Taguchi Optimization of Parameters for Feedstock Fabrication and FDM Manufacturing of Wear-Resistant UHMWPE-Based Composites

Investigation of the effects of irradiation and aging on the tribological behavior of ultra-high molecular weight polyethylene/graphene oxide composites under water lubrication

Ultra-high molecular weight polyethylene/graphene oxide (PE-UHMW/GO) composites have demonstrated potential in artificial joint applications. The tribological behavior of irradiated PE-UHMW/GO composites under water lubrication remained unclear, which limited their application range. In this study, the PE-UHMW/GO composites were gamma irradiated at 100 KGy in a vacuum and subsequently aged at 80 °C for 21 days in air. We assessed their water absorption, and mechanical and tribological properties post-treatment. Notably, gamma irradiation markedly enhanced the mechanical and tribological performance of PE-UHMW/GO composites. Irradiated composites had a 6.11% increase in compressive strength and a 25.72% increase in yield strength compared to unirradiated composites. Additionally, under water lubrication, the irradiated composites showed improved wear resistance and a reduced friction coefficient. The irradiation enhancement can be attributed to the irradiation-induced strengthening of the interface bonding between GO and PE-UHMW. Conversely, accelerated aging led to oxidative degradation, negatively impacting these properties. Aged composites exhibited lower compressive and yield strengths, higher friction coefficients, and diminished anti-wear properties compared to the irradiated composites. The wear mechanism evolved from predominantly fatigue wear in irradiated PE-UHMW/GO to a mix of abrasive and fatigue wear post-aging. While GO and aging influenced water absorption, irradiation had a minimal effect. These insights significantly contribute to the application potential of irradiated PE-UHMW/GO composites in artificial joints.

Application of Neural Network Models with Ultra-Small Samples to Optimize the Ultrasonic Consolidation Parameters for 'PEI Adherend/Prepreg (CF-PEI Fabric)/PEI Adherend' Lap Joints

The aim of this study was to optimize the ultrasonic consolidation (USC) parameters for 'PEI adherend/Prepreg (CF-PEI fabric)/PEI adherend' lap joints. For this purpose, artificial neural network (ANN) simulation was carried out. Two ANNs were trained using an ultra-small data sample, which did not provide acceptable predictive accuracy for the applied simulation methods. To solve this issue, it was proposed to artificially increase the learning sample by including additional data synthesized according to the knowledge and experience of experts. As a result, a relationship between the USC parameters and the functional characteristics of the lap joints was determined. The results of ANN simulation were successfully verified; the developed USC procedures were able to form a laminate with an even regular structure characterized by a minimum number of discontinuities and minimal damage to the consolidated components.

Mechanical strength predictability of full factorial, Taguchi, and Box Behnken designs: Optimization of thermal settings and Cellulose Nanofibers content in PA12 for MEX AM

Optimization of reinforced nanocomposites for MEX 3D-printing remain strong industrial claims. Herein, the efficacy of three modeling methods, i.e., full factorial (FFD), Taguchi (TD), and Box-Behnken (BBD), on the performance of MEX 3D printed nanocomposites was investigated, aiming to reduce the experimental effort. Filaments of medical-grade Polyamide 12 (PA12) reinforced with Cellulose NanoFibers (CNF) were evolved. Besides the CNF loading, 3D printing settings such as Nozzle (NT) and Bed (BΤ) Temperatures were optimization goals aiming to maximize the mechanical response. Three parameters and three levels of FFD were compliant with the ASTM-D638 standard (27 runs, five repetitions). An L9 orthogonal TD and a 15 runs BBD were compiled. In FFD, wt.3%CNF, 270 °C NT, and 80 °C BΤ led to 24% higher tensile strength compared to pure PA12. TGA, RAMAN, and SEM analyses interpreted the reinforcement mechanisms. TD and BBD exhibited fair approximations, requiring 7.4% and 11.8% of the FFD experimental effort.

Parametric Effects of Fused Filament Fabrication Approach on Surface Roughness of Acrylonitrile Butadiene Styrene and Nylon-6 Polymer

This research objective is to optimize the surface roughness of Nylon-6 (PA-6) and Acrylonitrile Butadiene Styrene (ABS) by analyzing the parametric effects of the Fused Filament Fabrication (FFF) technique of Three-Dimensional Printing (3DP) parameters. This article discusses how to optimize the surface roughness using Taguchi analysis by the S/N ratio, ANOVA, and modeling methods. The effects of ABS parameters (initial line thickness, raster width, bed temperature, build pattern, extrusion temperature, print speed, and layer thickness) and PA-6 parameters (layer thickness, print speed, extrusion temperature, and build pattern) were investigated with the average surface roughness (Ra) and root-mean-square average surface roughness (Rq) as response parameters. Validation tests revealed that Ra and Rq decreased significantly. After the optimization, the Ra-ABS and Rq-PA-6 for the fabricated optimized values were 1.75 µm and 21.37 µm, respectively. Taguchi optimization of Ra-ABS, Rq-ABS, Ra-PA-6, and Rq-PA-6 was performed to make one step forward to use them in further research and prototypes.

UHMWPE-Based Glass-Fiber Composites Fabricated by FDM. Multiscaling Aspects of Design, Manufacturing and Performance

The aim of the paper was to improve the functional properties of composites based on ultra-high molecular weight polyethylene (UHMWPE) by loading with reinforcing fibers. It was achieved by designing the optimal composition for its subsequent use as a feedstock for 3D-printing of guides for roller and plate chains, conveyors, etc. As a result, it was experimentally determined that loading UHMWPE with 17% high density polyethylene grafted with VinylTriMethoxySilane (HDPE-g-VTMS) was able to bind 5% glass fillers of different aspect ratios, thereby determining the optimal mechanical and tribological properties of the composites. Further increasing the content of the glass fillers caused a deterioration in their tribological properties due to insufficient adhesion of the extrudable matrix due to the excessive filler loading. A multi-level approach was implemented to design the high-strength anti-friction ‘UHMWPE+17%HDPE-g-VTMS+12%PP’-based composites using computer-aided algorithms. This resulted in the determination of the main parameters that provided their predefined mechanical and tribological properties and enabled the assessment of the possible load-speed conditions for their operation in friction units. The uniform distribution of the fillers in the matrix, the pattern of the formed supermolecular structure and, as a consequence, the mechanical and tribological properties of the composites were achieved by optimizing the values of the main control parameters (the number of processing passes in the extruder and the aspect ratio of the glass fillers).

Modeling and Optimization Approaches of Laser-Based Powder-Bed Fusion Process for Ti-6Al-4V Alloy

Laser-based powder-bed fusion (L-PBF) is a widely used additive manufacturing technology that contains several variables (processing parameters), which makes it challenging to correlate them with the desired properties (responses) when optimizing the responses. In this study, the influence of the five most influential L-PBF processing parameters of Ti-6Al-4V alloy—laser power, scanning speed, hatch spacing, layer thickness, and stripe width—on the relative density, microhardness, and various line and surface roughness parameters for the top, upskin, and downskin surfaces are thoroughly investigated. Two design of experiment (DoE) methods, including Taguchi L25 orthogonal arrays and fractional factorial DoE for the response surface method (RSM), are employed to account for the five L-PBF processing parameters at five levels each. The significance and contribution of the individual processing parameters on each response are analyzed using the Taguchi method. Then, the simultaneous contribution of two processing parameters on various responses is presented using RSM quadratic modeling. A multi-objective RSM model is developed to optimize the L-PBF processing parameters considering all the responses with equal weights. Furthermore, an artificial neural network (ANN) model is designed and trained based on the samples used for the Taguchi method and validated based on the samples used for the RSM. The Taguchi, RSM, and ANN models are used to predict the responses of unseen data. The results show that with the same amount of available experimental data, the proposed ANN model can most accurately predict the response of various properties of L-PBF components.

Electrospun Fibres with Hyaluronic Acid-Chitosan Nanoparticles Produced by a Portable Device

Electrospinning is a versatile technique to produce nano/microscale fibrous scaffolds for tissue engineering and drug delivery applications. This research aims to demonstrate that hyaluronic acid-chitosan (HA-CS) nanoparticles can be electrospun together with polycaprolactone (PCL) and gelatine (Ge) fibres using a portable device to create scaffolds for tissue repair. A range of polymer solutions of PCL-gelatine at different weight/volume concentrations and ratios were electrospun and characterised. Fibre–cell interaction (F11 cells) was evaluated based on cell viability and proliferation and, from here, a few polymer blends were electrospun into random or aligned fibre arrangements. HA-CS nanoparticles were synthesised, characterised, and used to functionalise electrospun fibres (8% w/v at 70 PCL:30 Ge), which were chosen based on cell viability. Different concentrations of HA-CS nanoparticles were tested to determine cytotoxicity. A single dosage (1 × 10⁻² mg/mL) was associated with higher cell proliferation compared with the cell-only control. This nanoparticle concentration was embedded into the electrospun fibres as either surface modification or blend. Fibres with blended NPs delivered a higher cell viability than unmodified fibres, while NP-coated fibres resulted in a higher cell proliferation (72 h) than the NP-blended ones. These biocompatible scaffolds allow cell attachment, maintain fibre arrangement, promote directional growth and yield higher cell viability.