The Experts below are selected from a list of 2106 Experts worldwide ranked by ideXlab platform
Thomas Gries - One of the best experts on this subject based on the ideXlab platform.
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Textile Science & Engineering
2020Co-Authors: Yvessimon Gloy, Thomas Gries, Wilfried Renkens, Herty M, Renkens ConsultingAbstract:Warp tension is a major parameter of the Weaving Process. The system analysis of a Weaving machine leads to a simulation model for calculating the warp yarn tension. Validation of the simulation has demonstrated that the results correspond well with the reality. In a second step, an improved model of this simulation was used in combination with a genetic algorithm and a gradient based method to calculate optimised setting parameters for the Weaving Process. A cost function was defined taken into account a desired course of the warp tension. It is known, that a low and constant warp tension course is suitable for Weaving. Using the genetic algorithm or the gradient based method leads to optimised Weaving machine parameters. Applying the optimised setting parameters on a loom demonstrated that the quality of the produced fabrics can be improved. Further analysis of produced fabrics did not show an influence of optimised Weaving machine parameters on the mechanical properties or productivity of the Weaving Process. Simulation and optimisation of warp tension in the Weaving Process
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integration of the vertical warp stop motion positioning in the model based self optimization of the Weaving Process
The International Journal of Advanced Manufacturing Technology, 2017Co-Authors: Yvessimon Gloy, Frederik James Marie Cloppenburg, Thomas GriesAbstract:The warp tension is a critical variable of the Weaving Process. If the warp tension is too high or too low, the Weaving Process will be interrupted. In order to find a suitable setting for the Weaving machine, the experience of the operator is needed. Self-optimization routines can support the operator in finding optimal settings. Within this paper, the model-based self-optimization of the Weaving Process developed at Institut fur Textiltechnik der RWTH Aachen University is presented. The self-optimization routine uses an automatic design of experiment to generate data for a full quadratic regression model of the characteristic values of the warp tension. Three weighted quality criteria are used to optimize the machine settings within given boundaries. An improvement is proposed by integrating the vertical warp stop motion position as a factor with high impact on the warp tension. The vertical warp stop motion position is automated and integrated into the optimization Process. The adjusted routine is validated on an air jet Weaving machine. The test results show that the integration of the warp stop motion position into a self-optimization routine leads to a 35% reduction of tension in the warp yarns. Compared to the existing routine, the integration of the warp stop motion position leads to a 23% higher effect on the warp tension as the target value of the optimization. The statistical validation shows that the quality of the used regression model is high. The described system also reduces the setup time of a Weaving machine. Economically, the improvements mean a reduction of production costs by 22%, when producing small lot sizes. The system therefore contributes to the competitiveness of Weaving mills in high-wage countries.
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Reduction of the Weaving Process Set-up Time through Multi-Objective Self-Optimization
Journal of Textile Science & Engineering, 2016Co-Authors: Marco Saggiomo, Y.s. Gloy, Thomas GriesAbstract:Real (physical) objects melt together with information-Processing (virtual) objects. These blends are called Cyber-Physical Production Systems (CPPS). The German government identifies this technological revolution as the fourth step of industrialization (Industry 4.0). Through embedding of intelligent, self-optimizing CPPS in Process chains, productivity of manufacturing companies and quality of goods can be increased. Textile producers especially in high-wage countries have to cope with the trend towards smaller lot sizes in combination with the demand for increasing product variations. One possibility to cope with these changing market trends consists in manufacturing with CPPS and cognitive machinery. This paper focuses on woven fabric production and presents a method for multiobjective self-optimization of the Weaving Process. Multi-objective self-optimization assists the operator in setting Weaving machine parameters according to the objective functions warp tension, energy consumption and fabric quality. Individual preferences of customers and plant management are integrated into the optimization routine. The implementation of desirability functions together with Nelder/Mead algorithm in a software-based Programmable Logic Controller (soft-PLC) is presented. The self-optimization routine enables a Weaving machine to calculate the optimal parameter settings autonomously. Set-up time is reduced by 75% and objective functions are improved by at least 14% compared to manual machine settings.
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Weaving machine as cyber-physical production system: Multi-objective self-optimization of the Weaving Process
2016 IEEE International Conference on Industrial Technology (ICIT), 2016Co-Authors: Marco Saggiomo, Y.s. Gloy, M. Kemper, Thomas GriesAbstract:Real (physical) objects melt together with information-Processing (virtual) objects. These blends are called Cyber-Physical Production Systems (CPPS). The German government identifies this technological revolution as the fourth step of industrialization (Industry 4.0). Through embedding of intelligent, self-optimizing CPPS in Process chains, productivity of manufacturing companies and quality of goods can be increased. Textile producers especially in high-wage countries have to cope with the trend towards smaller lot sizes in combination with the demand for increasing product variations. One possibility to cope with these changing market trends consists in manufacturing with CPPS and cognitive machinery. This paper focuses on woven fabric production and presents a method for multi-objective self-optimization of the Weaving Process. Multi-objective self-optimization assists the operator in setting Weaving machine parameters according to the objective functions warp tension, energy consumption and fabric quality. Individual preferences of customers and plant management are integrated into the optimization routine. The implementation of desirability functions together with Nelder/Mead algorithm in a software-based Programmable Logic Controller (soft-PLC) is presented. The self-optimization routine enables a Weaving machine to calculate the optimal parameter settings autonomously. Set-up time is reduced by 75 % and objective functions are improved by at least 14 % compared to manual machine settings.
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ICIT - Weaving machine as cyber-physical production system: Multi-objective self-optimization of the Weaving Process
2016 IEEE International Conference on Industrial Technology (ICIT), 2016Co-Authors: Marco Saggiomo, Yvessimon Gloy, M. Kemper, Thomas GriesAbstract:Real (physical) objects melt together with information-Processing (virtual) objects. These blends are called Cyber-Physical Production Systems (CPPS). The German government identifies this technological revolution as the fourth step of industrialization (Industry 4.0). Through embedding of intelligent, self-optimizing CPPS in Process chains, productivity of manufacturing companies and quality of goods can be increased. Textile producers especially in high-wage countries have to cope with the trend towards smaller lot sizes in combination with the demand for increasing product variations. One possibility to cope with these changing market trends consists in manufacturing with CPPS and cognitive machinery. This paper focuses on woven fabric production and presents a method for multi-objective self-optimization of the Weaving Process. Multi-objective self-optimization assists the operator in setting Weaving machine parameters according to the objective functions warp tension, energy consumption and fabric quality. Individual preferences of customers and plant management are integrated into the optimization routine. The implementation of desirability functions together with Nelder/Mead algorithm in a software-based Programmable Logic Controller (soft-PLC) is presented. The self-optimization routine enables a Weaving machine to calculate the optimal parameter settings autonomously. Set-up time is reduced by 75 % and objective functions are improved by at least 14 % compared to manual machine settings.
Yvessimon Gloy - One of the best experts on this subject based on the ideXlab platform.
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Textile Science & Engineering
2020Co-Authors: Yvessimon Gloy, Thomas Gries, Wilfried Renkens, Herty M, Renkens ConsultingAbstract:Warp tension is a major parameter of the Weaving Process. The system analysis of a Weaving machine leads to a simulation model for calculating the warp yarn tension. Validation of the simulation has demonstrated that the results correspond well with the reality. In a second step, an improved model of this simulation was used in combination with a genetic algorithm and a gradient based method to calculate optimised setting parameters for the Weaving Process. A cost function was defined taken into account a desired course of the warp tension. It is known, that a low and constant warp tension course is suitable for Weaving. Using the genetic algorithm or the gradient based method leads to optimised Weaving machine parameters. Applying the optimised setting parameters on a loom demonstrated that the quality of the produced fabrics can be improved. Further analysis of produced fabrics did not show an influence of optimised Weaving machine parameters on the mechanical properties or productivity of the Weaving Process. Simulation and optimisation of warp tension in the Weaving Process
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integration of the vertical warp stop motion positioning in the model based self optimization of the Weaving Process
The International Journal of Advanced Manufacturing Technology, 2017Co-Authors: Yvessimon Gloy, Frederik James Marie Cloppenburg, Thomas GriesAbstract:The warp tension is a critical variable of the Weaving Process. If the warp tension is too high or too low, the Weaving Process will be interrupted. In order to find a suitable setting for the Weaving machine, the experience of the operator is needed. Self-optimization routines can support the operator in finding optimal settings. Within this paper, the model-based self-optimization of the Weaving Process developed at Institut fur Textiltechnik der RWTH Aachen University is presented. The self-optimization routine uses an automatic design of experiment to generate data for a full quadratic regression model of the characteristic values of the warp tension. Three weighted quality criteria are used to optimize the machine settings within given boundaries. An improvement is proposed by integrating the vertical warp stop motion position as a factor with high impact on the warp tension. The vertical warp stop motion position is automated and integrated into the optimization Process. The adjusted routine is validated on an air jet Weaving machine. The test results show that the integration of the warp stop motion position into a self-optimization routine leads to a 35% reduction of tension in the warp yarns. Compared to the existing routine, the integration of the warp stop motion position leads to a 23% higher effect on the warp tension as the target value of the optimization. The statistical validation shows that the quality of the used regression model is high. The described system also reduces the setup time of a Weaving machine. Economically, the improvements mean a reduction of production costs by 22%, when producing small lot sizes. The system therefore contributes to the competitiveness of Weaving mills in high-wage countries.
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ICIT - Weaving machine as cyber-physical production system: Multi-objective self-optimization of the Weaving Process
2016 IEEE International Conference on Industrial Technology (ICIT), 2016Co-Authors: Marco Saggiomo, Yvessimon Gloy, M. Kemper, Thomas GriesAbstract:Real (physical) objects melt together with information-Processing (virtual) objects. These blends are called Cyber-Physical Production Systems (CPPS). The German government identifies this technological revolution as the fourth step of industrialization (Industry 4.0). Through embedding of intelligent, self-optimizing CPPS in Process chains, productivity of manufacturing companies and quality of goods can be increased. Textile producers especially in high-wage countries have to cope with the trend towards smaller lot sizes in combination with the demand for increasing product variations. One possibility to cope with these changing market trends consists in manufacturing with CPPS and cognitive machinery. This paper focuses on woven fabric production and presents a method for multi-objective self-optimization of the Weaving Process. Multi-objective self-optimization assists the operator in setting Weaving machine parameters according to the objective functions warp tension, energy consumption and fabric quality. Individual preferences of customers and plant management are integrated into the optimization routine. The implementation of desirability functions together with Nelder/Mead algorithm in a software-based Programmable Logic Controller (soft-PLC) is presented. The self-optimization routine enables a Weaving machine to calculate the optimal parameter settings autonomously. Set-up time is reduced by 75 % and objective functions are improved by at least 14 % compared to manual machine settings.
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model based self optimization of the Weaving Process
Cirp Journal of Manufacturing Science and Technology, 2015Co-Authors: Yvessimon Gloy, Florian Sandjaja, Thomas GriesAbstract:Abstract Warp tension is a critical variable of the Weaving Process. If the warp tension is too high or too low the Weaving Process will be interrupted. In order to find suitable setting for the Weaving machine, the experience of the operator or data base systems are used. Within this paper an automatic setup routine following model based self-optimization strategies is proposed. Within the routine, data for a regression model are collected by the Weaving machine. For given quality criteria the Weaving machine is able to calculate an optimal setting point. Validation of the routine shows that the chosen regression model is suitable; stress on the warp yarns is reduced. In addition, a statistical validation proves the usability of the regression models.
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Realization of an Automated Vertical Warp Stop Motion Positioning
Actuators, 2015Co-Authors: Frederik James Marie Cloppenburg, Yvessimon Gloy, Thomas GriesAbstract:The tension in the warp yarns is a critical variable in the Weaving Process. If the warp tension is too high or too low the Weaving Process will be interrupted. A parameter that directly affects the warp tension is the vertical warp stop motion position. The position of the warp stop motion must be set for every produced new article. The setting procedure is performed completely manual. In this paper we present a mechatronic modification of an air jet-Weaving machine to adjust the vertical warp stop motion position with the help of actuators. The parameters for the automated movement are determined and an open loop control, which uses a PLC, is proposed.
Damien Soulat - One of the best experts on this subject based on the ideXlab platform.
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Influence of 3D warp interlock fabrics parameters made with flax rovings on their final mechanical behaviour
Journal of Industrial Textiles, 2018Co-Authors: Anne-clémence Corbin, François Boussu, Manuela Ferreira, Damien SoulatAbstract:The three-dimensional Weaving Process enables to produce near-net shaped complex preforms used as reinforcement of composite materials. However, the lack of knowledge on the mechanical behaviour of...
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kinematic modelling of the Weaving Process applied to 2d fabric
Journal of Industrial Textiles, 2015Co-Authors: François Boussu, Jerome Vilfayeau, David Crépin, Damien Soulat, Philippe BoisseAbstract:A Weaving Process simulation of fabrics, used as fibrous reinforcements in composite applications, is presented in this article. The mechanical modelling of textile structures requires an accurate ...
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pedot pss based piezo resistive sensors applied to reinforcement glass fibres for in situ measurement during the composite material Weaving Process
Sensors, 2013Co-Authors: Nicolas Trifigny, François Boussu, Cédric Cochrane, Vladan Koncar, Fern M Kelly, Damien SoulatAbstract:The quality of fibrous reinforcements used in composite materials can be monitored during the Weaving Process. Fibrous sensors previously developed in our laboratory, based on PEDOT:PSS, have been adapted so as to directly measure the mechanical stress on fabrics under static or dynamic conditions. The objective of our research has been to develop new sensor yarns, with the ability to locally detect mechanical stresses all along the warp or weft yarn. This local detection is undertaken inside the Weaving loom in real time during the Weaving Process. Suitable electronic devices have been designed in order to record in situ measurements delivered by this new fibrous sensor yarn.
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Numerical modelling of the Weaving Process for textile composite
Key Engineering Materials, 2013Co-Authors: Jerome Vilfayeau, François Boussu, David Crépin, Damien Soulat, Philippe BoisseAbstract:Due to advancements made in 3D Weaving Process [1] and, in order to develop 3D textile structure as reinforcement of composite material for aeronautic application, a good prediction of the geometry and the mechanical properties of the 3D woven unit cell is required. Due to the complexity of these textile architectures, realistic geometric representations [2] of fabrics are often difficult to obtain especially for 3D woven fabrics, but these descriptions are necessary to define meshes for finite element computation [3]. At present, existing tools which model and define, early at a mesoscopic scale [4], the architecture of 3D fabrics don’t take into account the influence of the manufacturing Process on the shape modification of the textile structure. Some numerical model exists for the braiding Process [5] and the knitting Process [6], but not yet for the Weaving Process. During the manufacturing Process, fibres are subjected to significant deformations due to loads from the component of the loom or from the friction with the others fibres. These significant deformations lead to mechanical strength losses of the fabric. A numerical model of the different steps of the Weaving Process could predict these significant deformations and their influence on the geometry of the textile architecture. Thus, the objective of the NUMTISS project is to develop a numerical model of the deformation of the yarn during the Weaving Process. For the numerical modelling of the Weaving Process developed in finite element method, we considered all loom elements like rigid solid, and we will make the assumption that yarns are transverse isotropic elastic materials. Simulations of the Process for a plain weave, a twill 2-2 and a satin 8 fabric have already been performed, as well as the simulation of orthogonal warp interlock structures. Then, to understand the kinematic motions of Weaving Process, the tracking of some strategic elements on the industrial Weaving loom (reed, heddles, rapier,..) have been carried out. The tracking obtained from the video of the high speed camera will help us to define the numerical model of the Weaving kinematic closer to reality. Correlations between numerical results and specific structures in glass fibres produced on the loom will be presented. The influence of each step of the manufacturing Process on the characteristics of the textile structure could be analyzed [1]X. Chen, L. W. Taylor, L. J.Tsai. ”An overview on fabrication of three-dimensional woven textile preforms for composites”. Textile Research Journal, 2011, 81(9) 932–944 [2] SV Lomov, G Perie, DS Ivanov, I Verpoest and D Marsal. “Modeling three-dimensional fabrics and three-dimensional reinforced composites: challenges and solutions”. Textile Research Journal, 2011, 81(1) 28–41 [3] E. De Luycker, F. Morestin, P. Boisse, D. Marsal. « Simulation of 3D interlock composite performing”. Composite Structures, Volume 88, Issue 4, May 2009, Pages 615-623. [4] M. Ansar, W. Xinwei, Z. Chouwei. “Modeling strategies of 3D woven composites: A review”. Composite Structures 93 (2011) 1947–1963. [5] A. K. Pickett, J. Sirtautas, et A. Erber. « Braiding simulation and prediction of mechanical properties”. Applied Composite Materials, 2009. [6] M. Duhovic, D. Bhattacharyya. “Simulating the deformation mechanisms of knitted fabric composites”. Composites Part A : Applied Science and Manufacturing, 2006.
François Boussu - One of the best experts on this subject based on the ideXlab platform.
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Fibrous sensors to help the monitoring of Weaving Process
Smart Textiles and their Applications, 2020Co-Authors: François Boussu, N. Trifigny, Cédric Cochrane, Vladan KoncarAbstract:Abstract The observation of the kinematics of the Weaving Process has been done by several approaches. Firstly, a global view of the dynamic motions of the loom parts has been achieved by high-speed camera at different specific areas during the Weaving Process. Secondly, a local observation using an innovative sensor yarn has been also been performed during the Weaving Process. Dynamic measurements on the different loom locations have been conducted to detect the local distribution of elongation on different warp yarns, especially applied on two different tows counts of continuous E-glass yarns inserted into 3D warp interlock fabrics. Shed opening and Weaving reed beat-up steps have been confirmed as the most fibre degradation areas of the Weaving loom.
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Influence of 3D warp interlock fabrics parameters made with flax rovings on their final mechanical behaviour
Journal of Industrial Textiles, 2018Co-Authors: Anne-clémence Corbin, François Boussu, Manuela Ferreira, Damien SoulatAbstract:The three-dimensional Weaving Process enables to produce near-net shaped complex preforms used as reinforcement of composite materials. However, the lack of knowledge on the mechanical behaviour of...
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influence of 3d warp interlock fabric parameters on final geometry
Proceedings of the American Society for Composites: Thirty-First Technical Conference, 2016Co-Authors: François Boussu, Christophe Kerisit Caroline Chevalier, Daniel CoutellierAbstract:The exact geometry of 3D warp interlock fabric during production is highly dependent on the Weaving Process. Several fabric parameters as the number of layers, the weave diagram of linking warp yarns and the end and pick densities can influence the final geometry. Several fabrics have been produced on the same dobby Weaving machine using para-aramid yarns with different warp and weft densities. Thanks to these observations, differences between final geometries of 3D warp interlock fabric as the different position of yarn insertion and the cross-section shapes have been revealed.
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kinematic modelling of the Weaving Process applied to 2d fabric
Journal of Industrial Textiles, 2015Co-Authors: François Boussu, Jerome Vilfayeau, David Crépin, Damien Soulat, Philippe BoisseAbstract:A Weaving Process simulation of fabrics, used as fibrous reinforcements in composite applications, is presented in this article. The mechanical modelling of textile structures requires an accurate ...
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pedot pss based piezo resistive sensors applied to reinforcement glass fibres for in situ measurement during the composite material Weaving Process
Sensors, 2013Co-Authors: Nicolas Trifigny, François Boussu, Cédric Cochrane, Vladan Koncar, Fern M Kelly, Damien SoulatAbstract:The quality of fibrous reinforcements used in composite materials can be monitored during the Weaving Process. Fibrous sensors previously developed in our laboratory, based on PEDOT:PSS, have been adapted so as to directly measure the mechanical stress on fabrics under static or dynamic conditions. The objective of our research has been to develop new sensor yarns, with the ability to locally detect mechanical stresses all along the warp or weft yarn. This local detection is undertaken inside the Weaving loom in real time during the Weaving Process. Suitable electronic devices have been designed in order to record in situ measurements delivered by this new fibrous sensor yarn.
Frederik James Marie Cloppenburg - One of the best experts on this subject based on the ideXlab platform.
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integration of the vertical warp stop motion positioning in the model based self optimization of the Weaving Process
The International Journal of Advanced Manufacturing Technology, 2017Co-Authors: Yvessimon Gloy, Frederik James Marie Cloppenburg, Thomas GriesAbstract:The warp tension is a critical variable of the Weaving Process. If the warp tension is too high or too low, the Weaving Process will be interrupted. In order to find a suitable setting for the Weaving machine, the experience of the operator is needed. Self-optimization routines can support the operator in finding optimal settings. Within this paper, the model-based self-optimization of the Weaving Process developed at Institut fur Textiltechnik der RWTH Aachen University is presented. The self-optimization routine uses an automatic design of experiment to generate data for a full quadratic regression model of the characteristic values of the warp tension. Three weighted quality criteria are used to optimize the machine settings within given boundaries. An improvement is proposed by integrating the vertical warp stop motion position as a factor with high impact on the warp tension. The vertical warp stop motion position is automated and integrated into the optimization Process. The adjusted routine is validated on an air jet Weaving machine. The test results show that the integration of the warp stop motion position into a self-optimization routine leads to a 35% reduction of tension in the warp yarns. Compared to the existing routine, the integration of the warp stop motion position leads to a 23% higher effect on the warp tension as the target value of the optimization. The statistical validation shows that the quality of the used regression model is high. The described system also reduces the setup time of a Weaving machine. Economically, the improvements mean a reduction of production costs by 22%, when producing small lot sizes. The system therefore contributes to the competitiveness of Weaving mills in high-wage countries.
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Realization of an Automated Vertical Warp Stop Motion Positioning
Actuators, 2015Co-Authors: Frederik James Marie Cloppenburg, Yvessimon Gloy, Thomas GriesAbstract:The tension in the warp yarns is a critical variable in the Weaving Process. If the warp tension is too high or too low the Weaving Process will be interrupted. A parameter that directly affects the warp tension is the vertical warp stop motion position. The position of the warp stop motion must be set for every produced new article. The setting procedure is performed completely manual. In this paper we present a mechatronic modification of an air jet-Weaving machine to adjust the vertical warp stop motion position with the help of actuators. The parameters for the automated movement are determined and an open loop control, which uses a PLC, is proposed.