The objective of this work is to identify failure modes and detect the onset of process anomalies in additive manufacturing (AM) processes, specifically focusing on fused filament fabrication (FFF). We accomplish this objective using advanced Bayesian nonparametric analysis of in situ heterogeneous sensor data. Experiments are conducted on a desktop FFF machine instrumented with a heterogeneous sensor array including thermocouples, accelerometers, an infrared (IR) temperature sensor, and a real-time miniature video borescope. FFF process failures are detected online using the nonparametric Bayesian Dirichlet process (DP) mixture model and evidence theory (ET) based on the experimentally acquired sensor data. This sensor data-driven defect detection approach facilitates real-time identification and correction of FFF process drifts with an accuracy and precision approaching 85% (average F-score). In comparison, the F-score from existing approaches, such as probabilistic neural networks (PNN), naïve Bayesian clustering, support vector machines (SVM), and quadratic discriminant analysis (QDA), was in the range of 55–75%.

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The objective of this study is to manufacture composite filaments to be used in three-dimensional (3D) printing of fabrics using fused deposition modeling (FDM) method. The primary properties of a fabric are flexibility and strength which are lacking in the available 3D printed materials. Polylactic acid (PLA), thermoplastic polyurethane (TPU) and poly(ethylene) glycol (PEG) were blended in different proportions and extruded using twin-screw extruder to obtain composite filaments. The properties of the filaments were studied using various material characterization methods such as uniaxial tensile test, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscope (SEM). With the addition of PEG in the PLA/TPU composition, it was found that the yield stress and Young’s modulus of the composite filaments have significantly decreased compared to that of pure PLA filament. It was also noted that there was no significant difference in ultimate tensile strength whereas the elongation at break was increased by more than 500%. Using the composite filament, a plain weave fabric structure was 3D printed to investigate the printing ability of a complex structure. It is concluded that the composite filaments developed are suitable for 3D printing but non-uniformity in diameter affects the print quality and hence the overall properties of fabrics.

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