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Authors = Sandeep Kumar Dwivedi ORCID = 0000-0002-3728-1681

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18 pages, 4755 KiB  
Article
Optimization of FFF Process Parameters by Naked Mole-Rat Algorithms with Enhanced Exploration and Exploitation Capabilities
by Jasgurpreet Singh Chohan, Nitin Mittal, Raman Kumar, Sandeep Singh, Shubham Sharma, Shashi Prakash Dwivedi, Ambuj Saxena, Somnath Chattopadhyaya, Rushdan A. Ilyas, Chi Hieu Le and Szymon Wojciechowski
Polymers 2021, 13(11), 1702; https://doi.org/10.3390/polym13111702 - 23 May 2021
Cited by 56 | Viewed by 3608
Abstract
Fused filament fabrication (FFF) has numerous process parameters that influence the mechanical strength of parts. Hence, many optimization studies are performed using conventional tools and algorithms. Although studies have also been performed using advanced algorithms, limited research has been reported in which variants [...] Read more.
Fused filament fabrication (FFF) has numerous process parameters that influence the mechanical strength of parts. Hence, many optimization studies are performed using conventional tools and algorithms. Although studies have also been performed using advanced algorithms, limited research has been reported in which variants of the naked mole-rat algorithm (NMRA) are implemented for solving the optimization issues of manufacturing processes. This study was performed to scrutinize optimum parameters and their levels to attain maximum impact strength, flexural strength and tensile strength based on five different FFF process parameters. The algorithm yielded better results than other studies and successfully achieved a maximum response, which may be helpful to enhance the mechanical strength of FFF parts. The study opens a plethora of research prospects for implementing NMRA in manufacturing. Moreover, the findings may help identify critical parametric levels for the fabrication of customized products at the commercial level and help to attain the objectives of Industry 4.0. Full article
(This article belongs to the Special Issue Additive Manufacturing of Bio and Synthetic Polymers)
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10 pages, 243 KiB  
Proceeding Paper
Evaluation and Prevention of Hydrogen Embrittlement by NDT Methods: A Review
by Sujeet Choudhary, Manish Vishwakarma and Sandeep Kumar Dwivedi
Mater. Proc. 2021, 6(1), 18; https://doi.org/10.3390/CMDWC2021-10044 - 14 May 2021
Cited by 4 | Viewed by 4695
Abstract
This paper comprises of hydrogen embrittlement phenomena in material, factors responsible for the hydrogen embrittlement and non-destructive methods to evaluate the internal defect in machines or components when working in hydrogen atmosphere. Hydrogen embrittlement is responsible for sub-critical crack growth in materials, fracture [...] Read more.
This paper comprises of hydrogen embrittlement phenomena in material, factors responsible for the hydrogen embrittlement and non-destructive methods to evaluate the internal defect in machines or components when working in hydrogen atmosphere. Hydrogen embrittlement is responsible for sub-critical crack growth in materials, fracture and mechanical properties such as ductility, toughness, and consequently loss of strength. This hydrogen is induced into the material during electrochemical reactions and in a high-pressure hydrogen gas environment. The paper covers the review on the capabilities of non-destructive testing methods regarding advantages and disadvantages. Sometimes one non-destructive technique does not provide sufficient information about physical integrity and therefore a different combination of methods is required. Ultrasonic testing is very useful to detect internal defects. Full article
(This article belongs to the Proceedings of The 1st Corrosion and Materials Degradation Web Conference)
15 pages, 6396 KiB  
Article
Taguchi S/N and TOPSIS Based Optimization of Fused Deposition Modelling and Vapor Finishing Process for Manufacturing of ABS Plastic Parts
by Jasgurpreet Singh Chohan, Raman Kumar, TH Bhatia Singh, Sandeep Singh, Shubham Sharma, Jujhar Singh, Mozammel Mia, Danil Yurievich Pimenov, Somnath Chattopadhyaya, Shashi Prakash Dwivedi and Wojciech Kapłonek
Materials 2020, 13(22), 5176; https://doi.org/10.3390/ma13225176 - 17 Nov 2020
Cited by 91 | Viewed by 3342
Abstract
Despite several additive manufacturing techniques are commercially available in market, Fused Deposition Modeling (FDM) is increasingly used by researchers and engineers for new product development. FDM is an established process with a plethora of advantages, but the visible surface roughness (SR), being an [...] Read more.
Despite several additive manufacturing techniques are commercially available in market, Fused Deposition Modeling (FDM) is increasingly used by researchers and engineers for new product development. FDM is an established process with a plethora of advantages, but the visible surface roughness (SR), being an intrinsic limitation, is major barrier against utilization of fabricated parts for practical applications. In the present study, the chemical finishing method, using vapour of acetone mixed with heated air, is being used. The combined impact of orientation angle, finishing temperature and finishing time has been studied using Taguchi and ANOVA, whereas multi-criteria optimization is performed using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The surface finish was highly responsive to increase in temperature while orientation angle of 0° yielded maximum strength; increase in finishing time led to weight gain of FDM parts. As the temperature increases, the percentage change in surface roughness increases as higher temperature assists the melt down process. On the other hand, anisotropic behaviour plays a major role during tensile testing. The Signal-to-noise (S/N) ratio plots, and ANOVA results indicated that surface finish is directly proportionate to finishing time because a longer exposure results in complete layer reflowing and settlement. Full article
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18 pages, 1608 KiB  
Article
Mechanical Strength Enhancement of 3D Printed Acrylonitrile Butadiene Styrene Polymer Components Using Neural Network Optimization Algorithm
by Jasgurpreet Singh Chohan, Nitin Mittal, Raman Kumar, Sandeep Singh, Shubham Sharma, Jujhar Singh, Kalagadda Venkateswara Rao, Mozammel Mia, Danil Yurievich Pimenov and Shashi Prakash Dwivedi
Polymers 2020, 12(10), 2250; https://doi.org/10.3390/polym12102250 - 30 Sep 2020
Cited by 98 | Viewed by 5042
Abstract
Fused filament fabrication (FFF), a portable, clean, low cost and flexible 3D printing technique, finds enormous applications in different sectors. The process has the ability to create ready to use tailor-made products within a few hours, and acrylonitrile butadiene styrene (ABS) is extensively [...] Read more.
Fused filament fabrication (FFF), a portable, clean, low cost and flexible 3D printing technique, finds enormous applications in different sectors. The process has the ability to create ready to use tailor-made products within a few hours, and acrylonitrile butadiene styrene (ABS) is extensively employed in FFF due to high impact resistance and toughness. However, this technology has certain inherent process limitations, such as poor mechanical strength and surface finish, which can be improved by optimizing the process parameters. As the results of optimization studies primarily depend upon the efficiency of the mathematical tools, in this work, an attempt is made to investigate a novel optimization tool. This paper illustrates an optimization study of process parameters of FFF using neural network algorithm (NNA) based optimization to determine the tensile strength, flexural strength and impact strength of ABS parts. The study also compares the efficacy of NNA over conventional optimization tools. The advanced optimization successfully optimizes the process parameters of FFF and predicts maximum mechanical properties at the suggested parameter settings. Full article
(This article belongs to the Section Polymer Processing and Engineering)
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