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Article
Publication date: 1 August 2011

Farooq Assad and C. Cherif

The optimization of a process requires exact knowledge of the process, which is knowledge of correlations and inter-dependence between the process-determining variables…

Abstract

The optimization of a process requires exact knowledge of the process, which is knowledge of correlations and inter-dependence between the process-determining variables and the knowledge over the actual condition of the process. In a data rich knowledge poor process like spinning, where the exact relationships between machine, material, climate and quality are yet to be concluded objectively, this research focuses on the use of artificial neural networks as a tool to find out the correlations between decisive variables and to determine the optimum settings. Drawing frame is considered to be the last fault correction point in spinning preparation chain, therefore, its settings has a vital role to play towards yarn quality. Leveling action point is one of the important auto-leveling settings involving an automatic search function at Rieter drawing frame RSB-D40 and requiring a large amount of sliver. In this study, attempts were made to optimize the leveling action point. Optimization of draft settings is also within the scope of this article. The ANNs were used to achieve such objectives and they were found to be very helpful in identifying the optimum settings and hence decreasing material loss and improving sliver quality.

Details

Research Journal of Textile and Apparel, vol. 15 no. 3
Type: Research Article
ISSN: 1560-6074

Keywords

Book part
Publication date: 24 July 2020

Félix Orlando Martínez-Ríos, José Antonio Marmolejo-Saucedo and Gonzalo Abascal-Olascoaga

This chapter proposes a protocol based on blockchain technology applied to corporate social responsibility (CSR). The first part discusses the characteristics associated…

Abstract

This chapter proposes a protocol based on blockchain technology applied to corporate social responsibility (CSR). The first part discusses the characteristics associated with CSR actions and the main difficulties its development faces, such as transparency, security, fault tolerance, among others. Subsequently, the authors describe the characteristics and concepts related to blockchain-based developments to later describe our framework for the control and development of CSR actions based on blockchain. Herein, the authors also describe how to publicly and privately identify the participating elements of CSR and the operations and resources necessary for the implementation and operation of the proposed protocol.

Details

Strategy, Power and CSR: Practices and Challenges in Organizational Management
Type: Book
ISBN: 978-1-83867-973-6

Keywords

Open Access
Article
Publication date: 4 December 2017

Natalie Ishmael, Anura Fernando, Sonja Andrew and Lindsey Waterton Taylor

This paper aims to provide an overview of the current manufacturing methods for three-dimensional textile preforms while providing experimental data on the emerging…

5791

Abstract

Purpose

This paper aims to provide an overview of the current manufacturing methods for three-dimensional textile preforms while providing experimental data on the emerging techniques of combining yarn interlocking with yarn interlooping.

Design/methodology/approach

The paper describes the key textile technologies used for composite manufacture: braiding, weaving and knitting. The various textile preforming methods are suited to different applications; their capabilities and end performance characteristics are analysed.

Findings

Such preforms are used in composites in a wide range of industries, from aerospace to medical and automotive to civil engineering. The paper highlights how the use of knitting technology for preform manufacture has gained wider acceptance due to its flexibility in design and shaping capabilities. The tensile properties of glass fibre knit structures containing inlay yarns interlocked between knitted loops are given, highlighting the importance of reinforcement yarns.

Originality/value

The future trends of reinforcement yarns in knitted structures for improved tensile properties are discussed, with initial experimental data.

Details

Research Journal of Textile and Apparel, vol. 21 no. 4
Type: Research Article
ISSN: 1560-6074

Keywords

Article
Publication date: 18 April 2017

Donatas Petrulis and Salvinija Petrulyte

The purpose of this paper is to propose the materials structure-wetting behaviour relationships and to show their peculiarities for some types of surgical woven fabrics…

Abstract

Purpose

The purpose of this paper is to propose the materials structure-wetting behaviour relationships and to show their peculiarities for some types of surgical woven fabrics and applications of liquids.

Design/methodology/approach

To show the effects of fabrics structure on wetting behaviour of surgical textile materials, the special structural indices in terms of yarns and filaments lateral area were used.

Findings

It was shown good correlation between total lateral area of filaments in unit area of woven fabrics and wetting contact angle of liquid drops on the tested samples. Probably due to different structure of woven fabrics at a level of fibres, another index, i.e. total lateral area of yarns in unit area of fabrics, is not suitable to show clear effect on wetting behaviour of the samples. The possibilities of applications of relationships for several types of textile materials and liquids were indicated.

Originality/value

To date there are no investigations concerning relationships between special structural properties of the surgical woven fabrics and their wetting behaviour. On a basis of the proposed approach into fabrics structure evaluation, this study developed analysis and some types of new equations for prediction of wetting contact angle of the materials.

Details

International Journal of Clothing Science and Technology, vol. 29 no. 2
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 23 April 2020

Duc Hai Nguyen, Hu Wang, Fan Ye and Wei Hu

The purpose of this paper is to investigate the mechanical properties’ behaviors of woven composite cut-out structures with specific parameters. Because of the complexity…

Abstract

Purpose

The purpose of this paper is to investigate the mechanical properties’ behaviors of woven composite cut-out structures with specific parameters. Because of the complexity of micro-scale and meso-scale structure, it is difficult to accurately predict the mechanical material behavior of woven composites. Numerical simulations are increasingly necessary for the design and optimization of test procedures for composite structures made by the woven composite. The results of the proposed method are well satisfied with the results obtained from the experiment and other studies. Moreover, parametric studies on different plates based on the stacking sequences are investigated.

Design/methodology/approach

A multi-scale modeling approach is suggested. Back-propagation neural networks (BPNN), radial basis function (RBF) and least square support vector regression are integrated with efficient global optimization (EGO) to reduce the weight of assigned structure. Optimization results are verified by finite element analysis.

Findings

Compared with other similar studies, the advantage of the suggested strategy uses homogenized properties behaviors with more complex analysis of woven composite structures. According to investigation results, it can be found that 450/−450 ply-orientation is the best buckling load value for all the cut-out shape requirements. According to the optimal results, the BPNN-EGO is the best candidate for the EGO to optimize the woven composite structures.

Originality/value

A multi-scale approach is used to investigate the mechanical properties of a complex woven composite material architecture. Buckling of different cut-out shapes with the same area is surveyed. According to investigation, 45°/−45° ply-orientation is the best for all cut-out shapes. Different surrogate models are integrated in EGO for optimization. The BPNN surrogate model is the best choice for EGO to optimization difficult problems of woven composite materials.

Details

Engineering Computations, vol. 38 no. 3
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 14 April 2022

Ahmad Chihadeh and Michael Kaliske

This paper aims to introduce a method to couple truss finite elements to the material point method (MPM). It presents modeling reinforced material using MPM and describes…

Abstract

Purpose

This paper aims to introduce a method to couple truss finite elements to the material point method (MPM). It presents modeling reinforced material using MPM and describes how to consider the bond behavior between the reinforcement and the continuum.

Design/methodology/approach

The embedded approach is used for coupling reinforcement bars with continuum elements. This description is achieved by coupling continuum elements in the background mesh to the reinforcement bars, which are described using truss- finite elements. The coupling is implemented between the truss elements and the continuum elements in the background mesh through bond elements that allow for freely distributed truss elements independent of the continuum element discretization. The bond elements allow for modeling the bond behavior between the reinforcement and the continuum.

Findings

The paper introduces a novel method to include the reinforcement bars in the MPM applications. The reinforcement bars can be modeled without any constraints with a bond-slip constitutive model being considered.

Originality/value

As modeling of reinforced materials is required in a wide range of applications, a method to include the reinforcement into the MPM framework is required. The proposed approach allows for modeling reinforced material within MPM applications.

Details

Engineering Computations, vol. 39 no. 7
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 6 June 2016

Musa Akdere, Sascha Schriever, Gunnar Seide and Thomas Gries

The wet-spinning process is very important for the development and production of new lightweight design materials. The washing process is determined as one of the most…

Abstract

Purpose

The wet-spinning process is very important for the development and production of new lightweight design materials. The washing process is determined as one of the most cost-expensive part of wet spinning. The purpose of this paper is to show the development of a new washing concept. It proposes to increase the washing performance by decreasing fiber-fiber-interfaces during the washing process.

Design/methodology/approach

For this purpose, conventional washing concepts are investigated by means of simulations and experiments to obtain process knowledge. Computational fluid dynamics simulation and particle image velocimetry measurements are used to investigate the process.

Findings

The overall deficit in conventional washing methods is the large number of fiber-fiber-interfaces, which inhibit the solvent transport out of the compact fiber bundle. Therefore, a new washing concept with included water nozzles is developed. Based on the simulations and observations it is found that the arrangement of the nozzles has direct influence on the fanning of the fiber bundle.

Originality/value

With increased fanning of the fiber bundle a more efficient solvent transport is expected. The developed washing box is a prosperous concept to achieve a higher washing performance during the wet-spinning process. The variable design of the washing box makes it possible to test different nozzle configurations and designs. In this paper the two most promising nozzle arrangements are shown and compared to each other.

Details

International Journal of Clothing Science and Technology, vol. 28 no. 3
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 13 December 2017

Shouyan Chen and Tie Zhang

The purpose of this paper is to reduce the strain and vibration during robotic machining.

Abstract

Purpose

The purpose of this paper is to reduce the strain and vibration during robotic machining.

Design/methodology/approach

An intelligent approach based on particle swarm optimization (PSO) and adaptive iteration algorithms is proposed to optimize the PD control parameters in accordance with robotic machining state.

Findings

The proposed intelligent approach can significantly reduce robotic machining strain and vibration.

Originality value

The relationship between robotic machining parameters is studied and the dynamics model of robotic machining is established. In view of the complexity of robotic machining process, the PSO and adaptive iteration algorithms are used to optimize the PD control parameters in accordance with robotic machining state. The PSO is used to optimize the PD control parameters during stable-machining state, and the adaptive iteration algorithm is used to optimize the PD control parameters during cut-into state.

Details

Industrial Robot: An International Journal, vol. 45 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 26 May 2022

Mingwei Hu, Hongwei Sun, Liangchuang Liao and Jiajian He

The purpose of this paper is to introduce a method for stiffness modeling, identification and updating of collaborative robots (cobots). This method operates in real-time…

Abstract

Purpose

The purpose of this paper is to introduce a method for stiffness modeling, identification and updating of collaborative robots (cobots). This method operates in real-time and with high precision and can eliminate the modeling error between the actual stiffness model and the theoretical stiffness model.

Design/methodology/approach

To simultaneously ensure the computational efficiency and modeling accuracy of the stiffness model, this method introduces the finite element substructure method (FESM) into the virtual joint method (VJM). The stiffness model of the cobots is built by integrating several 6-degree of freedom virtual joints that represent the elastic deformation of the cobot modules, and the stiffness matrices of these modules can be identified and obtained by the FESM. A model-updating method is proposed to identify stiffness influence coefficients, which can eliminate the modeling error between the actual prototype model and the theoretical finite element model.

Findings

The average relative error and the cycle time of the proposed method are approximately 6.14% and 1.31 ms, respectively. Compared with other stiffness modeling methods, this method not only has high modeling accuracy in high dexterity poses but also in low dexterity poses.

Originality/value

A hybrid stiffness modeling method is introduced to integrate the modeling accuracy of the FESM into the VJM. Stiffness influence coefficients are proposed to eliminate the modeling error between the theoretical and actual stiffness models.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 12 April 2022

Monica Puri Sikka, Alok Sarkar and Samridhi Garg

With the help of basic physics, the application of computer algorithms in the form of recent advances such as machine learning and neural networking in textile Industry…

Abstract

Purpose

With the help of basic physics, the application of computer algorithms in the form of recent advances such as machine learning and neural networking in textile Industry has been discussed in this review. Scientists have linked the underlying structural or chemical science of textile materials and discovered several strategies for completing some of the most time-consuming tasks with ease and precision. Since the 1980s, computer algorithms and machine learning have been used to aid the majority of the textile testing process. With the rise in demand for automation, deep learning, and neural networks, these two now handle the majority of testing and quality control operations in the form of image processing.

Design/methodology/approach

The state-of-the-art of artificial intelligence (AI) applications in the textile sector is reviewed in this paper. Based on several research problems and AI-based methods, the current literature is evaluated. The research issues are categorized into three categories based on the operation processes of the textile industry, including yarn manufacturing, fabric manufacture and coloration.

Findings

AI-assisted automation has improved not only machine efficiency but also overall industry operations. AI's fundamental concepts have been examined for real-world challenges. Several scientists conducted the majority of the case studies, and they confirmed that image analysis, backpropagation and neural networking may be specifically used as testing techniques in textile material testing. AI can be used to automate processes in various circumstances.

Originality/value

This research conducts a thorough analysis of artificial neural network applications in the textile sector.

Details

Research Journal of Textile and Apparel, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1560-6074

Keywords

1 – 10 of 252