Box-Behnken modeling to quantify the impact of control parameters on the energy and tensile efficiency of PEEK in MEX 3D-printing DOI Creative Commons
Nectarios Vidakis, Markos Petousis, Nikolaos Mountakis

et al.

Heliyon, Journal Year: 2023, Volume and Issue: 9(7), P. e18363 - e18363

Published: July 1, 2023

Currently, energy efficiency and saving in production engineering, including Material Extrusion (MEX) Additive Manufacturing, are of key importance to ensure process sustainability cost-effectiveness. The functionality parts made with MEX 3D-printing remains solid, especially for expensive high-performance polymers, biomedical, automotive, aerospace industries. Herein, the tensile strength metrics investigated over three control parameters (Nozzle Temperature, Layer Thickness, Printing Speed), aid laboratory-scale PEEK filaments fabricated melt extrusion. A double optimization is attempted by consuming minimum energy, improved strength. three-level Box-Behnken design five replicas each experimental run was employed. Statistical analysis findings proved that LT most decisive setting mechanical An 0.1 mm maximized endurance (∼74 MPa), but at same time, it responsible worst (∼0.58 MJ) printing time (∼900 s) expenditure. statistical further discussed interpreted using fractographic SEM optical microscopy, revealing 3D quality fracture mechanisms samples. Thermogravimetric (TGA) performed. hold measurable engineering industrial merit, since they may be utilized achieve an optimum case-dependent compromise between usually contradictory goals productivity, performance, functionality.

Language: Английский

Effect of 3D printing process parameters on surface and mechanical properties of FFF-printed PEEK DOI
Aditya Pulipaka, Kunal Manoj Gide, Ali Beheshti

et al.

Journal of Manufacturing Processes, Journal Year: 2022, Volume and Issue: 85, P. 368 - 386

Published: Dec. 5, 2022

Language: Английский

Citations

116
A multi-parametric process evaluation of the mechanical response of PLA in FFF 3D printing DOI

John D. Kechagias,

Nectarios Vidakis, Markos Petousis

et al.

Materials and Manufacturing Processes, Journal Year: 2022, Volume and Issue: 38(8), P. 941 - 953

Published: June 21, 2022

Polylactic acid (PLA) material in filament form can be 3D printed and complex physical models by using a low-cost extrusion mechanism process that is broadly known as fused fabrication (FFF). Even though the PLA-FFF has been extensively studied literature, its parts' mechanical response varies significantly, it not association with six control parameters at same time, i.e. infill density (ID), raster deposition angle (RDA), nozzle temperature (NT), printing speed (PS), layer thickness (LT), bed (BT). The simultaneous influence of variable on properties challenging assignment aspires to rank parameters' importance, model process, finally validate independent experiments. One-hundred twenty-five experiments run following Taguchi L25 orthogonal array repeated five times for study purpose. After an extensive literature survey preliminary experiments, parameter selection discrete values were selected. experimental results analyzed statistical tools critically compared literature. RDA, NT, PS, ID significantly impact PLA parts.

Language: Английский

Citations

101
Recent trends and future outlooks in manufacturing methods and applications of FGM: a comprehensive review DOI
Parveen Kumar, Satish Kumar Sharma, Ratnesh Kumar Raj Singh

et al.

Materials and Manufacturing Processes, Journal Year: 2022, Volume and Issue: 38(9), P. 1033 - 1067

Published: June 16, 2022

Owing to its graded function and agglomeration of contradictory properties over structure, functionally materials (FGMs) are popular as second-generation composites. FGMs intended optimize performance capability survive in a harsh working environment without failure or losing their properties. This article presents comprehensive review FGM literature, detailing the evolution development history, classification, manufacturing methods for different types FGMs, citing merits limitations each. Moreover, current status industry-specific applications each category is also summarized discussed. Furthermore, key challenges future scopes provide insight into research directions

Language: Английский

Citations

75
Fused filament fabrication parameter adjustments for sustainable 3D printing DOI

John D. Kechagias,

Dimitrios Chaidas

Materials and Manufacturing Processes, Journal Year: 2023, Volume and Issue: 38(8), P. 933 - 940

Published: Feb. 10, 2023

Sustainability denotes that energy consumption and its effects on society should also be considered at the early stages of a product idea, except for structure cost. Quality metrics fused filament fabrication (FFF) 3D printed parts as time, quality flexibility are crucial well-being production elements. This work analyses sustainability low-cost advocates good practices. By following recommended rules, viable components can produced eliminate material costs waste. It is essential to choose correct parameters prepare models will print. Careful choices must made during this pre-production phase because it determines how right sustainable final be. Of course, with experience failure prints, user becomes more flexible capable making judgments better sustainability.

Language: Английский

Citations

63
Functionality Versus Sustainability for PLA in MEX 3D Printing: The Impact of Generic Process Control Factors on Flexural Response and Energy Efficiency DOI Open Access
Markos Petousis, Nectarios Vidakis, Nikolaos Mountakis

et al.

Polymers, Journal Year: 2023, Volume and Issue: 15(5), P. 1232 - 1232

Published: Feb. 28, 2023

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), concurrent achievement of these opposing goals may become puzzle, especially since MEX 3D-printing offers variety process parameters. Herein, multi-objective optimization material deployment, 3D printing flexural response, and energy consumption AM with PLA introduced. To evaluate impact important generic device-independent control parameters on responses, Robust Design theory was employed. Raster Deposition Angle (RDA), Layer Thickness (LT), Infill Density (ID), Nozzle Temperature (NT), Bed (BT), Printing Speed (PS) were selected to compile five-level orthogonal array. A total 25 experimental runs five specimen replicas each accumulated 135 experiments. Analysis variances reduced quadratic regression models (RQRM) used decompose parameter responses. The ID, RDA, LT ranked first time, weight, strength, consumption, respectively. RQRM predictive experimentally validated hold significant technological merit, proper adjustment per case.

Language: Английский

Citations

45
Maximizing performance and efficiency in 3D printing of polylactic acid biomaterials: Unveiling of microstructural morphology, and implications of process parameters and modeling of the mechanical strength, surface roughness, print time, and print energy for fused filament fabricated (FFF) bioparts DOI
Ray Tahir Mushtaq,

Yanen Wang,

Chengwei Bao

et al.

International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: 259, P. 129201 - 129201

Published: Jan. 6, 2024

Language: Английский

Citations

24
Exploring forest fire susceptibility and management strategies in Western Himalaya: Integrating ensemble machine learning and explainable AI for accurate prediction and comprehensive analysis DOI Creative Commons
Hoang Thi Hang, Javed Mallick, Saeed Alqadhi

et al.

Environmental Technology & Innovation, Journal Year: 2024, Volume and Issue: 35, P. 103655 - 103655

Published: May 5, 2024

Forest fires pose a significant threat to ecosystems and socio-economic activities, necessitating the development of accurate predictive models for effective management mitigation. In this study, we present novel machine learning approach combined with Explainable Artificial Intelligence (XAI) techniques predict forest fire susceptibility in Nainital district. Our innovative methodology integrates several robust — AdaBoost, Gradient Boosting Machine (GBM), XGBoost Random Deep Neural Network (DNN) as meta-model stacking framework. This not only utilises individual strengths these models, but also improves overall prediction performance reliability. By using XAI techniques, particular SHAP (SHapley Additive exPlanations) LIME (Local Interpretable Model-agnostic Explanations), improve interpretability provide insights into decision-making processes. results show effectiveness ensemble model categorising different zones: very low, moderate, high high. particular, identified extensive areas susceptibility, precision, recall F1 values underpinning their effectiveness. These achieved ROC AUC above 0.90, performing exceptionally well an 0.94. The are remarkably inclusion confidence intervals most important metrics all emphasises robustness reliability supports practical use management. Through summary plots, analyze global variable importance, revealing annual rainfall Evapotranspiration (ET) key factors influencing susceptibility. Local analysis consistently highlights importance rainfall, ET, distance from roads across models. study fills research gap by providing comprehensive interpretable modelling that our ability effectively manage risk is consistent environmental protection sustainable goals.

Language: Английский

Citations

20
Multifunctional Material Extrusion 3D-Printed Antibacterial Polylactic Acid (PLA) with Binary Inclusions: The Effect of Cuprous Oxide and Cellulose Nanofibers DOI Creative Commons
Markos Petousis, Nectarios Vidakis, Nikolaos Mountakis

et al.

Fibers, Journal Year: 2022, Volume and Issue: 10(6), P. 52 - 52

Published: June 10, 2022

In this work, we present an effective process easily adapted in industrial environments for the development of multifunctional nanocomposites material extrusion (MEX) 3D printing (3DP). The literature is still very limited field, although interest such materials constantly increasing. Nanocomposites with binary inclusions were prepared and investigated study. Polylactic acid (PLA) was used as matrix material, cuprous oxide (Cu2O) cellulose nanofibers (CNF) nanoadditives introduced to enhance mechanical properties induce antibacterial performance. Specimens built according international standards a thermomechanical process. Tensile, flexural, impact, microhardness tests conducted. effect on thermal through thermogravimetric analysis, Raman spectroscopic analysis morphological characteristics evaluated atomic force microscopy (AFM), scanning electron (SEM), energy-dispersive X-ray (EDS) analyses. performance nanomaterials studied against Staphylococcus aureus (S. aureus) Escherichia coli (E. coli) bacteria, screening agar well diffusion method. All exhibited biocidal bacteria tested. tested PLA/1.0 CNF/0.5 Cu2O had 51.1% higher tensile strength 35.9% flexural than pure PLA material.

Language: Английский

Citations

49
Application of machine learning methods on dynamic strength analysis for additive manufactured polypropylene-based composites DOI Creative Commons
Ruijun Cai, Kui Wang, Wei Wen

et al.

Polymer Testing, Journal Year: 2022, Volume and Issue: 110, P. 107580 - 107580

Published: April 9, 2022

This study aimed at applying machine learning (ML) methods to analyze dynamic strength of 3D-printed polypropylene (PP)-based composites. The additive manufactured PP-based composites with different fillers and printing parameters was investigated by split Hopkinson pressure bars. Based on experimental results, six approaches were applied express the relationships between materials as well parameters. performance algorithms relatively small training datasets evaluated. comparison results showed that artificial neural network could achieve highest prediction accuracy but low computational efficiency, whereas support vector regression provide satisfactory both good efficiency. extreme gradient boosting random forest recommended if importance input required.

Language: Английский

Citations

46
Multi-functional polyamide 12 (PA12)/ multiwall carbon nanotube 3D printed nanocomposites with enhanced mechanical and electrical properties DOI Creative Commons
Nectarios Vidakis, Markos Petousis, Emmanouil Velidakis

et al.

Advanced Composite Materials, Journal Year: 2022, Volume and Issue: 31(6), P. 630 - 654

Published: May 22, 2022

Inducing electrical properties in thermoplastic materials and enhancing their mechanical with the addition of nanofiller Fused Filament Fabrication (FFF) is main purpose study. Multiwall carbon nanotubes (MWCNT) at different weight percentage (wt.%) loadings (0.1%, 0.5%, 1.0%, 2.5%, 5.0%, 10.0%) were incorporated into Polyamide 12 (PA12) matrix. Melt mixing followed by filament extrusion was applied. Filaments employed to 3D print specimens. A thorough study on electrically Conductive Polymeric Composites (CPCs) percolation threshold carried out. Mechanical thermomechanical response investigations also conducted. Scanning Electron Microscopy (SEM) morphology printed samples. The results showed a enhancement for 5.0 wt.% filler’s ratio. conductivity increased increasing filler loading. 10% PA12/MWCNT nanocomposite additionally exhibited an electrothermal Joule-heating behavior. antibacterial behavior tested agar well diffusion screening method, gram-negative Escherichia coli (E. coli) gram-positive Staphylococcus aureus (S. aureus). mild antimicrobial performance observed. It can be concluded that multi-functional lightweight CPCs developed herein could applied various applications, e.g. joule-heating devices, flexible conductors, anti-static enclosures.

Language: Английский

Citations

45