A generalised approach on kerf geometry prediction during CO2 laser cut of PMMA thin plates using neural networks

This study presents an application of feedforward and backpropagation neural network (FFBP-NN) for predicting the kerf characteristics, i.e. the kerf width in three different distances from the surface (upper, middle and down) and kerf angle during laser cutting of 4 mm PMMA (polymethyl methacrylate) thin plates. Stand-off distance (SoD: 7, 8 and 9 mm), cutting speed (CS: 8, 13 and 18 mm/sec) and laser power (LP: 82.5, 90 and 97.5 W) are the studied parameters for low power CO2 laser cutting. A three-parameter three-level full factorial array has been used, and twenty-seven (33) cuts are performed. Subsequently, the upper, middle and down kerf widths (Wu, Wm and Wd) and the kerf angle (KA) were measured and analysed through ANOM (analysis of means), ANOVA (analysis of variances) and interaction plots. The statistical analysis highlighted that linear modelling is insufficient for the precise prediction of kerf characteristics. An FFBP-NN was developed, trained, validated and generalised for the accurate prediction of the kerf geometry. The FFBP-NN achieved an R-all value of 0.98, in contrast to the ANOVA linear models, which achieved Rsq values of about 0.86. According to the ANOM plots, the parameter values which optimize the KA resulting in positive values close to zero degrees were the 7 mm SoD, 8 mm/s CS and 97.5 W LP

Pancreatic adenocarcinoma-associated polymyositis treated with corticosteroids along with cancer specific treatment: case report

<p>Abstract</p> <p>Background</p> <p>Adenocarcinoma of the pancreas only rarely is associated with inflammatory myopathy. In this setting, polymyositis may be treated with glucocorticoids in combination with cancer specific treatment.</p> <p>Case presentation</p> <p>We present the case of a 52-year-old man with stage IIA pancreatic tail adenocarcinoma who underwent surgical treatment and six months into therapy with gemcitabine he developed symmetrical, painful, proximal muscle weakness with peripheral oedema. Re-evaluation with imaging modalities, muscle histology and biochemistry conferred the diagnosis of polymyositis associated with pancreatic cancer progression. The patient was treated with glucocorticoids along with gemcitabine and erlotinib which resulted in complete remission within six months. He remained in good health for a further six months on erlotinib maintenance therapy when a new computer tomography scan showed pancreatic cancer relapse and hence prompted 2^ndline chemotherapy with gemcitabine.</p> <p>Conclusions</p> <p>Polymyositis associated with pancreatic cancer may respond to glucocorticoids along with cancer specific treatment.</p

An experimental study of laser cutting of PLA-wood flour 3D printed plates using a modified Taguchi design

Wooden powder flour blended with thermoplastic polylactic acid (WPLA) is an eco-friendly composite material used in filament material extrusion (MEX) additive manufacturing (AM). This work investigates the effect of CO2 laser cutting (LC) of filament MEX WPLA thin plates with variable cutting parameters on mean kerf width (Wm) and means surface roughness (Ra). The experimental design consists of three parameters with three levels each, i.e., the beam cutting direction (CD: 0, 45, 90°), the cutting speed (CS: 8, 13, 18 mm/s), and the beam power (BP: 82.5, 90, 97.5 W). Eleven experiments were performed following the Taguchi L9 orthogonal array plus two in the central point. Finally, additional combinations were run and validated the suggested modified Taguchi design resulting in acceptable mean average percentage errors (MAPE). The optimum parameters' values combination (90° CD, 18mm/s CS and 97.5W BP) results in about 8.44 μm Ra and 0.355 mm Wm

Optimization of Friction Stir Welding Parameters in Hybrid Additive Manufacturing: Weldability of 3D-Printed Poly(methyl methacrylate) Plates

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 &gt; 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

Optimization of Selective Laser Sintering/Melting Operations by Using a Virus-Evolutionary Genetic Algorithm

This work presents the multi-objective optimization results of three experimental cases involving the laser sintering/melting operation and obtained by a virus evolutionary genetic algorithm. From these three experimental cases, the first one is formulated as a single-objective optimization problem aimed at maximizing the density of Ti6Al4V specimens, with layer thickness, linear energy density, hatching space and scanning strategy as the independent process parameters. The second one refers to the formulation of a two-objective optimization problem aimed at maximizing both the hardness and tensile strength of Ti6Al4V samples, with laser power, scanning speed, hatch spacing, scan pattern angle and heat treatment temperature as the independent process parameters. Finally, the third case deals with the formulation of a three-objective optimization problem aimed at minimizing mean surface roughness, while maximizing the density and hardness of laser-melted L316 stainless steel powder. The results obtained by the proposed algorithm are statistically compared to those obtained by the Greywolf (GWO), Multi-verse (MVO), Antlion (ALO), and dragonfly (DA) algorithms. Algorithm-specific parameters for all the algorithms including those of the virus-evolutionary genetic algorithm were examined by performing systematic response surface experiments to find the beneficial settings and perform comparisons under equal terms. The results have shown that the virus-evolutionary genetic algorithm is superior to the heuristics that were tested, at least on the basis of evaluating regression models as fitness functions

Impact of process parameters on dimensional accuracy of PolyJet 3D printed parts using grey Taguchi method

In this study, the dimensional accuracy of parts fabricated with PolyJet 3D Printing Direct process is investigated. An L4 orthogonal array was utilized as the design of experiments, while the process parameters examined are layer thickness, build style and scale. A simple prototype was proposed and specified external and internal dimensions were measured using a digital vernier calliper. Grey-Taguchi method was applied for optimizing all dimensional measurements. The effect of each parameter on dimensional accuracy has been identified using ANOM (Analysis of Means), while ANOVA (Analysis of Variances) has been performed to determine each parameter’s dominance. Additionally, the results of this study were compared with the findings of a previous optimization study in which the usual Taguchi method was used. It was concluded that 16 μm of layer thickness, glossy style and 50% scale provide the optimum dimensional results, while scale is the most important factor

Impact of process parameters on dimensional accuracy of PolyJet 3D printed parts using grey Taguchi method

In this study, the dimensional accuracy of parts fabricated with PolyJet 3D Printing Direct process is investigated. An L4 orthogonal array was utilized as the design of experiments, while the process parameters examined are layer thickness, build style and scale. A simple prototype was proposed and specified external and internal dimensions were measured using a digital vernier calliper. Grey-Taguchi method was applied for optimizing all dimensional measurements. The effect of each parameter on dimensional accuracy has been identified using ANOM (Analysis of Means), while ANOVA (Analysis of Variances) has been performed to determine each parameter’s dominance. Additionally, the results of this study were compared with the findings of a previous optimization study in which the usual Taguchi method was used. It was concluded that 16 μm of layer thickness, glossy style and 50% scale provide the optimum dimensional results, while scale is the most important factor

Friction Stir Welding Optimization of 3D-Printed Acrylonitrile Butadiene Styrene in Hybrid Additive Manufacturing

The feasibility of joining material extrusion (MEX) 3D-printed acrylonitrile butadiene styrene (ABS) plates with the friction stir welding (FSW) process was investigated herein as a promising topic of hybrid additive manufacturing (HAM). The influence of three process parameters on the mechanical strength of the joints was thoroughly examined and analyzed with a full factorial experimental design and statistical modeling. Hereto, the welding tool pin geometry, travel speed, and rotational speed were investigated. The joint&rsquo;s efficiency and quality are evaluated through tensile tests and morphological characterization. More specifically, specimens&rsquo; areas of particular interest were investigated with stereoscopic, optical, and scanning electron microscopy. Throughout the FSW experimental course, the welding temperature was monitored to evaluate the state of the ABS material during the process. The majority of the welded specimens exhibited increased mechanical strength compared with the respective ones of non-welded 3D printed specimens of the same geometry. Statistical modeling proved that all processing parameters were significant. The feasibility of the FSW process in 3D printed ABS workpieces was confirmed, making the FSW a cost-effective process for joining 3D printing parts, further expanding the industrial merit of the approach