Experimental Analyses and Predictive Modelling of Ultrasonic Welding Parameters for Enhancing Smart Textile Fabrication
This study aims to illustrate the design, fabrication, and optimisation of an ultrasonic welding (UW) machine to join copper wires with non-woven PVC textiles as smart textiles. The study explicitly evaluates UW parameters’ impact on heat generation, joint strength, and electrical properties, with a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/5/1488 |
| _version_ | 1797263891397345280 |
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| author | Mohamed Baraya Mohamed S. El-Asfoury Omnia O. Fadel Ahmed Abass |
| author_facet | Mohamed Baraya Mohamed S. El-Asfoury Omnia O. Fadel Ahmed Abass |
| author_sort | Mohamed Baraya |
| collection | DOAJ |
| description | This study aims to illustrate the design, fabrication, and optimisation of an ultrasonic welding (UW) machine to join copper wires with non-woven PVC textiles as smart textiles. The study explicitly evaluates UW parameters’ impact on heat generation, joint strength, and electrical properties, with a comprehensive understanding of the process dynamics and developing a predictive model applicable to smart textiles. The methodological approach involved designing and manufacturing an ultrasonic piezoelectric transducer using ABAQUS finite element analyses (FEA) software and constructing a UW machine for the current purpose. The full factorial design (FFD) approach was employed in experiments to systematically assess the influence of welding time, welding pressure, and copper wire diameter on the produced joints. Experimental data were meticulously collected, and a backpropagation neural network (BPNN) model was constructed based on the analysis of these results. The results of the experimental investigation provided valuable insights into the UW process, elucidating the intricate relationship between welding parameters and heat generation, joint strength, and post-welding electrical properties of the copper wires. This dataset served as the basis for developing a neural network model, showcasing a high level of accuracy in predicting welding outcomes compared to the FFD model. The neural network model provides a valuable tool for controlling and optimising the UW process in the realm of smart textile production. |
| first_indexed | 2024-04-25T00:20:13Z |
| format | Article |
| id | doaj.art-87d23c096c744c16aeb111c36b193725 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-25T00:20:13Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-87d23c096c744c16aeb111c36b1937252024-03-12T16:54:57ZengMDPI AGSensors1424-82202024-02-01245148810.3390/s24051488Experimental Analyses and Predictive Modelling of Ultrasonic Welding Parameters for Enhancing Smart Textile FabricationMohamed Baraya0Mohamed S. El-Asfoury1Omnia O. Fadel2Ahmed Abass3Department of Production Engineering and Mechanical Design, Faculty of Engineering, Port Said University, Port Fuad 42526, EgyptDepartment of Production Engineering and Mechanical Design, Faculty of Engineering, Port Said University, Port Fuad 42526, EgyptDepartment of Production Engineering and Mechanical Design, Faculty of Engineering, Port Said University, Port Fuad 42526, EgyptDepartment of Production Engineering and Mechanical Design, Faculty of Engineering, Port Said University, Port Fuad 42526, EgyptThis study aims to illustrate the design, fabrication, and optimisation of an ultrasonic welding (UW) machine to join copper wires with non-woven PVC textiles as smart textiles. The study explicitly evaluates UW parameters’ impact on heat generation, joint strength, and electrical properties, with a comprehensive understanding of the process dynamics and developing a predictive model applicable to smart textiles. The methodological approach involved designing and manufacturing an ultrasonic piezoelectric transducer using ABAQUS finite element analyses (FEA) software and constructing a UW machine for the current purpose. The full factorial design (FFD) approach was employed in experiments to systematically assess the influence of welding time, welding pressure, and copper wire diameter on the produced joints. Experimental data were meticulously collected, and a backpropagation neural network (BPNN) model was constructed based on the analysis of these results. The results of the experimental investigation provided valuable insights into the UW process, elucidating the intricate relationship between welding parameters and heat generation, joint strength, and post-welding electrical properties of the copper wires. This dataset served as the basis for developing a neural network model, showcasing a high level of accuracy in predicting welding outcomes compared to the FFD model. The neural network model provides a valuable tool for controlling and optimising the UW process in the realm of smart textile production.https://www.mdpi.com/1424-8220/24/5/1488ultrasonic weldingsmart textilescopper wire joiningartificial neural network (ANN)full factorial experimental design (FFD) |
| spellingShingle | Mohamed Baraya Mohamed S. El-Asfoury Omnia O. Fadel Ahmed Abass Experimental Analyses and Predictive Modelling of Ultrasonic Welding Parameters for Enhancing Smart Textile Fabrication Sensors ultrasonic welding smart textiles copper wire joining artificial neural network (ANN) full factorial experimental design (FFD) |
| title | Experimental Analyses and Predictive Modelling of Ultrasonic Welding Parameters for Enhancing Smart Textile Fabrication |
| title_full | Experimental Analyses and Predictive Modelling of Ultrasonic Welding Parameters for Enhancing Smart Textile Fabrication |
| title_fullStr | Experimental Analyses and Predictive Modelling of Ultrasonic Welding Parameters for Enhancing Smart Textile Fabrication |
| title_full_unstemmed | Experimental Analyses and Predictive Modelling of Ultrasonic Welding Parameters for Enhancing Smart Textile Fabrication |
| title_short | Experimental Analyses and Predictive Modelling of Ultrasonic Welding Parameters for Enhancing Smart Textile Fabrication |
| title_sort | experimental analyses and predictive modelling of ultrasonic welding parameters for enhancing smart textile fabrication |
| topic | ultrasonic welding smart textiles copper wire joining artificial neural network (ANN) full factorial experimental design (FFD) |
| url | https://www.mdpi.com/1424-8220/24/5/1488 |
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