Strength Improvement of Additive Manufacturing Components by Reinforcing Carbon Fiber and by Employing Bioinspired Interlock Sutures

Selvam, Arivazhagan; Mayilswamy, Suresh; Whenish, Ruban

doi:10.1002/vnl.21766

Cited by 28 publications

(15 citation statements)

References 43 publications

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“…For instance, it was observed that the infill density and layer thickness have significantly influenced the tensile strength of ABS polymer 16 . High infill density gives high tensile strength and good surface characteristics for PETG material 17 . Apart from changes in internal process parameters, some external changes were also considered to obtain the expected mechanical performance of printed material by adding carbon fibers (short/lengthy) along with polymers 18 .…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization and prediction of surface roughness and printing time in FFF printed ABS polymer

Selvam

Mayilswamy

Whenish

et al. 2022

Sci Rep

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In this study, fused filament fabrication (FFF) printing parameters were optimized to improve the surface quality and reduce the printing time of Acrylonitrile Butadiene Styrene (ABS) polymer using the Analysis of Variance (ANOVA), it is a statistical analysis tool. A multi-objective optimization technique was employed to predict the optimum process parameter values using particle swarm optimization (PSO) and response surface methodology (RSM) techniques. Printing time and surface roughness were analyzed as a function of layer thickness, printing speed and nozzle temperature. A central composite design was preferred by employing the RSM method, and experiments were carried out as per the design of experiments (DoE). To understand the relationship between the identified input parameters and the output responses, several mathematical models were developed. After validating the accuracy of the developed regression model, these models were then coupled with PSO and RSM to predict the optimum parameter values. Moreover, the weighted aggregated sum product assessment (WASPAS) ranking method was employed to compare the RSM and PSO to identify the best optimization technique. WASPAS ranking method shows PSO has finer optimal values [printing speed of 125.6 mm/sec, nozzle temperature of 221 °C and layer thickness of 0.29 mm] than the RSM method. The optimum values were compared with the experimental results. Predicted parameter values through the PSO method showed high surface quality for the type of the surfaces, i.e., the surface roughness value of flat upper and down surfaces is approximately 3.92 µm, and this value for the other surfaces is lower, which is approximately 1.78 µm, at a minimum printing time of 24 min.

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Section: Introductionmentioning

confidence: 99%

Multi-objective optimization and prediction of surface roughness and printing time in FFF printed ABS polymer

Selvam

Mayilswamy

Whenish

et al. 2022

Sci Rep

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“…The error % between the PSO predicted result and the experimental result showed that PSO is an effective method to achieve the required objective. 42 GA is used to predict the optimum squeeze casting process parameters on TS, hardness and surface roughness. To convert the objective functions to single objective, different weights are provided to each objective.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of alloying elements to enhance the wear resistance and impact strength of HCCI produced by furan sand mold

Dhayaneethi¹,

Anburaj

Selvam

2022

Proceedings of the Institution of Mechanical Engineers, Part E:

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High Chromium White Cast Iron (HCWCI) plays a major role in manufacturing of wear-resistant components. Due to unique wear resistance property, attribution to the additions of carbide forming elements, they have been used for mill liner applications. By varying the wt% of alloying elements such as Cr, Ti, and Mo, the wear resistance and impact strength of High Chromium Cast Iron (HCCI) can be increased. To enhance the wear resistance property according to Central Composite Design (CCD), 16 samples were fabricated by varying the wt% of alloying elements. To fabricate the samples, furan sand molds were prepared and used for the further casting process. The properties of Furan sand mold enhance the mechanical properties and reduce the mold rejection rate, production time, etc. To attain the optimum Wear Rate (WR) and Impact Strength (IS) value without dominance, optimization techniques such as Response Surface Methodological (RSM) and Particle swarm optimization (PSO) are employed to solve the multi-objective problem. The RSM and PSO predicted optimum solutions are compared by using the Weighted Aggregated Sum Product Assessment (WASPAS) ranking method. The WASPAS result revealed that when compared to the RSM result, the PSO predicted optimal wt% of chemical composition (22 wt % Cr, 3 wt % Ti, and 2.99 wt % Mo) gives the optimum WR value (53 mm3/min) and IS value (3.77 J). To validate the PSO result, experiments were carried out for the predicted wt% of alloying elements and tested. The difference between the PSO predicted result and experimental result is less than 5% error which clearly shows that PSO is an effective method to solve the multi-objective problem.

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“…20,21 The process starts with a 3D model, which is sliced by applying slicing algorithms with defined process parameters. [22][23][24] AM is a material-oriented manufacturing technology that has encouraged the minimal usage of material and energy. 25 AM has manifested several benefits -optimized material and energy usage, short supply chains, freeform design, optimized and light weight design, shape consolidation, multi-material processing, and minimal postprinting requirements.…”

Section: Introductionmentioning

confidence: 99%

A review on fabrication of 3D printed biomaterials using optical methodologies for tissue engineering applications

John¹,

Antony

Whenish

et al. 2022

Proc Inst Mech Eng H

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Human body comprises of different internal and external biological components. Human organs tend to fail due to continuous or sudden stress which leads to deterioration, failure, and dislocation. The choice of selection and fabrication of materials for tissue engineering play a key role in terms of suitability, sensitivity, and functioning with other organs as a replacement for failed organs. The progressive improvement of the additive manufacturing (AM) approach in healthcare made it possible to print multi-material and customized complex/intricate geometries in a layer-by-layer fashion. The customized or patient-specific implant fabrication can be easily produced with a high success rate due to the development of AM technologies with tailorable properties. The structural behavior of 3D printed biomaterials is a crucial factor in tissue engineering as they affect the functionality of the implants. Various techniques have been developed in appraising the important features and the effects of the subsequent design of the biomaterial implants. The behavior of the AM built biomaterial implants can be understood visually by an imaging system with a high spatial and spectral resolution. This review intends to present an overview of various biomaterials used in implants, followed by a detailed description of optical 3D printing procedures and evaluation of the performance of 3D printed biomaterials using optical characterization.

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Strength Improvement of Additive Manufacturing Components by Reinforcing Carbon Fiber and by Employing Bioinspired Interlock Sutures

Cited by 28 publications

References 43 publications

Multi-objective optimization and prediction of surface roughness and printing time in FFF printed ABS polymer

Multi-objective optimization and prediction of surface roughness and printing time in FFF printed ABS polymer

Multi-objective optimization of alloying elements to enhance the wear resistance and impact strength of HCCI produced by furan sand mold

A review on fabrication of 3D printed biomaterials using optical methodologies for tissue engineering applications

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