Acrylonitrile Butadiene Styrene (ABS) nanocomposites were developed using Material Extrusion (MEX) Additive Manufacturing (AM) and Fused Filament Fabrication (FFF) methods. A range of mechanical tests was conducted on the produced 3D-printed structures to investigate the effect of Titanium Nitride (TiN) nanoparticles on the mechanical response of thermoplastic polymers. Detailed morphological characterization of the produced filaments and 3D-printed specimens was carried out using Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM). High-magnification images revealed a direct impact of the TiN concentration on the surface characteristics of the nanocomposites, indicating a strong correlation with their mechanical performance. The chemical compositions of the raw and nanocomposite materials were thoroughly investigated by conducting Raman and Energy Dispersive Spectroscopy (EDS) measurements. Most of the mechanical properties were improved with the inclusion of TiN nanoparticles with a content of 6 wt. % to reach the optimum mechanical response overall. ABS/TiN 6 wt. % exhibits remarkable increases in flexural modulus of elasticity (42.3%) and toughness (54.0%) in comparison with pure ABS. The development of ABS/TiN nanocomposites with reinforced mechanical properties is a successful example that validates the feasibility and powerful abilities of MEX 3D printing in AM.
Challenging issues arise in the design of control strategies for piezoelectric smart structures. Piezoelectric materials have been investigated for use in distributed parameter systems in order to provide active control efficiently and affordably. In the active control of dynamic systems, distributed sensors and actuators can be created using piezoelectric materials. The three fundamental issues that structural control engineers must face when creating robust control laws are structural modeling methodologies, uncertainty modeling, and robustness validation. These issues are reviewed in this article. A smart structure with piezoelectric (PZT) materials is investigated for its active vibration response under dynamic disturbance. Numerical modeling with finite elements is used to achieve that. The vibration for different model values is presented considering the uncertainty of the modeling. A vibration suppression was achieved with a robust controller and with a reduced order controller. Results are presented for the frequency domain and the state space domain. This work cleary demostrated the advantage of robust control in the vibration suppration of smart stuctures.
Process sustainability vs. mechanical strength is a strong market-driven claim in Material Extrusion (MEX) Additive Manufacturing (AM). Especially for the most popular polymer, Polylactic Acid (PLA), the concurrent achievement of these opposing goals may become a puzzle, especially since MEX 3D-printing offers a variety of process parameters. Herein, multi-objective optimization of material deployment, 3D printing flexural response, and energy consumption in MEX AM with PLA is introduced. To evaluate the impact of the most important generic and device-independent control parameters on these responses, the Robust Design theory was employed. Raster Deposition Angle (RDA), Layer Thickness (LT), Infill Density (ID), Nozzle Temperature (NT), Bed Temperature (BT), and Printing Speed (PS) were selected to compile a five-level orthogonal array. A total of 25 experimental runs with five specimen replicas each accumulated 135 experiments. Analysis of variances and reduced quadratic regression models (RQRM) were used to decompose the impact of each parameter on the responses. The ID, RDA, and LT were ranked first in impact on printing time, material weight, flexural strength, and energy consumption, respectively. The RQRM predictive models were experimentally validated and hold significant technological merit, for the proper adjustment of process control parameters per the MEX 3D-printing case.
Acrylonitrile butadiene styrene (ABS) is a multipurpose thermoplastic and the second most popular material in material extrusion (MEX) additive manufacturing (AM). It is widely used in various types of industrial applications in the automotive sector, housing, and food processing, among others. This work investigates the effect of seven generic control parameters (orientation angle, raster deposition angle, infill density, layer thickness, nozzle temperature, printing speed, and bed temperature) on the performance and the energy consumption of 3D-printed ABS parts in compression loading. Raw material with melt extrusion was formed in a filament form for MEX 3D printing. Samples after the ASTM D695-02a standard were 3D printed, with the seven control parameters, three levels, and five replicas each (135 experiments in total). Results were analyzed with statistical modeling tools regarding the compressive and the energy consumption metrics (printing time, weight, energy printing consumption/EPC, specific printing energy/SPE, specific printing power/SPP, compression strength, compression modulus of elasticity, and toughness). The layer thickness was the most critical control parameter. Nozzle temperature and raster deposition angle were the less critical parameters. This work provides reliable information with great technological and industrial impact.
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