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Prof. John (Ioannis) Kechagias
University of Thessaly, Volos, Greece

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0 CNC + CAM
0 Milling
0 Quality Engineering
0 3D printing
0 manufacturing technology

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Article
Published: 16 August 2021 in Lasers in Manufacturing and Materials Processing
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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.

ACS Style

John D. Kechagias; Konstantinos Ninikas; Panagiotis Stavropoulos; Konstantinos Salonitis. A Generalised Approach on Kerf Geometry Prediction during CO2 Laser cut of PMMA Thin Plates using Neural Networks. Lasers in Manufacturing and Materials Processing 2021, 8, 372 -393.

AMA Style

John D. Kechagias, Konstantinos Ninikas, Panagiotis Stavropoulos, Konstantinos Salonitis. A Generalised Approach on Kerf Geometry Prediction during CO2 Laser cut of PMMA Thin Plates using Neural Networks. Lasers in Manufacturing and Materials Processing. 2021; 8 (3):372-393.

Chicago/Turabian Style

John D. Kechagias; Konstantinos Ninikas; Panagiotis Stavropoulos; Konstantinos Salonitis. 2021. "A Generalised Approach on Kerf Geometry Prediction during CO2 Laser cut of PMMA Thin Plates using Neural Networks." Lasers in Manufacturing and Materials Processing 8, no. 3: 372-393.

Journal article
Published: 07 July 2021 in Journal of Manufacturing and Materials Processing
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This study investigated the impact of the laser speed and power, and the position and orientation of the samples, on the average surface roughness (Ra) and dimensional accuracy (DA) during CO2 laser cutting of polymethyl methacrylate (PMMA) thin sheets. A mixed five-parameter fractional factorial design was applied, and thirty-six measurements for the Ra and DA were obtained. The experimental results were analysed using ANOM diagrams, ANOVA analysis and interaction plots of all parameters. It was concluded that the laser speed is the critical parameter for both surface roughness and dimensional accuracy, resulting in strong interactions with laser power and positioning parameters. It was also shown that Ra values are affected by the orientation of the specimen and can be minimized when the samples are aligned in the laser travel direction. Finally, it was proved that lower laser speed improves the average roughness but reduces the dimensional accuracy.

ACS Style

Konstantinos Ninikas; John Kechagias; Konstantinos Salonitis. The Impact of Process Parameters on Surface Roughness and Dimensional Accuracy during CO2 Laser Cutting of PMMA Thin Sheets. Journal of Manufacturing and Materials Processing 2021, 5, 74 .

AMA Style

Konstantinos Ninikas, John Kechagias, Konstantinos Salonitis. The Impact of Process Parameters on Surface Roughness and Dimensional Accuracy during CO2 Laser Cutting of PMMA Thin Sheets. Journal of Manufacturing and Materials Processing. 2021; 5 (3):74.

Chicago/Turabian Style

Konstantinos Ninikas; John Kechagias; Konstantinos Salonitis. 2021. "The Impact of Process Parameters on Surface Roughness and Dimensional Accuracy during CO2 Laser Cutting of PMMA Thin Sheets." Journal of Manufacturing and Materials Processing 5, no. 3: 74.

Research article
Published: 24 June 2021 in Materials and Manufacturing Processes
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Wood-flour PLA (PLA/W) composite material is a recyclable new material that is suitable for wood-looking components. This organic material can be found in different wood-flour (WF) compositions recently and is appropriate for the FFF (Fused Filament Fabrication) process. The current research investigates the impact of two key parameters, the nozzle temperature (NT, oC) and the layer thickness (LT, mm) onto surface quality (roughness average Ra and maximum profile height Rt; μm) and dimensional accuracy (linear external and wall thickness in X and Y direction, mm). A commercially available wood flour of pine with additives and pure PLA used for the experimental work. The results are analyzed using statistical descriptive tools (ANOM, ANOVA and interaction plots) and regression analysis for modeling the results. It has been found that lower values of LT and NT optimize both the surface quality and the dimensional accuracy. The LT is the dominant parameter for the surface quality, while both the LT and the NT are equally important for dimensional accuracy.

ACS Style

Dimitrios Chaidas; John D. Kechagias. An investigation of PLA/W parts quality fabricated by FFF. Materials and Manufacturing Processes 2021, 1 -9.

AMA Style

Dimitrios Chaidas, John D. Kechagias. An investigation of PLA/W parts quality fabricated by FFF. Materials and Manufacturing Processes. 2021; ():1-9.

Chicago/Turabian Style

Dimitrios Chaidas; John D. Kechagias. 2021. "An investigation of PLA/W parts quality fabricated by FFF." Materials and Manufacturing Processes , no. : 1-9.

Journal article
Published: 04 June 2021 in Materials
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Polypropylene (PP) is an engineered thermoplastic polymer widely used in various applications. This work aims to enhance the properties of PP with the introduction of titanium dioxide (TiO2) nanoparticles (NPs) as nanofillers. Novel nanocomposite filaments were produced at 0.5, 1, 2, and 4 wt.% filler concentrations, following a melt mixing extrusion process. These filaments were then fed to a commercially available fused filament fabrication (FFF) 3D printer for the preparation of specimens, to be assessed for their mechanical, viscoelastic, physicochemical, and fractographic properties, according to international standards. Tensile, flexural, impact, and microhardness tests, as well as dynamic mechanical analysis (DMA), Raman, scanning electron microscopy (SEM), melt flow volume index (MVR), and atomic force microscopy (AFM), were conducted, to fully characterize the filler concentration effect on the 3D printed nanocomposite material properties. The results revealed an improvement in the nanocomposites properties, with the increase of the filler amount, while the microstructural effect and processability of the material was not significantly affected, which is important for the possible industrialization of the reported protocol. This work showed that PP/TiO2 can be a novel nanocomposite system in AM applications that the polymer industry can benefit from.

ACS Style

Nectarios Vidakis; Markos Petousis; Emmanouil Velidakis; Lazaros Tzounis; Nikolaos Mountakis; John Kechagias; Sotirios Grammatikos. Optimization of the Filler Concentration on Fused Filament Fabrication 3D Printed Polypropylene with Titanium Dioxide Nanocomposites. Materials 2021, 14, 3076 .

AMA Style

Nectarios Vidakis, Markos Petousis, Emmanouil Velidakis, Lazaros Tzounis, Nikolaos Mountakis, John Kechagias, Sotirios Grammatikos. Optimization of the Filler Concentration on Fused Filament Fabrication 3D Printed Polypropylene with Titanium Dioxide Nanocomposites. Materials. 2021; 14 (11):3076.

Chicago/Turabian Style

Nectarios Vidakis; Markos Petousis; Emmanouil Velidakis; Lazaros Tzounis; Nikolaos Mountakis; John Kechagias; Sotirios Grammatikos. 2021. "Optimization of the Filler Concentration on Fused Filament Fabrication 3D Printed Polypropylene with Titanium Dioxide Nanocomposites." Materials 14, no. 11: 3076.

Research article
Published: 31 March 2021 in Materials and Manufacturing Processes
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In this work, two typical surface characteristics, i.e., mean surface roughness and angle of the kerf during laser processing of 3D-printed Polylactic Acid (PLA) plates with 4.00 mm in thickness, are investigated. A carbon dioxide laser was utilized to separate 27 work pieces of rectangular shape. The governing laser parameters, speed of cutting and laser power, were varied according to full factorial experimental methodology. An orthogonal array (OA) having nine combinations was implemented, and nine specimens were cut with the same set-up and the same parameters three times (27 replicates in total). The experimental results were analyzed using descriptive statistical analysis, i.e., histograms, box plots, interaction charts and optimized using analysis of means (ANOM) plots as well as ANOVA analysis. The data analysis indicated that laser speed is the dominant parameter for the kerf angle, whilst both the laser velocity and power are important for mean surface roughness of the cut surface for PLA 3D-printed parts. The spread of the data is smaller in Y direction, which indicates that the weaving phenomenon affects the laser cut performance.

ACS Style

J.D. Kechagias; K. Ninikas; M. Petousis; N. Vidakis; N. Vaxevanidis. An investigation of surface quality characteristics of 3D printed PLA plates cut by CO2 laser using experimental design. Materials and Manufacturing Processes 2021, 1 -10.

AMA Style

J.D. Kechagias, K. Ninikas, M. Petousis, N. Vidakis, N. Vaxevanidis. An investigation of surface quality characteristics of 3D printed PLA plates cut by CO2 laser using experimental design. Materials and Manufacturing Processes. 2021; ():1-10.

Chicago/Turabian Style

J.D. Kechagias; K. Ninikas; M. Petousis; N. Vidakis; N. Vaxevanidis. 2021. "An investigation of surface quality characteristics of 3D printed PLA plates cut by CO2 laser using experimental design." Materials and Manufacturing Processes , no. : 1-10.

Preprint content
Published: 10 March 2021
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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 PMMA thin plates. Stand-off distance, cutting speed and beam power are the studied parameters for the case of low power CO2 laser cutting. A three-parameter three-level full factorial array has been used and twenty-seven (33) cuts were performed. Subsequently, the kerf width and angle were measured and analysed through ANOM, ANOVA and interaction plots. The statistical analysis highlighted that linear modeling is insufficient for the precise prediction of kerf characteristics. A FFBP-NN was developed, trained, validated and generalised for the accurate prediction of the kerf geometry. The FFBP-NN achieved an R-sq value of 0.98, in contrast to the ANOVA linear models which achieved a value of about 0.90.

ACS Style

John Dimitrios Kechagias; Konstantinos Ninikas; Panagiotis Stavropoulos; Konstantinos Salonitis. A generalised approach on kerf geometry prediction during CO2 laser cut of PMMA thin plates using neural networks. 2021, 1 .

AMA Style

John Dimitrios Kechagias, Konstantinos Ninikas, Panagiotis Stavropoulos, Konstantinos Salonitis. A generalised approach on kerf geometry prediction during CO2 laser cut of PMMA thin plates using neural networks. . 2021; ():1.

Chicago/Turabian Style

John Dimitrios Kechagias; Konstantinos Ninikas; Panagiotis Stavropoulos; Konstantinos Salonitis. 2021. "A generalised approach on kerf geometry prediction during CO2 laser cut of PMMA thin plates using neural networks." , no. : 1.

Journal article
Published: 19 January 2021 in Materials
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Plastic waste reduction and recycling through circular use has been critical nowadays, since there is an increasing demand for the production of plastic components based on different polymeric matrices in various applications. The most commonly used recycling procedure, especially for thermoplastic materials, is based on thermomechanical process protocols that could significantly alter the polymers’ macromolecular structure and physicochemical properties. The study at hand focuses on recycling of polyamide 12 (PA12) filament, through extrusion melting over multiple recycling courses, giving insight for its effect on the mechanical and thermal properties of Fused Filament Fabrication (FFF) manufactured specimens throughout the recycling courses. Three-dimensional (3D) FFF printed specimens were produced from virgin as well as recycled PA12 filament, while they have been experimentally tested further for their tensile, flexural, impact and micro-hardness mechanical properties. A thorough thermal and morphological analysis was also performed on all the 3D printed samples. The results of this study demonstrate that PA12 can be successfully recycled for a certain number of courses and could be utilized in 3D printing, while exhibiting improved mechanical properties when compared to virgin material for a certain number of recycling repetitions. From this work, it can be deduced that PA12 can be a viable option for circular use and 3D printing, offering an overall positive impact on recycling, while realizing 3D printed components using recycled filaments with enhanced mechanical and thermal stability.

ACS Style

Nectarios Vidakis; Markos Petousis; Lazaros Tzounis; Athena Maniadi; Emmanouil Velidakis; Nikolaos Mountakis; John D. Kechagias. Sustainable Additive Manufacturing: Mechanical Response of Polyamide 12 over Multiple Recycling Processes. Materials 2021, 14, 466 .

AMA Style

Nectarios Vidakis, Markos Petousis, Lazaros Tzounis, Athena Maniadi, Emmanouil Velidakis, Nikolaos Mountakis, John D. Kechagias. Sustainable Additive Manufacturing: Mechanical Response of Polyamide 12 over Multiple Recycling Processes. Materials. 2021; 14 (2):466.

Chicago/Turabian Style

Nectarios Vidakis; Markos Petousis; Lazaros Tzounis; Athena Maniadi; Emmanouil Velidakis; Nikolaos Mountakis; John D. Kechagias. 2021. "Sustainable Additive Manufacturing: Mechanical Response of Polyamide 12 over Multiple Recycling Processes." Materials 14, no. 2: 466.

Journal article
Published: 13 October 2020 in Mathematics
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An experimental investigation of the surface quality of the Poly-Jet 3D printing (PJ-3DP) process is presented. PJ-3DP is an additive manufacturing process, which uses jetted photopolymer droplets, which are immediately cured with ultraviolet lamps, to build physical models, layer-by-layer. This method is fast and accurate due to the mechanism it uses for the deposition of layers as well as the 16 microns of layer thickness used. Τo characterize the surface quality of PJ-3DP printed parts, an experiment was designed and the results were analyzed to identify the impact of the deposition angle and blade mechanism motion onto the surface roughness. First, linear regression models were extracted for the prediction of surface quality parameters, such as the average surface roughness (Ra) and the total height of the profile (Rt) in the X and Y directions. Then, a Feed Forward Back Propagation Neural Network (FFBP-NN) was proposed for increasing the prediction performance of the surface roughness parameters Ra and Rt. These two models were compared with the reported ones in the literature; it was revealed that both performed better, leading to more accurate surface roughness predictions, whilst the NN model resulted in the best predictions, in particular for the Ra parameter.

ACS Style

Nectarios Vidakis; Markos Petousis; Nikolaos Vaxevanidis; John Kechagias. Surface Roughness Investigation of Poly-Jet 3D Printing. Mathematics 2020, 8, 1758 .

AMA Style

Nectarios Vidakis, Markos Petousis, Nikolaos Vaxevanidis, John Kechagias. Surface Roughness Investigation of Poly-Jet 3D Printing. Mathematics. 2020; 8 (10):1758.

Chicago/Turabian Style

Nectarios Vidakis; Markos Petousis; Nikolaos Vaxevanidis; John Kechagias. 2020. "Surface Roughness Investigation of Poly-Jet 3D Printing." Mathematics 8, no. 10: 1758.

Journal article
Published: 25 June 2020 in Micromachines
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In order to expand the mechanical and physical capabilities of 3D-printed structures fabricated via commercially available 3D printers, nanocomposite and microcomposite filaments were produced via melt extrusion, 3D-printed and evaluated. The scope of this work is to fabricate physically and mechanically improved nanocomposites or microcomposites for direct commercial or industrial implementation while enriching the existing literature with the methodology applied. Zinc Oxide nanoparticles (ZnO nano) and Zinc Oxide micro-sized particles (ZnO micro) were dispersed, in various concentrations, in Acrylonitrile Butadiene Styrene (ABS) matrices and printable filament of ~1.75mm was extruded. The composite filaments were employed in a commercial 3D printer for tensile and flexion specimens’ production, according to international standards. Results showed a 14% increase in the tensile strength at 5% wt. concentration in both nanocomposite and microcomposite materials, when compared to pure ABS specimens. Furthermore, a 15.3% increase in the flexural strength was found in 0.5% wt. for ABS/ZnO nano, while an increase of 17% was found on 5% wt. ABS/ZnO micro. Comparing the two composites, it was found that the ABS/ZnO microcomposite structures had higher overall mechanical strength over ABS/ZnO nanostructures.

ACS Style

Nectarios Vidakis; Markos Petousis; Athena Maniadi; Emmanuel Koudoumas; George Kenanakis; Cosmin Romanitan; Oana Tutunaru; Mirela Suchea; John Kechagias. The Mechanical and Physical Properties of 3D-Printed Materials Composed of ABS-ZnO Nanocomposites and ABS-ZnO Microcomposites. Micromachines 2020, 11, 615 .

AMA Style

Nectarios Vidakis, Markos Petousis, Athena Maniadi, Emmanuel Koudoumas, George Kenanakis, Cosmin Romanitan, Oana Tutunaru, Mirela Suchea, John Kechagias. The Mechanical and Physical Properties of 3D-Printed Materials Composed of ABS-ZnO Nanocomposites and ABS-ZnO Microcomposites. Micromachines. 2020; 11 (6):615.

Chicago/Turabian Style

Nectarios Vidakis; Markos Petousis; Athena Maniadi; Emmanuel Koudoumas; George Kenanakis; Cosmin Romanitan; Oana Tutunaru; Mirela Suchea; John Kechagias. 2020. "The Mechanical and Physical Properties of 3D-Printed Materials Composed of ABS-ZnO Nanocomposites and ABS-ZnO Microcomposites." Micromachines 11, no. 6: 615.

Journal article
Published: 29 May 2020 in Energies
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Sustainability is becoming more and more important as a decision attribute in the manufacturing environment. However, quantitative metrics for all the aspects of the triple bottom line are difficult to assess. Within the present paper, the sustainability metrics are considered in tandem with other traditional manufacturing metrics such as time, flexibility, and quality and a novel framework is presented that integrates information and requirements from Computer-Aided Technologies (CAx) systems. A novel tool is outlined for considering a number of key performance indicators related to the triple bottom line when deciding the most appropriate process route. The implemented system allows the assessment of alternative process plans considering the market demands and available resources.

ACS Style

Prateek Saxena; Panagiotis Stavropoulos; John Kechagias; Konstantinos Salonitis. Sustainability Assessment for Manufacturing Operations. Energies 2020, 13, 2730 .

AMA Style

Prateek Saxena, Panagiotis Stavropoulos, John Kechagias, Konstantinos Salonitis. Sustainability Assessment for Manufacturing Operations. Energies. 2020; 13 (11):2730.

Chicago/Turabian Style

Prateek Saxena; Panagiotis Stavropoulos; John Kechagias; Konstantinos Salonitis. 2020. "Sustainability Assessment for Manufacturing Operations." Energies 13, no. 11: 2730.

Journal article
Published: 19 May 2020 in Journal of Manufacturing and Materials Processing
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This paper investigates the quality performance of FDM 3D printed models with thin walls. The design of experiments method (DOE) was used and nine models of the same size were fabricated in a low-cost 3D printer using polylactic acid (PLA) material. Two limited studied parameters were considered (extraction temperature and wall thickness), each one having three levels. External X and Y dimensions were measured using a micrometer, as well as four surface roughness parameters (Ra, Rz, Rt, Rsm) with a surface tester. Two optimization techniques (the Taguchi approach and Grey relational analysis) were utilized along with statistical analysis to examine how the temperature and wall thickness affect the dimensional accuracy and the surface quality of the parts. The results showed that high extraction temperature and median wall thickness values optimize both dimensional accuracy and surface roughness, while temperature is the most important factor.

ACS Style

Kyriaki-Evangelia Aslani; Dimitrios Chaidas; John Kechagias; Panagiotis Kyratsis; Konstantinos Salonitis. Quality Performance Evaluation of Thin Walled PLA 3D Printed Parts Using the Taguchi Method and Grey Relational Analysis. Journal of Manufacturing and Materials Processing 2020, 4, 47 .

AMA Style

Kyriaki-Evangelia Aslani, Dimitrios Chaidas, John Kechagias, Panagiotis Kyratsis, Konstantinos Salonitis. Quality Performance Evaluation of Thin Walled PLA 3D Printed Parts Using the Taguchi Method and Grey Relational Analysis. Journal of Manufacturing and Materials Processing. 2020; 4 (2):47.

Chicago/Turabian Style

Kyriaki-Evangelia Aslani; Dimitrios Chaidas; John Kechagias; Panagiotis Kyratsis; Konstantinos Salonitis. 2020. "Quality Performance Evaluation of Thin Walled PLA 3D Printed Parts Using the Taguchi Method and Grey Relational Analysis." Journal of Manufacturing and Materials Processing 4, no. 2: 47.

Research article
Published: 04 May 2020 in SN Applied Sciences
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The dimensional accuracy of a simple benchmark specimen fabricated with fused filament fabrication (FFF) route is discussed in the present study. FFF is a low-cost 3D-printing process that builds complicated parts by extruding molten plastic. Experimental method was designed according to Taguchi robust design based on an orthogonal array with nine experiments (L9 orthogonal array). The printing material was the polylactic acid (PLA). First, Grey–Taguchi method was used for the identification of the optimal printing parameter levels which result in the best dimensional accuracy for the PLA FFF parts. The printing parameters selected included number of shells, printing temperature, infill rate and printing pattern; they were selected in accordance with relevant studies already published. Then, in the second phase, nine specimens were fabricated using the same optimal printing parameter values determined in the first phase. The tolerance of these specimens was characterized according to international tolerance grades (IT grades). Data analysis showed that nozzle temperature is the dominant parameter. Additionally, the parts printed using the optimized process parameter levels possess good dimensional accuracy, which is compatible with the IT grades specification.

ACS Style

Kyriaki-Evangelia Aslani; Konstantinos Kitsakis; John D. Kechagias; Nikolaos M. Vaxevanidis; Dimitrios E. Manolakos. On the application of grey Taguchi method for benchmarking the dimensional accuracy of the PLA fused filament fabrication process. SN Applied Sciences 2020, 2, 1 -11.

AMA Style

Kyriaki-Evangelia Aslani, Konstantinos Kitsakis, John D. Kechagias, Nikolaos M. Vaxevanidis, Dimitrios E. Manolakos. On the application of grey Taguchi method for benchmarking the dimensional accuracy of the PLA fused filament fabrication process. SN Applied Sciences. 2020; 2 (6):1-11.

Chicago/Turabian Style

Kyriaki-Evangelia Aslani; Konstantinos Kitsakis; John D. Kechagias; Nikolaos M. Vaxevanidis; Dimitrios E. Manolakos. 2020. "On the application of grey Taguchi method for benchmarking the dimensional accuracy of the PLA fused filament fabrication process." SN Applied Sciences 2, no. 6: 1-11.

Journal article
Published: 27 April 2020 in Sustainability
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Sustainability in additive manufacturing refers mainly to the recycling rate of polymers and composites used in fused filament fabrication (FFF), which nowadays are rapidly increasing in volume and value. Recycling of such materials is mostly a thermomechanical process that modifies their overall mechanical behavior. The present research work focuses on the acrylonitrile-butadiene-styrene (ABS) polymer, which is the second most popular material used in FFF-3D printing. In order to investigate the effect of the recycling courses on the mechanical response of the ABS polymer, an experimental simulation of the recycling process that isolates the thermomechanical treatment from other parameters (i.e., contamination, ageing, etc.) has been performed. To quantify the effect of repeated recycling processes on the mechanic response of the ABS polymer, a wide variety of mechanical tests were conducted on FFF-printed specimens. Regarding this, standard tensile, compression, flexion, impact and micro-hardness tests were performed per recycle repetition. The findings prove that the mechanical response of the recycled ABS polymer is generally improved over the recycling repetitions for a certain number of repetitions. An optimum overall mechanical behavior is found between the third and the fifth repetition, indicating a significant positive impact of the ABS polymer recycling, besides the environmental one.

ACS Style

Nectarios Vidakis; Markos Petousis; Athena Maniadi; Emmanuel Koudoumas; Achilles Vairis; John Kechagias. Sustainable Additive Manufacturing: Mechanical Response of Acrylonitrile-Butadiene-Styrene over Multiple Recycling Processes. Sustainability 2020, 12, 3568 .

AMA Style

Nectarios Vidakis, Markos Petousis, Athena Maniadi, Emmanuel Koudoumas, Achilles Vairis, John Kechagias. Sustainable Additive Manufacturing: Mechanical Response of Acrylonitrile-Butadiene-Styrene over Multiple Recycling Processes. Sustainability. 2020; 12 (9):3568.

Chicago/Turabian Style

Nectarios Vidakis; Markos Petousis; Athena Maniadi; Emmanuel Koudoumas; Achilles Vairis; John Kechagias. 2020. "Sustainable Additive Manufacturing: Mechanical Response of Acrylonitrile-Butadiene-Styrene over Multiple Recycling Processes." Sustainability 12, no. 9: 3568.

Journal article
Published: 05 November 2019 in Measurement
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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 L9 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.

ACS Style

John D. Kechagias; Kyriaki-Evangelia Aslani; Nikolaos A. Fountas; Nikolaos M. Vaxevanidis; Dimitrios E. Manolakos. A comparative investigation of Taguchi and full factorial design for machinability prediction in turning of a titanium alloy. Measurement 2019, 151, 107213 .

AMA Style

John D. Kechagias, Kyriaki-Evangelia Aslani, Nikolaos A. Fountas, Nikolaos M. Vaxevanidis, Dimitrios E. Manolakos. A comparative investigation of Taguchi and full factorial design for machinability prediction in turning of a titanium alloy. Measurement. 2019; 151 ():107213.

Chicago/Turabian Style

John D. Kechagias; Kyriaki-Evangelia Aslani; Nikolaos A. Fountas; Nikolaos M. Vaxevanidis; Dimitrios E. Manolakos. 2019. "A comparative investigation of Taguchi and full factorial design for machinability prediction in turning of a titanium alloy." Measurement 151, no. : 107213.

Paper
Published: 30 October 2019 in IOP Conference Series: Materials Science and Engineering
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The current paper is a case study of optimizing fused filament fabrication (FFF) process using robust design. FFF process is a low cost 3d printing process that uses ABS (Acrylonitrile-Butadiene-Styrene) filament in order to build progressive layer by layer, physical prototypes. Four (4) parameters having three levels each ones is used (Deposition angle, Layer thickness, Infill ratio, Infill pattern). The quality indicator that used for the optimization process is the dimensional accuracy. It was found that the layer thickness is the most important parameter in the reported experimental area.

ACS Style

A Tsiolikas; T Mikrou; F Vakouftsi; K E Aslani; J Kechagias. Robust design application for optimizing ABS fused filament fabrication process: A case study. IOP Conference Series: Materials Science and Engineering 2019, 564, 012021 .

AMA Style

A Tsiolikas, T Mikrou, F Vakouftsi, K E Aslani, J Kechagias. Robust design application for optimizing ABS fused filament fabrication process: A case study. IOP Conference Series: Materials Science and Engineering. 2019; 564 (1):012021.

Chicago/Turabian Style

A Tsiolikas; T Mikrou; F Vakouftsi; K E Aslani; J Kechagias. 2019. "Robust design application for optimizing ABS fused filament fabrication process: A case study." IOP Conference Series: Materials Science and Engineering 564, no. 1: 012021.

Conference paper
Published: 30 October 2019 in IOP Conference Series: Materials Science and Engineering
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Nowadays computers have invaded all levels of production, thus improving the quality and quantity of products. Digital manufacturing involves all tools for design, simulate, and programming machine tools in order to manufacture prototypes or tools for production use. This project is a case study of digital manufacturing for prototyping of an internal combustion engine visualization model. Solidworks is used for 3D modeling of all parts of the engine. Fused filament fabrication (FFF) is used for physical modeling of the engine parts. Pros and cons of the manufacturing process are discussed. It is concluded that parameter optimization is needed in order to improve quality indicators of the 3D printed engine parts.

ACS Style

K Kitsakis; Kyriaki-Evangelia Aslani; N Vaxevanidis; John (Ioannis) Kechagias. An internal combustion engine visualization physical prototype applying digital manufacturing. IOP Conference Series: Materials Science and Engineering 2019, 564, 012022 .

AMA Style

K Kitsakis, Kyriaki-Evangelia Aslani, N Vaxevanidis, John (Ioannis) Kechagias. An internal combustion engine visualization physical prototype applying digital manufacturing. IOP Conference Series: Materials Science and Engineering. 2019; 564 (1):012022.

Chicago/Turabian Style

K Kitsakis; Kyriaki-Evangelia Aslani; N Vaxevanidis; John (Ioannis) Kechagias. 2019. "An internal combustion engine visualization physical prototype applying digital manufacturing." IOP Conference Series: Materials Science and Engineering 564, no. 1: 012022.

Journal article
Published: 03 September 2019 in Frattura ed Integrità Strutturale
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Machinability of engineering materials is crucial for industrial manufacturing processes since it affects all the essential aspects involved, e.g. work­load, resources, surface integrity and part quality. Two basic ma­chin­ability para­meters are the surface roughness, closely associated with the functional and tribological performance of components, and the cutting forces acting on the tool. Knowledge of the cutting forces is needed for estimation of power re­quirements and for the design of machine tool elements, tool-holders and fix­tures, adequately rigid and free from vibration. This work in­ve­stigates the in­flu­ence of cutting conditions on machinability indicators such as the main cutting force Fc and surface roughness parameters Ra and Rt when longitudinally turning CuZn39Pb3 brass alloy. Full quadratic regression models were de­veloped to correlate the machining conditions with the imparted machinability characteristics. Further on, an advanced artificial grey wolf optimization algorithm was implemented to optimize the aforementioned responses with great success in finding the final optimal values of the turning parameters.

ACS Style

Nikolaos Fountas; Angelos Koutsomichalis; John (Ioannis) Kechagias; Nikolaos Vaxevanidis. Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm. Frattura ed Integrità Strutturale 2019, 13, 584 -594.

AMA Style

Nikolaos Fountas, Angelos Koutsomichalis, John (Ioannis) Kechagias, Nikolaos Vaxevanidis. Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm. Frattura ed Integrità Strutturale. 2019; 13 (50):584-594.

Chicago/Turabian Style

Nikolaos Fountas; Angelos Koutsomichalis; John (Ioannis) Kechagias; Nikolaos Vaxevanidis. 2019. "Multi-response optimization of CuZn39Pb3 brass alloy turning by implementing Grey Wolf algorithm." Frattura ed Integrità Strutturale 13, no. 50: 584-594.

Conference paper
Published: 01 May 2019 in 2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)
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In the current study, the surface finish of specimens fabricated with PolyJet 3D Printing Direct process is discussed. Three surface roughness indicators were measured at three positions, while three process parameters namely layer thickness, build style and scale were examined. An L4 orthogonal array was employed for the design of experiments. Grey-Taguchi method was applied in order to optimize all surface roughness parameters. The effect of each parameter has been investigated using ANOM (Analysis of Means), while ANOVA (Analysis of Variances) has been performed to identify each parameter importance onto the surface texture. Additionally, the findings of this study were compared with the results of a similar optimization study conducted before, using the usual Taguchi method. It was concluded that 16 µm of layer thickness and glossy style provide the optimum surface roughness results, while built style is the most dominant factor. All the results of the Grey Taguchi method are compatible with the ones of the usual Taguchi method.

ACS Style

Kyriaki-Evangelia Aslani; Foteini Vakouftsi; John (Ioannis) Kechagias; Nikos E. Mastorakis. Surface Roughness Optimization of Poly-Jet 3D Printing Using Grey Taguchi Method. 2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) 2019, 213 -218.

AMA Style

Kyriaki-Evangelia Aslani, Foteini Vakouftsi, John (Ioannis) Kechagias, Nikos E. Mastorakis. Surface Roughness Optimization of Poly-Jet 3D Printing Using Grey Taguchi Method. 2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO). 2019; ():213-218.

Chicago/Turabian Style

Kyriaki-Evangelia Aslani; Foteini Vakouftsi; John (Ioannis) Kechagias; Nikos E. Mastorakis. 2019. "Surface Roughness Optimization of Poly-Jet 3D Printing Using Grey Taguchi Method." 2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO) , no. : 213-218.

Journal article
Published: 05 October 2018 in Procedia Structural Integrity
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This paper investigates the machinability characteristics of a high-leaded Brass alloy (CuZn39Pb3) by considering the effect of rotational speed; feed rate and depth of cut on main cutting force Fc, arithmetic surface roughness Ra and maximum height of profile Rt during its longitudinally turning. An L18 mixed-level Taguchi Orthogonal Array experimental design was established so as to systematically examine the effect of machining conditions on the aforementioned responses. Full quadratic regression models were developed for correlating the experimental and fitted data after the statistical analysis for studying the significance of the cutting conditions to main cutting force Fc, arithmetic surface roughness Ra and maximum height of profile Rt. Experimental results have shown that depth of cut holds dominant effect of cutting force whilst its contribution equals to 73.61%. Rotational speed and feed rate have just as important effect on arithmetic surface roughness average with 38.85% and 32.15% contributions respectively. For the maximum height of the profile, rotational speed has a significant contribution equal to 42.38% of the overall significance. The models created can explain the investigated parameters’ variation to the percentages of 99.44%, 97.29% and 96.76% for main cutting force Fc, arithmetic surface roughness Ra and maximum height of profile Rt respectively.

ACS Style

N.M. Vaxevanidis; N.A. Fountas; A. Koutsomichalis; J.D. Kechagias. Experimental investigation of machinability parameters in turning of CuZn39Pb3 brass alloy. Procedia Structural Integrity 2018, 10, 333 -341.

AMA Style

N.M. Vaxevanidis, N.A. Fountas, A. Koutsomichalis, J.D. Kechagias. Experimental investigation of machinability parameters in turning of CuZn39Pb3 brass alloy. Procedia Structural Integrity. 2018; 10 ():333-341.

Chicago/Turabian Style

N.M. Vaxevanidis; N.A. Fountas; A. Koutsomichalis; J.D. Kechagias. 2018. "Experimental investigation of machinability parameters in turning of CuZn39Pb3 brass alloy." Procedia Structural Integrity 10, no. : 333-341.

Conference paper
Published: 24 July 2018 in MATEC Web of Conferences
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A methodology is presented to optimize the performance of an Artificial Neural Network (ANN) using Design of Experiments (DOE). 8 different feed forward back propagation (FFBP) ANNs were developed and tested according to the L8 full factorial orthogonal array. The 3 parameters tested were: Number of Hidden Neurons, Learning rate, and Momentum; each one having two levels. By utilizing the analysis of means (ANOM) and the analysis of variances (ANOVA), the optimum levels of ANN parameters were determined. The developed ANN was applied for predicting cutting forces and average surface roughness in turning Ti-6Al-4V alloy.

ACS Style

John (Ioannis) Kechagias; Aristidis Tsiolikas; Panagiotis Asteris; Nikolaos Vaxevanidis. Optimizing ANN performance using DOE: application on turning of a titanium alloy. MATEC Web of Conferences 2018, 178, 01017 .

AMA Style

John (Ioannis) Kechagias, Aristidis Tsiolikas, Panagiotis Asteris, Nikolaos Vaxevanidis. Optimizing ANN performance using DOE: application on turning of a titanium alloy. MATEC Web of Conferences. 2018; 178 ():01017.

Chicago/Turabian Style

John (Ioannis) Kechagias; Aristidis Tsiolikas; Panagiotis Asteris; Nikolaos Vaxevanidis. 2018. "Optimizing ANN performance using DOE: application on turning of a titanium alloy." MATEC Web of Conferences 178, no. : 01017.