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In this work, the expansion of friction stir welding (FSW) in parts made via material extrusion (MEX) 3D printing was investigated. Poly(methyl methacrylate) (PMMA) plates were joined in a full factorial experimental design. The effects of three FSW parameters (weld tool pin geometry, rotating speed, and travel speed) on the weld results were studied. The tensile strength was investigated using statistical modeling tools. A morphological characterization study was also conducted on the weld zone, with microscopy. The state of the material during the FSW process was monitored via real-time temperature measurements. The feasibility of the process was verified. The results show high industrial merit for the process. The highest tensile strength was reported for the sample welded with the frustum tool, at 1400 rpm and a 9 mm/min travel speed (the highest studied), with a welding efficiency > 1. This can be attributed to the reduced porosity of the weld area compared to the 3D printed structure, and indicates a high potential for joining 3D-printed PMMA sheets via the FSW process. [ABSTRACT FROM AUTHOR]

In this work, material extrusion (MEX) 3D-printed polylactic acid (PLA) thin workpieces were joined via the friction stir welding (FSW) process to evaluate the feasibility and the key features of the process. To ensure the reliability of the process, a special fixture was designed and manufactured. Three critical parameters were investigated, i.e., the welding tool geometry, the travel speed, and the tool rotational speed. Two different tool geometries were manufactured and tested. Specimens were welded with various welding parameters values, to calibrate the experimental ranges of the subsequent full factorial course. The results were recorded and evaluated with an optical microscope, a stereoscope, and scanning electron microscopy (SEM). The thermal field and the mechanical performance of the joints were measured and evaluated. In the majority of the welding scenarios, the welded specimens' mechanical performance was increased compared to the identical not welded 3D-printed samples. The travel speed proved to be the most critical parameter affecting the mechanical strength of the parts. The highest tensile strength is reported for a specimen welded with 6 mm/min travel speed, 1400 rpm rotational speed, and weld tool with the cylindrical pin. The results were analyzed and optimized with statistical modeling tools, to evaluate and document the impact of each parameter studied herein. Herewith, a cost-effective and efficient FSW joining process of MEX-made polymeric pieces enables a new possibility to permanently assemble 3D-printed parts of limited size to larger assemblies, with the aid of simple tools and a milling machine. [ABSTRACT FROM AUTHOR]

This study investigates the mechanical response of antibacterial PA12/TiO2 nanocomposite 3D printed specimens by varying the TiO2 loading in the filament, raster deposition angle, and nozzle temperature. The prediction of the antibacterial and mechanical performance of such nanocomposites is a challenging field, especially nowadays with the covid-19 pandemic dilemma. The experimental work in this study utilizes a fully factorial design approach to analyze the effect of three parameters on the mechanical response of 3D printed components. Therefore, all combinations of these three parameters were tested, resulting in twenty-seven independent experiments, in which each combination was repeated three times (a total of eighty-one experiments). The antibacterial performance of the fabricated PA12/TiO2 nanocomposite materials was confirmed, and regression and arithmetic artificial neural network (ANN) models were developed and validated for mechanical response prediction. The analysis of the results showed that an increase in the TiO2% loading decreased the mechanical responses but increased the antibacterial performance of the nanocomposites. In addition, higher nozzle temperatures and zero deposition angles optimize the mechanical performance of all TiO2% nanocomposites. Independent experiments evaluated the proposed models with mean absolute percentage errors (MAPE) similar to the ANN models. These findings and the interaction charts show a strong interaction between the studied parameters. Therefore, the authors propose the improvement of predictions by utilizing artificial neural network models and genetic algorithms as future work and the spreading of the experimental area with extra variable parameters and levels. [ABSTRACT FROM AUTHOR]

3D printing (3DP) of polymers using fused filament fabrication (FFF) is not yet massively adopted in industrial environments due to shape accuracy and surface integrity limitations. However, the FFF process combined with laser processing (hybrid manufacturing) or other precision machining processes is under investigation nowadays and is a promising combination for high quality 3DP final parts. This work investigates the effects on the dimensional accuracy and the surface roughness of process parameters, during low power CO2 laser cutting (LC) of thin acrylonitrile butadiene styrene (ABS) plates manufactured with the FFF process. Even though LC is highly flexible and the quality of the machined surfaces is versatile, certain problems are associated with LC, such as the kerf angle formation and the surface texture quality, which need optimization in respect to the LC parameters. The full factorial design methodology is adopted, having four parameters as input, i.e., stand-off distance (SoD), raster deposition angle (RDA), laser speed (LS), and laser power (LP), and kerf geometry characteristics as output, i.e., kerf widths (upper, middle, and down; Wu, Wm, and Wd), kerf angle (KA), and average and max height surface roughness (Ra and Rt). The statistical analysis is used to investigate the relations between the input and the output parameters. Seventy-two independent experiments were utilized. The analysis of variances (ANOVA), the interaction study, and the quadratic regression models (QRM) were adapted to fit the input with the output parameters, optimize the process KA close to 0°, and minimize the Ra close to 0 μm. The optimum parameter values (7.5 mm SoD, zero RDA, 14.4 mm/s LS, and 105 W LP) are validated by seven independent experiments, which show that only the Wu and Ra predicted values are close to the actual values following the ANOVA analysis and the mean average percengtage error (MAPE) index. [ABSTRACT FROM AUTHOR]

• Comparison of Taguchi Experimental Design and full factorial design. • Machinability performance in turning of difficult-to-cut material (Ti6Al4V ELI alloy). • Application of statistical methods to characterize the machinability performance. • Taguchi Design does not always give the same results as full factorial design. This study investigates the machinability performance during dry longitudinal turning of Ti-6Al-4V-ELI titanium alloy using Taguchi Experimental Design (TED) and full factorial design (FFD). Main cutting force (Fc) and mean surface roughness (Ra) are selected as the output machinability parameters. Spindle speed (n), feed rate (s) and depth of cut (a) are the independent input cutting variables, each one having three different levels. A complete combination array of 27 (33) experiments was realized and the machinability performance is recorded. Then, the "full 27-array" is divided in three sub-arrays, each one having the "orthogonality property-OP" according to Taguchi L 9 array. The performance of each sub-array is analyzed using both stem-and-leaf and box plots, as well as analysis of means (ANOM) and analysis of variance (ANOVA) and is compared with the FFD one. Data analysis (DA) during present study indicates that Taguchi design is appropriate for analyzing machinability issues of "difficult-to-cut" materials. [ABSTRACT FROM AUTHOR]