Abstract
Smart textile is a new direction in the textile domain that aims to integrate technologies in designing and manufacturing functional textiles. Fabrics. The advancement of digital textile innovation is gaining ground in textile technology. A digital twin is a promising technology for the classical textile industry and smart garments. Digital twin combines various technologies such as IoT, cloud computing, and 3D simulation, bringing innovations to design, manufacture, and deliver high-quality fabrics. This chapter starts with an introduction that outlines the state of the art of textile technologies, digital textile innovation, and digital twin technology. Then two architectures for digital twins in the textile and fashion industries are presented. Moreover, this chapter sheds light on some possible applications and challenges of using digital twins in the textile industry.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Jones, D., Snider, C., Nassehi, A., Yon, J., Hicks, B.: Characterising the digital twin: a systematic literature review. CIRP J. Manuf. Sci. Technol. 29, 36–52 (2020)
Liu, S., Bao, J., Lu, Y., Li, J., Lu, S., Sun, X.: Digital twin modeling method based on biomimicry for machining aerospace components. J. Manuf. Syst. 58, 180–195 (2021)
Tao, F., Zhang, M., Liu, Y., Nee, A.Y.: Digital twin driven prognostics and health management for complex equipment. CIRP Ann. 67(1), 169–172 (2018)
Rasheed, A., San, O., Kvamsdal, T.: Digital twin: values, challenges and enablers from a modeling perspective. IEEE Access 8, 21980–22012 (2020)
Laaki, H., Miche, Y., Tammi, K.: Prototyping a digital twin for real time remote control over mobile networks: application of remote surgery. IEEE Access 7, 20325–20336 (2019)
Fernández-Ruiz, I.: Computer modelling to personalize bioengineered heart valves. Nat. Rev. Cardiol. 15(8), 440–441 (2018)
Zhang, B., Korolj, A., Lai, B.F.L., Radisic, M.: Advances in organon-a-chip engineering. Nat. Rev. Mater. 3(8), 257–278 (2018)
Mukherjee, T., Debroy, T.: A digital twin for rapid qualification of 3D printed metallic components. Appl. Mater. Today 14, 59–65 (2019)
Knapp, G., Mukherjee, T., Zuback, J., Wei, H., Palmer, T., De, A., Debroy, T.: Building blocks for a digital twin of additive manufacturing. Acta Mater. 135, 390–399 (2017)
Yu, H., Miao, C., Leung, C., White, T.J.: Towards AI-powered personalization in MOOC learning. NPJ Sci. Learn. 2, 15 (2017)
Peng, H., Ma, S., Spector, J.M.: Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment. In: Foundations and Trends in Smart Learning, pp. 171–176. Springer, Cham, Switzerland (2019)
Adu, E.K., Poo, D.C.: Smart learning: a new paradigm of learning in the smart age. In: Proceedings of the International Conference on Teaching and Learning in Higher Education (TLHE). National University of Singapore, Singapore (2014)
Batty, M.: Digital twins. Environ. Plan. B, Urban Anal. City Sci. 45, 817–820 (2018)
Mohammadi, N., Taylor, J.E.: Smart city digital twins. In: Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI), Nov. 2017, pp. 1–5
Kent, L., Snider, C., Hicks, B.: Early stage digital-physical twinning to engage citizens with city planning and design. In: Proceedings of the IEEE Conference on Virtual Reality 3D User Interfaces (VR), March 2019, pp. 1014–1015
Joseph, A., Cvetkovic, M., Palensky, P.: Predictive mitigation of short term voltage instability using a faster than real-time digital replica. In: Proceedings of the IEEE PES Innovative Smart Grid Technologies Conference (ISGT-Eur.), Oct. 2018, pp. 1–6
Esch, J.: Prolog to aviation cyber physical systems: foundations for future aircraft and air transport. Proc. IEEE 101(8), 1831–1833 (2013)
Cheng, Z., Kuzmichev, V.E.: Digital twin and men’s underwear design. IOP Conf. Ser. Mater. Sci. Eng. (IOP Publishing) 012075 (2018)
Riedelsheimer, T., Dorfhuber, L., Stark, R.: User centered development of a digital twin concept with focus on sustainability in the clothing industry. Procedia CIRP 90, 660–665 (2020)
Ruhland, P., Li, Y., Coutandin, S., et al.: Production of hybrid tubular metal-fibre preforms: development of a digital twin for the draping process. Procedia CIRP 99, 437–442 (2021)
Zhang, S.C., Kuzmichev, V.E.: A method of selection the textile materials for virtual reconstruction. IOP Conf. Ser. Mater. Sci. Eng. (IOP Publishing) 811(1), 012008 (2020)
Kamppuri, T., Kallio, K., Mäkelä, S.M., Harlin, A.: Finland as a forerunner in sustainable and knowledge-based textile industry-Roadmap for 2035 (2021)
Peng, X., Kuzmichev, V.E.: Virtual method of predicting the accuracy of pattern blocks. IOP Conf. Ser. Mater. Sci. Eng. (IOP Publishing) 459(1), 012084 (2018)
Scheuermann, C., Binderberger, T., von Frankenberg, N., Werner, A.: Digital twin: a machine learning approach to predict individual stress levels in extreme environments. In: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers, pp. 657–664 (2020)
Zhang, Z., Zhu, Z., Zhang, J., Wang, J.: Construction of Intelligent Integrated Model Framework for the Workshop Manufacturing System Via Digital Twin (2021)
Hossain, M.., Shakhawat Hossain Rony, M., Faridul Hossain, K.M., Kawsar Hossain, M., Azharul Hossain, M., Zhou, Y.: Effective mechanical and chemical washing process in garment industries. Am. J. Appl. Phys. 2, 1–25 (2017)
Sarkar, P.: Garment Manufacturing Process from Fabric to Finished Product. https://www.onlineclothingstudy.com/2017/07/garment-manufacturing-process-fabric-to-fashion.html (2017)
Cassidy, T., Goswami, P.: Textile and Clothing Design Technology, p. 525. Taylor & Francis Group (2018)
Behera, B.K., Hari, P.K.: Woven Textile Structure, p. 462. Woodhead Publishing Series in Textiles (2010)
Ben Abdessalem, S., Azeiez, M., Mokhtar, S.: Knitted fabric faults: inspection, causes and solutions. Indian Text. J. 4, 40–48 (2009)
Rienzo, M.D., Meriggi, P., Rizzo, F., et al.: Textile technology for the vital signs monitoring in telemedicine and extreme environments. IEEE Trans. Inf. Technol. Biomed. 14, 711–717 (2010)
Billinghurst, M., Starner, T.: Wearable devices: new ways to manage informations. Computer 32, 57–64 (1999)
El-Sherif, M.A., Yuan, J., Macdiarmid, A.: Fiber optic sensors and smart fabrics. J. Intell. Mater. Syst. Struct. 11, 407–414 (2016). https://doi.org/10.1106/mknk-e482-gwug-0he7
Curone, D., Secco, E.L., Tognetti, A., et al.: Smart garments for emergency operators: the ProeTEX project. IEEE Trans. Inf. Technol. Biomed. 114, 694–701 (2010)
Hinduja, H., Kekkar, S., Chourasia, S., et al.: Industry 4.0 digital twin and its industrial applications. Int. J. Sci. Eng. Technol. 8, 1–7 (2020)
Mattila, H.: Yarn to fabric: intelligent textiles. In: Sinclair, R. (ed.) Textiles and Fashion, pp. 355–376. Elsevier (2015)
Grieves, M., Vickers, J.: Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems, pp. 85–113. Springer (2017)
Khajavi, S.H., Motlagh, N.H., Jaribion, A., Werner, L.C., Holmström, J.: Digital twin: vision, benefits, boundaries, and creation for buildings. IEEE Access 7, 147406–147419 (2019)
Grieves, M.: Digital twin: manufacturing excellence through virtual factory replication. https://www.researchgate.net/publication/275211047_Digital_Twin_Manufacturing_Excellence_through_Virtual_Factory_Replication (2017)
Barhanpurka, K., Barhanpurka, S.: Applications of big data in textile industry. Textile Value Chain. https://textilevaluechain.in/in-depth-analysis/articles/textile-articles/applications-of-big-data-in-textile-industry/ (2019)
Wang, Y., Kung, L., Byrd, T.A.: Big data analytics: understanding its capabilities and potential benefits for healthcare organizations. Technol. Forecast. Soc. Chang. 126, 3–13 (2018)
Lv, Y., Yue, X., Chen, Q., Wang, M.: Fabric defect detection with cartoon–texture decomposition. In: International Conference on Artificial Intelligence on Textile and Apparel, pp. 277–283. Springer, Cham (2018)
Tong, L., Zhou, X., Wen, J., Gao, C.: Optimal gabor filtering for the inspection of striped fabric. In: International Conference on Artificial Intelligence on Textile and Apparel, pp. 291–297. Springer, Cham (2018)
Gao, C., Zhou, J., Wong, W.K., Gao, T.: Woven fabric defect detection based on convolutional neural network for binary classification. In: International Conference on Artificial Intelligence on Textile and Apparel, pp. 307–313. Springer, Cham (2018)
Wang, F., Jin, X., Luo, W.: Intelligent cashmere/wool classification with convolutional neural network. In: International Conference on Artificial Intelligence on Textile and Apparel, pp. 17–25. Springer, Cham (2018)
Zeng, X., Xing, P.: Yarn quality prediction for spinning production using the improved apriori algorithms. In: International Conference on Artificial Intelligence on Textile and Apparel, pp. 27–36, Springer, Cham (2018)
Hui, C.L., Ng, S.F.: Predicting seam performance of commercial woven fabrics using multiple logarithm regression and artificial neural networks. Text. Res. J. 79(18), 1649–1657 (2009)
Abd Jelil, R.: Review of artificial intelligence applications in garment manufacturing. In: Artificial Intelligence for Fashion Industry in the Big Data Era, pp. 97–123. Springer, Singapore (2018)
Aivaliotis, P., Georgoulias, K., Chryssolouris, G.: The use of digital twin for predictive maintenance in manufacturing. Int. J. Comput. Integr. Manuf. 32(11), 1067–1080 (2019)
Leng, J., Yan, D., Liu, Q., Zhang, H., Zhao, G., Wei, L., Chen, X., et al.: Digital twin-driven joint optimisation of packing and storage assignment in large-scale automated high-rise warehouse product-service system. Int. J. Comput. Integr. Manuf. 1–18 (2019)
Liu, K., Zeng, X., Bruniaux, P., Tao, X., Kamalha, E., Wang, J.: Garment fit evaluation using machine learning technology. In: Artificial Intelligence for Fashion Industry in the Big Data Era, pp. 273–288. Springer, Singapore (2018)
Hong, Y., Zeng, X., Brunixaux, P., Chen, Y.: Evaluation of fashion design using artificial intelligence tools. In: Artificial Intelligence for Fashion Industry in the Big Data Era, pp. 245–256. Springer, Singapore (2018)
Ren, S., Hui, C.L.P., Choi, T.M.J.: AI-based fashion sales forecasting methods in big data era. In: Artificial Intelligence for Fashion Industry in the Big Data Era, pp. 9–26. Springer, Singapore (2018)
Pal, K.: Internet of things and blockchain technology in apparel manufacturing supply chain data management. Proc. Comput. Sci. 170, 450–457 (2020)
Fuller, A., Fan, Z., Day, C., Barlow, C.: Digital twin: enabling technologies, challenges and open research. IEEE Access 8, 108952–108971 (2020)
Barricelli, B.R., Casiraghi, E., Fogli, D.: A survey on digital twin: definitions, characteristics, applications, and design implications. IEEE Access 7, 167653–167671 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Alkhammash, E.H., Karaa, W.b.A., Bhouri, N., Abdessalem, S.B., Hassanien, A.E. (2022). Digital Twin Solutions for Textile Industry: Architecture, Services, and Challenges. In: Hassanien, A.E., Darwish, A., Snasel, V. (eds) Digital Twins for Digital Transformation: Innovation in Industry. Studies in Systems, Decision and Control, vol 423. Springer, Cham. https://doi.org/10.1007/978-3-030-96802-1_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-96802-1_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-96801-4
Online ISBN: 978-3-030-96802-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)