Industry 4.0 Revolution in Clothing and Apparel Sector: Smart Apparel Factory Proposal

Yıl 2019, Cilt: 10 Sayı: 37, 73 - 96, 01.04.2019

Ebru Gökalp Mert Onuralp Gökalp P. Erhan Eren

https://doi.org/10.5824/1309-1581.2019.2.005.x

Öz

Together with the latest technological innovations, the vision of the smart factory has been enabled in the light of the last industrial revolution called Industry 4.0. Industry 4.0 has an important potential to change all production processes and business models in the fashion and apparel sector, which is a labor-intensive sector called the locomotive sector of our country. Therefore, in order to survive in a challenging global competitive environment, the transition of the fashion and apparel industry from ordinary production facilities to smart factories is required to invest in Industry 4.0 technologies. However, it has been determined that the studies in the literature on how these relatively new technologies can affect the apparel industry are limited and not adequately covered. In this study, which was prepared in order to address this gap, firstly the current system analysis was carried in the production system of an ordinary garment factory. Then, a smart apparel factory was proposed as a new production system in line with the vision of Industry 4.0. After introducing the technological components of the proposed Smart Apparel Factory, innovative approaches developed based on these technological components are presented in a holistic way. Then, the benefits and challenges of the proposed Smart Apparel Factory were analyzed and the proposed progressive implementation plan for transition from the current situation to the smart apparel factory was given.

Anahtar Kelimeler

Digital Transformation Endüstri 4.0, Akıllı Fabrika, Hazır Giyim ve Konfeksiyon

Hazır Giyim ve Konfeksiyon Sektöründe Endüstri 4.0 Devrimi: Akıllı Konfeksiyon Fabrikası Önerisi

Öz

Son teknolojik yeniliklerle birlikte, Endüstri 4.0 olarak adlandırılan endüstriyel devrim ışığında akıllı fabrika vizyonunun gerçekleştirilmesine imkan sağlanmıştır. Endüstri 4.0, ülkemizin lokomotif sektörü olarak adlandırılan ve emek yoğun bir sektör olan hazır giyim ve konfeksiyon sektöründeki tüm üretim süreçlerini ve iş modellerini değiştirmek için önemli bir potansiyele sahiptir. Bu nedenle, çetin küresel rekabet ortamında ayakta kalabilmeleri için hazır giyim ve konfeksiyon endüstrisinin sıradan üretim tesislerinden akıllı fabrikalara geçişleri başlatılarak, Endüstri 4.0 teknolojilerine yatırım yapmasına ihtiyaç vardır. Ancak, nispeten yeni olan bu teknolojilerin hazır giyim ve konfeksiyon endüstrisini nasıl etkileyebileceğine dair literatürdeki çalışmaların sınırlı sayıda ve yeterli kapsamda olmadığı tespit edilmiştir. Bu eksikliği gidermek amacı ile hazırlanan bu çalışmada, öncelikle mevcut sistem analizi yapılarak, konfeksiyon fabrikalarında şu anda yürütülen sistem incelenmiş olup, ardından Endüstri 4.0 ve akıllı fabrika vizyonu doğrultusunda yeni bir üretim sistemi olarak akıllı konfeksiyon fabrikası önerilmiştir. Önerilen Akıllı Konfeksiyon Fabrikası’nın teknolojik bileşenlerine yer verildikten sonra, bu teknolojik altyapıyı temel alarak geliştirilen yenilikçi yaklaşımlar bütüncül bir şekilde sunulmuştur. Ayrıca, önerilen Akıllı Konfeksiyon Fabrikasının fayda ve zorlukları analiz edilmiş olup, mevcut durumdan akıllı konfeksiyon fabrikasına geçiş için önerilen aşamalı uygulama planına yer verilmiştir.

Anahtar Kelimeler

Dijital Dönüşüm, Endüstri 4.0, Akıllı Fabrika, Hazır Giyim ve Konfeksiyon

Kaynakça

• Azuma, R. T. (1997). A survey of augmented reality. Presence: Teleoperators & Virtual Environments, 6(4), 355–385.
• Chen, T., Wang, Y.-C., & Lin, Z. (2014). Predictive distant operation and virtual control of computer numerical control machines. Journal of Intelligent Manufacturing, 1–17.
• Cooray, P., & Rupasinghe, T. (2015). A Real Time Production Tracking and a Decision Support System (PTDSS): A Case Study from an Apparel Company.
• Deming, W. E. (1951). Elementary principles of the statistical control of quality: a series of lectures. Nippon Kagaku Gijutsu Remmei.
• Gil, P., Mateo, C., & Torres, F. (2014). 3D visual sensing of the human hand for the remote operation of a robotic hand. International Journal of Advanced Robotic Systems, 11(2), 26.
• Gökalp, E., Gökalp, M. O., & Eren, P. E. (2018). Industry 4.0 Revolution in Clothing and Apparel Factories: Apparel 4.0. Içinde Industry 4.0 from the MIS Perspective (ss. 169–183). Bern, Switzerland: Peter Lang.
• Gökalp, E., Şener, U., & Eren, P. E. (2017). Development of an assessment model for industry 4.0: Industry 4.0-MM. https://doi.org/10.1007/978-3-319-67383-7_10 in Computer and Information Science (C. 770).
• Gokalp, M. O., Kayabay, K., Akyol, M. A., Eren, P. E., & Kocyigit, A. (2016). Big Data for Industry 4.0: A Conceptual Framework. Içinde 2016 International Conference on Computational Science and Computational Intelligence (CSCI) (ss. 431–434). IEEE. https://doi.org/10.1109/CSCI.2016.0088
• Gökalp, M. O., Kayabay, K., Çoban, S., Yandık, Y. B., & Eren, P. E. (2019). Büyük Veri Çağında İşletmelerde Veri Bilimi.
• Grant, R. M. (1996). Toward a knowledge‐based theory of the firm. Strategic management journal, 17(S2), 109–122.
• Islam, M., Mohiuddin, H. M., Mehidi, S. H., & Sakib, N. (2014). An optimal layout design in an apparel industry by appropriate line balancing: A case study. Global Journal of Research In Engineering, 14(5).
• Jayatilake, H., & Rupasinghe, T. D. (y.y.). Implementing Industry 4.0 in the apparel industry; A study to design a customized smart apparel production plant.
• Jayatilake, H., & Withanaarachchi, A. S. (2016). Industry 4.0 in the Apparel-Manufacturing Sector: Opportunities for Sri Lanka.
• Juels, A. (2006). RFID security and privacy: A research survey. IEEE journal on selected areas in communications, 24(2), 381–394.
• Kagermann, H., Helbig, J., Hellinger, A., & Wahlster, W. (2013). Recommendations for Implementing the strategic initiative INDUSTRIE 4.0: securing the future of German manufacturing industry; final report of the Industrie 4.0 working group. Forschungsunion.
• Kayabay, K., Akyol, M. A., Gökalp, M. O., Koçyiğit, A., & Eren, P. E. (2018). Current Research Topics in Industry 4.0 and an Analysis of Prominent Frameworks. Içinde Industry 4.0 from the MIS Perspective (ss. 126–139). Bern, Switzerland: Peter Lang. https://doi.org/https://doi.org/10.3726/b15120
• Kayabay, K., Gokalp, M. O., Akyol, M. A., Eren, P. E., & Kocyigit, A. (2016). GELECEĞİN KURULUŞLARI İÇİN BÜYÜK VERİ: MEVCUT DURUM VE EĞİLİMLER.
• Kayabay, K., Gökalp, M. O., Eren, P. E., & Koçyiğit, A. (2018). [WiP] A Workflow and Cloud Based Service-Oriented Architecture for Distributed Manufacturing in Industry 4.0 Context. Içinde 2018 IEEE 11th Conference on Service-Oriented Computing and Applications (SOCA) (ss. 88–92). IEEE.
• Keung Kwok, S., & Wu, K. K. W. (2009). RFID-based intra-supply chain in textile industry. Industrial Management & Data Systems, 109(9), 1166–1178.
• Lee, J., Kao, H.-A., & Yang, S. (2014). Service innovation and smart analytics for industry 4.0 and big data environment. Procedia Cirp, 16, 3–8.
• Lisboa, H. B., de Oliveira Santos, L. A. R., Miyashiro, E. R., Sugawara, K. J., Miyagi, P. E., & Junqueira, F. (2013). 3D virtual environments for manufacturing automation. Içinde 22nd International Congress of Mechanical Engineering (COBEM 2013), University of São Paulo, Brazil November (ss. 3–7).
• McNeil, I. (2002). An encyclopedia of the history of technology. Routledge.
• Monostori, L. (2015). Cyber-physical production systems: roots from manufacturing science and technology. at-Automatisierungstechnik, 63(10), 766–776.
• Pham, A. (2009). E3: Microsoft shows off gesture control technology for Xbox 360. Los Angeles Times, 1.
• Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64–88.
• Porter, M. E., & Heppelmann, J. E. (2015). How smart, connected products are transforming companies. Harvard Business Review, 93(10), 96–114.
• Prasanna, K. R., & Hemalatha, M. (2012). RFID GPS and GSM based logistics vehicle load balancing and tracking mechanism. Procedia Engineering, 30, 726–729.
• Rajkumar, R., Lee, I., Sha, L., & Stankovic, J. (2010). Cyber-physical systems: the next computing revolution. Içinde Design Automation Conference (DAC), 2010 47th ACM/IEEE (ss. 731–736). IEEE.
• Sääski, J., Salonen, T., Liinasuo, M., Pakkanen, J., Vanhatalo, M., & Riitahuhta, A. (2008). Augmented reality efficiency in manufacturing industry: a case study. Içinde DS 50: Proceedings of NordDesign 2008 Conference, Tallinn, Estonia, 21.-23.08. 2008.
• Şener, U., Gökalp, E., & Eren, P. E. (2018). Toward A Maturity Model for Industry 4.0: A Systematic Literature Review. Içinde Industry 4.0 from the MIS Perspective (ss. 290–302). Bern, Switzerland: Peter Lang.
• Srivastava, S. K. (2016). Industry 4.0. Lucknow: BHU Engineer’s Alumni.
• Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of communication, 42(4), 73–93.
• Steven, A. (2000). Information systems: A management perspective. Addison-Wesley.
• Stoppa, M., & Chiolerio, A. (2014). Wearable electronics and smart textiles: a critical review. Sensors, 14(7), 11957–11992.
• Sveiby, K.-E. (2001). A knowledge-based theory of the firm to guide in strategy formulation. Journal of intellectual capital, 2(4), 344–358.
• TEA. (2018). http://www.tim.org.tr/. Tarihinde adresinden erişildi http://www.tim.org.tr/
• Von Solms, R., & Van Niekerk, J. (2013). From information security to cyber security. computers & security, 38, 97–102.
• World Economic Forum. (2016). The future of jobs: Employment, skills and workforce strategy for the fourth industrial revolution. World Economic Forum, Geneva, Switzerland.
• Zhang, Y., Huang, G. Q., Sun, S., & Yang, T. (2014). Multi-agent based real-time production scheduling method for radio frequency identification enabled ubiquitous shopfloor environment. Computers & Industrial Engineering, 76, 89–97.
• Zhong, R. Y., Dai, Q. Y., Qu, T., Hu, G. J., & Huang, G. Q. (2013). RFID-enabled real-time manufacturing execution system for mass-customization production. Robotics and Computer- Integrated Manufacturing, 29(2), 283–292.