Accordingly, the goal of thiswork is to understand the effect of the process parameters andthe geometry on the thermal profile in AM parts. As a steptowards this goal, the objectives of this work are two-fold: (1) todevelop and apply a finite element-based framework thatcaptures the transient thermal phenomena in the fused filamentfabrication (FFF) additive manufacturing of acrylonitrilebutadiene styrene (ABS) parts, and (2) validate the modelderived thermal profiles with experimental in-processmeasurements of the temperature trends obtained under differentfeed rate settings (viz., the translation velocity, also called scanspeed or deposition speed, of the extruder on the FFF machine).In the specific context of FFF, this foray is the critical first-steptowards understanding how and why the thermal profile directlyaffects the degree of bonding between adjacent roads (lineartrack of deposited material), which in turn determines thestrength of the part, as well as, propensity to form defects, suchas delamination. From the experimental validation perspective,we instrumented a Hyrel Hydra FFF machine with three noncontact infrared temperature sensors (thermocouples) locatednear the nozzle (extruder) of the machine. These sensors measurethe surface temperature of a road as it is deposited. Test parts are printed under three different settings of feed rate, andsubsequently, the temperature profiles acquired from the infraredthermocouples are juxtaposed against the model-derivedtemperature profiles. Comparison of the experimental andmodel-derived thermal profiles confirms a high-degree ofcorrelation therein, with maximum absolute error less than 10%.This work thus presents one of the first efforts in validation ofthermal profiles in FFF via in-process sensing. In our futurework, we will focus on predicting defects, such as delaminationand inter-road porosity based on the thermal profile.