Response surface methodology and artificial neural network modeling of work of adhesion on plasma-treated polyester–cotton-woven fabrics

Putra, Valentinus Galih Vidia; Mohamad, Juliany Ningsih

doi:10.1080/01694243.2022.2053349

Cited by 3 publications

(1 citation statement)

References 34 publications

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“…Artificial neural networks are intelligent devices that have been designed to improve the quality of mechanical research. A neural system is a promising information processing technique that is commonly employed in anticipating output [43]. The neural network is made up of three layers of neurons.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

Analysis of tensile strength on friction stir welded Al 6061 composite reinforced with B₄C and Cr₂O₃ using RSM and ANN

Uday

Rajamurugan²

2023

Eng. Res. Express

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Aluminum (Al) alloys are reinforced with carbides and oxides to enhance their properties. Al composites are developed to meet current automotive, shipbuilding, and aviation requirements. In the current study, aluminum 6061 is reinforced with B4C and Cr2O3 separately to fabricate Al6061 + B4C and Al 6061+Cr2O3 aluminum metal matrix composites (Al MMC). The Al composites were fabricated by stir casting with a wt % in steps of 2%, 4%, and 6%. Joining of Al MMC is essential to develop valuable components. The developed composites were welded using friction stir welding (FSW). FSW is recognized and widely used for joining Al MMC due to premium weld quality with minimum defects. The present study aims to analyze the effect of process parameters and predictive accuracy of the artificial neural network (ANN) and response surface methodology (RSM). The parameters selected for the study are tool rotational speed, tool travel speed, and reinforcement wt %. The FSW was performed based on the experimental design developed by the design expert software. Through RSM analysis, it was found that both the independent factors (tool rotational and tool transverse speed) and the interaction of factors jointly contribute to the FSW joint properties. The higher ultimate strength of 139 MPa and lower tensile strength of 48 MPa are found. As the tool travel speed increase from 20 to 25 mm\min, ultimate tensile strength increase about 59%. The average accuracy of RSM was 98.26 and of ANN was 94.86.

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Section: Artificial Neural Networkmentioning

confidence: 99%

Analysis of tensile strength on friction stir welded Al 6061 composite reinforced with B₄C and Cr₂O₃ using RSM and ANN

Uday

Rajamurugan²

2023

Eng. Res. Express

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Review of Plasma Surface Engineering Technology Toward Sustainable Textile Materials

Ssekasamba,

Tebyetekerwa,

Haodong

et al. 2024

Mater Circ Econ

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A mathematical model and microcontroller-based method for measuring dielectric permittivity and discharge characteristics with Arduino ATmega 328: a case study in a physics laboratory

Putra,

Ngadiyono

2023

Math. models, eng.

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A microcontroller-based measuring instrument and a new mathematical model are used to investigate capacitor permittivity and dielectric materials' charge-discharge characteristics. In this study, a prototype capacitive permittivity measurement apparatus for dielectric materials was carefully developed using an Arduino microcontroller, a resistor, and a capacitor. The experimental setup comprises a capacitor-resistor circuit, wherein a 5-volt power supply sourced from the microcontroller interfaces with a computer. During the charging process, a comprehensive evaluation of model-data alignment was performed, yielding values of 0.54252156, 0.9951, and 111.2508701 for the sum of squares error (SSE), the coefficient of determination (R-squared), and the sum of squares total (SST), respectively. Similarly, the analysis extended to the discharging process, unveiling values of 5.10174756, 0.962805684, and 137.1647082 for SSE, R-squared, and SST, respectively. These findings confirm the accuracy of the microcontroller that was programmed by incorporating a model in precisely measuring the relative permittivity of dielectric materials and capacitance values, with an R-squared value above 0.95 following capacitor literature benchmarks. The novelty of this study is that this configuration enabled the precise assessment of both permittivity and the charge-discharge characteristics of the dielectric materials within the capacitor. This methodology made it possible to accurately measure the permittivity and charge-discharge characteristics of dielectric materials within a capacitor. The scientific significance of this research lies in its ability to provide a carefully developed instrument capable of investigating the permittivity of dielectric materials and capacitor capacitance measurements. Scholars, international engineering communities, and academics can use this technological breakthrough to advance research into dielectric material properties and capacitor characteristics.

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Response surface methodology and artificial neural network modeling of work of adhesion on plasma-treated polyester–cotton-woven fabrics

Cited by 3 publications

References 34 publications

Analysis of tensile strength on friction stir welded Al 6061 composite reinforced with B₄C and Cr₂O₃ using RSM and ANN

Analysis of tensile strength on friction stir welded Al 6061 composite reinforced with B₄C and Cr₂O₃ using RSM and ANN

Review of Plasma Surface Engineering Technology Toward Sustainable Textile Materials

A mathematical model and microcontroller-based method for measuring dielectric permittivity and discharge characteristics with Arduino ATmega 328: a case study in a physics laboratory

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Response surface methodology and artificial neural network modeling of work of adhesion on plasma-treated polyester–cotton-woven fabrics

Cited by 3 publications

References 34 publications

Analysis of tensile strength on friction stir welded Al 6061 composite reinforced with B4C and Cr2O3 using RSM and ANN

Analysis of tensile strength on friction stir welded Al 6061 composite reinforced with B4C and Cr2O3 using RSM and ANN

Review of Plasma Surface Engineering Technology Toward Sustainable Textile Materials

A mathematical model and microcontroller-based method for measuring dielectric permittivity and discharge characteristics with Arduino ATmega 328: a case study in a physics laboratory

Contact Info

Product

Resources

About

Analysis of tensile strength on friction stir welded Al 6061 composite reinforced with B₄C and Cr₂O₃ using RSM and ANN

Analysis of tensile strength on friction stir welded Al 6061 composite reinforced with B₄C and Cr₂O₃ using RSM and ANN