Smartening and Digital Transformation Plan in the Industry based on Best Practices
محورهای موضوعی : IT Strategy
Mehdi Azadimotlagh
1
,
Reza Sharafdini
2
,
Zahra Salimi
3
,
Melika khosravi
4
,
Yekta Farzadkia
5
1 - Department of Computer Engineering, Faculty of Engineering of Jam, Persian Gulf University, Bushehr, Iran
2 - Department of Mathematics, , Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, Iran.
3 - Department of Computer Science, Faculty of Mathematical Sciences, Alzahra University, Tehran, Iran
4 - Department of Computer Science, Faculty of Mathematical Sciences, Alzahra University, Tehran, Iran
5 - Department of Computer Science, Faculty of Mathematical Sciences, Alzahra University, Tehran, Iran
کلید واژه: Smartening, Digital Transformation, Industry 4.0, Executive Plan,
چکیده مقاله :
Due to smart production, Industry 4.0 has become an essential paradigm in industry. This paradigm is looking for smartening and digital transformation in industries where its goal is not only technology upgrade but also integration of advanced technology such as Artificial Intelligence, Internet of Things, Cloud computing, Digital twins and simulation software, Big Data Processing, Blockchain, etc. in production processes for increasing efficiency, flexibility, and productivity in various sections of production. Research shows that smartening and digital transformation are essential to creating a competitive advantage in global markets and leadership in the coming decades. Neglecting this change of approach can lead to losing customers and sales markets. Unfortunately, despite its advantages, implementing the smart industry faces significant challenges that can hinder its achievement of goals. So, whether at the national or corporate level, benefiting from a cohesive program for smartening and digital transformation in any industry is essential. In this paper, based on research in more than 20 leading countries in the field of smart industry, a strategic plan for smartening and digital transformation in industries has been presented. By using this strategic plan, it is possible to overcome the challenges and reach the smart industry in various fields.
Due to smart production, Industry 4.0 has become an essential paradigm in industry. This paradigm is looking for smartening and digital transformation in industries where its goal is not only technology upgrade but also integration of advanced technology such as Artificial Intelligence, Internet of Things, Cloud computing, Digital twins and simulation software, Big Data Processing, Blockchain, etc. in production processes for increasing efficiency, flexibility, and productivity in various sections of production. Research shows that smartening and digital transformation are essential to creating a competitive advantage in global markets and leadership in the coming decades. Neglecting this change of approach can lead to losing customers and sales markets. Unfortunately, despite its advantages, implementing the smart industry faces significant challenges that can hinder its achievement of goals. So, whether at the national or corporate level, benefiting from a cohesive program for smartening and digital transformation in any industry is essential. In this paper, based on research in more than 20 leading countries in the field of smart industry, a strategic plan for smartening and digital transformation in industries has been presented. By using this strategic plan, it is possible to overcome the challenges and reach the smart industry in various fields.
[1] Mesías-Ruiz, G.A. and et al., Boosting precision crop protection towards agriculture 5.0 via machine learning and emerging technologies: A contextual review. Frontiers in Plant Science, 2023. 14.
[2] Jefroy, N., M. Azarian, and H. Yu, Moving from Industry 4.0 to Industry 5.0: What Are the Implications for Smart Logistics? Logistics, 2022. 6(2): p. 26.
[3] Geldes, C., Challenges of Industry 4.0 for companies in emerging economies. some inputs for the research. Journal of Technology Management & Innovation, 2023. 18(3): p. 3-4.
[4] Verma, D., Analysis of smart manufacturing technologies for industry using AI methods. Turkish Journal of Computer and Mathematics Education (Turcomat), 2018. 9(2): p. 529-540.
[5] Azadimotlagh, M., N. Jafari, and R. Sharafdini, Review on architecture and challenges in smart cities. Journal of Information Systems and Telecommunication, 2025. 13(1): p. 33-49.
[6] Khamsehand, A., M. Mirfallah Lialestani, and R. Radfar, Digital Transformation Model Based on Grounded Theory. Journal of Information Systems and Telecommunication (JIST), 2021. 9(4): p. 275-284.
[7] Dai, H.N. and et al., Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies. Enterprise Information Systems, 2019. 14(9–10): p. 1279-1303.
[8] Tsai, M.F. and et al., Smart Machinery Monitoring System with Reduced Information Transmission and Fault Prediction Methods Using Industrial Internet of Things. Mathematics, 2021. 9(1): p. 3.
[9] Sun, X., H. Yu, and W.D. Solvang, The application of Industry 4.0 technologies in sustainable logistics: a systematic literature review (2012–2020) to explore future research opportunities. Environmental Science and Pollution Research, 2022. 29: p. 9560-9591.
[10] Lee, E.A., The past, present and future of cyber-physical systems: a focus on models. Sensors, 2015. 15(3): p. 4837-4869.
[11] Tyagi, A.K. and N. Sreenath, Cyber Physical Systems: Analyses, challenges and possible solutions. Internet of Things and Cyber-Physical Systems, 2021. 1: p. 22-33.
[12] Li, H. and X. Zhang, Automation in construction: RFID-based wireless manufacturing for real-time management. Automation in Construction, 2011. 20(6): p. 742-752.
[13] Uckelmann, D., M. Harrison, and F. Michahelles, Architecting the Internet of Things. 2011, Berlin: Springer.
[14] Emerging Technologies & Innovation. MIT Technology Review.
[15] Mozaffariand, F., et al., Application of Machine Learning in the Telecommunications Industry: Partial Churn Prediction by Using a Hybrid Feature Selection Approach. Journal of Information Systems and Telecommunication (JIST), 2023. 11(4): p. 331-346.
[16] AzarkasbandSeyed, S. and H. Khasteh, Economic Impacts and Global Successes through the Internet of Everything (IoE) in the World Countries. Journal of Information Systems and Telecommunication (JIST), 2024. 12(3): p. 228-240.
[17] Erl, T., R. Puttini, and Z. Mahmood, Cloud Computing: Concepts, Technology & Architecture. 2013, Boston: Pearson.
[18] Kagermann, H., W. Wahlster, and J. Helbig, Recommendations for implementing the strategic initiative INDUSTRIE 4.0. 2013, acatech: Germany.
[19] Paprzycki, M., M. Ganzha, and K. Wasielewska, Agent-Based Simulation of Freight Distribution in the Context of Smart Cities. Scalable Computing: Practice and Experience (SCPE), 2020.
[20] Zhang, J., L. Chen, and M. Ahmed, Advanced Machine Learning Techniques for Predictive Maintenance in Industrial IoT Systems. Wireless Communications and Mobile Computing, 2022.
[21] Javaid, M. and et al., Blockchain technology applications for Industry 4.0: A literature-based review. Blockchain: Research and Applications, 2021. 2(4): p. 100027.
[22] Market Research & Business Strategy. Frost & Sullivan.
[23] Smagin, S.I. and A.V. Ometov, A Blockchain-Based Approach to Data Security in Distributed Systems, in Computational Science – ICCS 2018 (Lecture Notes in Computer Science, vol 10860), J. Dongarra, M. Taufer, and C. Kartsaklis, Editors. 2018, Springer.
[24] Bellavista, P., A. Corradi, and M. Di Felice, Advancements in IoT-Based Environmental Monitoring Systems Using Low-Cost Sensors. Sensors, 2023.
[25] Perno, M., L. Hvam, and A. Haug, Implementation of digital twins in the process industry: A systematic literature review of enablers and barriers. Computers in Industry, 2022. 134: p. 103558.
[26] International Telecommunication, U., Measuring digital development: Facts and figures. 2022, ITU Publications: Geneva.
[27] Wresearch, South Korea Smart Manufacturing Market Outlook. 2023, 6Wresearch: New Delhi, India.
[28] Siemens, A.G., Digital Industries and Industry 4.0. 2022, Siemens.
[29] Collins, L.M. and L.M. Smith, Review: Smart agri-systems for the pig industry. Animal, 2022. 16(Supplement 2): p. 100518.
[30] Kantaros, A. and et al., 3D printing: Making an innovative technology widely accessible through makerspaces and outsourced services. Materials Today: Proceedings, 2022. 49(Part 7): p. 2712-2723.
[31] Aliwi, I. and et al., The Role of Immersive Virtual Reality and Augmented Reality in Medical Communication: A Scoping Review. Journal of Patient Experience, 2023. 10.
[32] World Intellectual Property, O., Global Innovation Index 2023. 2023, WIPO: Geneva.
[33] 2023 State of Smart Manufacturing Study. Asia Manufacturing News Today, 2023.
[34] Counterpoint, R., Global Technology Market Overview Q1 2023. 2023.
[35] Acatech – National Academy of, S. and Engineering, Industrie 4.0 in Germany: Innovation and Implementation, in acatech Position Paper. 2022.
[36] Kumar, S. and R. Swarnkar, RFID technology in healthcare: A systematic review. International Journal of E-Health and Medical Communications, 2016. 7(2): p. 1-18.
[37] Stackpole, B., Industry turns up the dial on AI. 2025, Automation World.
[38] Google, C., The ROI of AI in manufacturing: The next wave of AI in manufacturing. 2025, Google Cloud Blog.
[39] Research, G.I.I., Smart manufacturing market size, share & growth analysis (2026-2034). 2026, GII/Facts & Factors.
[40] Wiegand, T. and M. Wynn, Sustainability, the Circular Economy and Digitalisation in the German Textile and Clothing Industry. Sustainability, 2023. 15(11).
[41] Sport, Business and Management: An International Journal. Sport, Business and Management: An International Journal, 2025.
[42] IEEE Sensors Journal. IEEE Sensors Journal, 2025.
[43] Recent Advances in Chemical Sensing. Sensors and Actuators B: Chemical, 2023.
[44] MarketsandMarkets, Global Industrial Automation Market—Forecast to 2025, in Market Report. 2023.
[45] Grand View, R., Smart Manufacturing Market Analysis Report. 2024.
[46] Advanced Materials. Advanced Materials, 2025.
[47] Hermann, M., T. Pentek, and B. Otto, Design principles for Industrie 4.0 scenarios: A literature review. Procedia CIRP, 2016. 52: p. 167-172.
[48] Carvalho, T.P., et al., A systematic literature review of machine learning methods applied to predictive maintenance. Computers & Industrial Engineering, 2019. 137: p. 106024.
[49] Hofmann, E. and M. Rüsch, Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry, 2017. 89: p. 23-34.
[50] Malaysia Investment Development, A., Malaysia Accelerates Tech Transformation with Industry4WRD. 2023.
[51] Edward, O.T., The Impact of the Fourth Industrial Revolution (IR 4.0) on Modern Civilisation in Malaysia, in BERNAMA News. 2023.
[52] Ghobakhloo, M., The future of manufacturing industry: a strategic roadmap toward Industry 4.0. Journal of Manufacturing Technology Management, 2018. 29(6): p. 910-936.
[53] Savastano, M. and et al., Contextual impacts on industrial processes brought by the digital transformation of manufacturing: a systematic review. Sustainability, 2019. 11(3): p. 891.
[54] Rosa, P., C. Sassanelli, and S. Terzi, Circular business models in the digital age: A review. Sustainability, 2020. 12(19): p. 7911.
[55] Manufacturing & Industrial News. Industry Today, 2024.
[56] Bibby, L. and B. Dehe, Defining and assessing industry 4.0 maturity levels – case of the defence sector. Production Planning & Control, 2018. 29(12): p. 1030-1043.
[57] Gumbi, L. and H. Twinomurinzi, Smme readiness for smart manufacturing (4IR) adoption: a systematic review. 2020. p. 41-54.
[58] Szász, L. and et al., Industry 4.0: a review and analysis of contingency and performance effects. Journal of Manufacturing Technology Management, 2020. 32(3): p. 667-694.
[59] Mittal, S. and et al., A critical review of smart manufacturing & industry 4.0 maturity models: implications for small and medium-sized enterprises (SMEs). Journal of Manufacturing Systems, 2018. 49: p. 194-214.
[60] Ghonim, H.M. and et al., The impact of lean practices on operational performance: an empirical investigation of manufacturing firms. International Journal of Productivity and Performance Management, 2020.
[61] Kumar, A., R. Chandramohan, and P. Sathishkumar, Thermal performance analysis of a parabolic trough solar collector using hybrid nanofluids: A numerical approach. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2021.
[62] Mayahi, A., F. Shams, and M.R. Meybodi, A novel hybrid machine learning model for predictive maintenance in Industry 4.0. Computers in Industry, 2020.
[63] Mittal, S., et al., Smart manufacturing: Characteristics, technologies and enabling factors. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2018. 233(5): p. 1342-1361.
[64] Khan, M.K., M.T. Sohail, and S.G. Hassan, Digital transformation and sustainable development: A bibliometric analysis. 2021.
[65] Chhikara, P. and et al., Data dimensionality reduction techniques for industry 4.0: research results, challenges, and future research directions. Software Practice and Experience, 2020. 52(3): p. 658-688.
[66] Jafari, N., M. Azarian, and H. Yu, Moving from industry 4.0 to industry 5.0: what are the implications for smart logistics? Logistics, 2022. 6(2): p. 26.
[67] Chandra, G.R., B.K. Sharma, and I.A. Liaqat, UAE’s Strategy Towards Most Cyber Resilient Nation. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 2019. 8(12).
[68] Boyes, H., et al., The industrial internet of things (IIoT): An analysis framework. Computers in Industry, 2018. 101: p. 1-12.
[69] Thun, M.J. and A.R. Hofer, Regulatory challenges for smart manufacturing in Europe: Harmonization and standardization of legal frameworks. Journal of European Industrial Policy, 2021. 14(3): p. 215-232.
[70] Stoppa, M. and A. Chiolerio, Wearable electronics and smart textiles: A critical review. Sensors, 2014. 14(7): p. 11957-11992.
[71] McKinsey and Company, The state of AI in manufacturing 2025. 2025, McKinsey Digital.
[72] Wireless, K., IoT insights & trends: What 2025 taught us. 2025, KORE Wireless.
[73] iFactory, A.I., Industry 4.0 readiness checklist for manufacturers in 2026. 2025, iFactory Blog.
[74] Huawei Cloud, B., NFC technology in electronic manufacturing: Efficiency and traceability. 2025, Huawei Cloud.
[75] Kamble, N.N. and N.K. Swamy, Integrated RFID-verified smart manufacturing system for bottle production using Industry 4.0. 2025, Springer.
[76] Paszkiewicz, A., RFID-enabled smart manufacturing: Real-time asset tracking and operational workflow optimization. 2025, Tehnički glasnik.
[77] World, R., 2025 RFID cost and implementation analysis. 2025, RFID World.
[78] Stoyanova, D., Industrial digitalization: Systematic literature review. 2025, Information.
[79] Cvetković, A. and et al., Internet of Things Security Aspects. Zbornik Radova Univerziteta Sinergija, 2020. 21(6).
[80] Adebayo, R., AI-enhanced manufacturing robotics: a review of applications and trends. World Journal of Advanced Research and Reviews, 2023. 21(3): p. 2060-2072.
[81] Anumbe, N., C. Saidy, and R. Harik, A primer on the factories of the future. Sensors, 2022. 22(15): p. 5834.
[82] Technologie News & Trends. Business Insider Deutschland.
[83] Official Mercedes-Benz Website. Mercedes-Benz.
[84] SFAW 2024: South Korea's pressing demand for automation and robotics, in Interact Analysis. 2024.
[85] Smart Manufacturing Summit 2024. Business France, 2024.
[86] Official Website. Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA).
[87] South Korea Smart Manufacturing Market Outlook, in 6Wresearch. 2024.
[88] U.S. Manufacturing Ecosystem Key to Economic Growth, in U.S. Department of Defense. 2023.
[89] U.S. Smart Manufacturing Market Report, in Grand View Research. 2023.
[90] Smart manufacturing trends, in AdvancedTech Blog. 2024.
[91] 6 (mostly digital) trends shaping manufacturing in 2024, in IndustryWeek. 2024.
[92] Indonesia Smart Cities Market Outlook to 2028, in Ken Research. 2024.
[93] Smart Cities in Indonesia – IoT Market Outlook. Statista, 2024.
[94] Azhar, M., Indonesia’s New Capital Nusantara to Become Tech‑Enabled Smart City. GovInsider.
[95] Editorial, I., Smart Manufacturing: Indonesia’s Strategy for Global Competitiveness in the Digital Age. INTIMEDIA.
[96] 5 Smart Technologies for 'Making Indonesia 4.0'. Suryacipta.
[97] Indonesia Digital Economy, in U.S. International Trade Administration.
[98] Malaysia Smart Manufacturing Opportunities, in International Trade Administration.
[99] Automation Project Initiative: Building a Smarter Future for Manufacturing. Malaysian Investment Development Authority (MIDA), 2023.
[100] NIMP 2030: Digitalisation Vital for Smart Factory Realisation, in Malaysian Investment Development Authority. 2023.
[101] Malaysia Digital Transformation: A Catalyst for Sustainable Progress, in World Economic Forum. 2024.
[102] Aiyedogbon, J.O., M.S. Gonzalez, and A.K. Mahmoud, Sustainable Urban Development Through Smart City Technologies: A Case Study of Emerging Economies. International Journal of Technology and Systems (IJTS), 2023. [103] Smith, E.J., D.R. Lee, and S.K. Johnson, Artificial Intelligence Applications in Modern Library Systems: Challenges and Opportunities. Journal of Librarianship and Information Science, 2021.
[104] Kumar, R., A. Sharma, and V. Singh, Enhancing Data Security in IoT Networks Using Machine Learning Algorithms. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 2021.
[105] Paprzycki, M., M. Ganzha, and K. Wasielewska, Agent-Based Modeling and Simulation for Smart Cities: A Case Study of Freight Distribution, in Intelligent Information and Database Systems. 2020, Springer.
[106] Consulting, M.H.P.M., Industry 4.0 Barometer 2026: Software-defined manufacturing. 2026, MHP/LMU Munich.
[107] Munich, M.L., Industry 4.0 Barometer 2026: Full Report. 2026, Hannover Messe.
[108] International Federation of, R., World Robotics 2025 Report. 2025, IFR.
[109] Bonafide, R., South Korea Smart Factory Market Overview, 2029. 2024, Bonafide Research.
[110] Grand View, R., South Korea Smart Factory Market Size & Outlook, 2025-2030. 2026, Grand View Research.
[111] Economy Middle, E., UAE's rapid adoption of Industry 4.0 technologies drives manufacturing growth. 2025, Economy Middle East.
[112] Zhavoronkov, A., Q. Vanhaelen, and T.I. Oprea, Will artificial intelligence for drug discovery impact clinical pharmacology? Clinical Pharmacology & Therapeutics, 2020. 107(4): p. 780-785.
[113] Drexler, M., Artificial Intelligence in Clinical Trials: Opportunities, Challenges, and Practical Considerations. Clinical Pharmacology & Therapeutics, 2020. 107(4): p. 712-715.
[114] Fighting Counterfeit Pharmaceuticals: Securing the Integrity of the Pharmaceutical Supply Chain, in PwC Strategy&. 2017.
[115] Wang, Y., X. Yu, and Y. Zhang, Sustainable pharmaceutical manufacturing: Towards green innovation and circular economy. Journal of Cleaner Production, 2022. 370: p. 133537.
[116] Gheorghiu, L. and L. Dumitrescu, Smart cold chain management for biologics using IoT technologies: A review. International Journal of Pharmaceutics, 2022. 616: p. 121626.
[117] Sharma, V. and R. Tripathi, Adoption of Industry 4.0 technologies in Indian pharmaceutical manufacturing: Challenges and opportunities. Journal of Manufacturing Technology Management, 2021. 32(8): p. 1650-1670.
[118] Patel, S. and M. Patel, Pharmaceutical supply chain optimization using ERP and analytics technologies. Computers in Industry, 2021. 130: p. 103469.
[119] Makhlouf, H. and M. Vincent, Artificial intelligence and big data analytics in drug discovery and clinical development. Drug Discovery Today, 2023. 28(3): p. 103422.
[120] Gates, B., The future of clinical trials is decentralized. Nature Medicine, 2020. 26: p. 1101-1102.
[121] Kumar, S. and E.M. Budin, Pharmaceutical supply chain management and cold chain logistics during the COVID-19 pandemic. Journal of Operations Management, 2022. 68(2): p. 245-260.
[122] Topol, E., High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 2019. 25(1): p. 44-56.
[123] Chen, Y. and H. Lee, The application of robotic process automation in regulatory compliance of pharmaceutical manufacturing. Regulatory Toxicology and Pharmacology, 2021. 123: p. 104964.
[124] Müller, S., R. Köhler, and A. Frings, Artificial Intelligence in the Chemical Industry, in McKinsey & Company. 2020.
[125] Wellener, P., B. Dollar, and S. Laaper, The Internet of Things in the Chemical Industry: Shaping the Future with Connected Operations, in Deloitte Insights. 2021.
[126] Green Chemistry Editorial, B., Green Chemistry: Sustainable Design for the Chemical Industry, in Royal Society of Chemistry. 2023.
[127] How Digitalization is Transforming the Chemical Industry, in BASF Magazine. 2022.
[128] CCUS in Clean Energy Transitions, in International Energy Agency (IEA Reports). 2020.
[129] Modular Production: The Future of Chemical Manufacturing, in Namur and ProcessNet, ProcessNet Publications. 2019.
[130] Franz, H., Fraunhofer-Gesellschaft: Bridging science and industrial application in Germany’s chemical sector. Journal of Technology Transfer, 2021. 46(2): p. 345-360.
[131] Müller, T. and J. Stein, From academia to entrepreneurship: The role of the Chemical Invention Factory at TU Berlin. Chemistry Today, 2022. 40(4): p. 18-22.
[132] Kuhn, A. and M. Becker, Global contributions of ETH Zurich and LBNL to chemical engineering research and innovation. International Journal of Chemical Engineering, 2023. 41(1): p. 12-26.
[133] Smith, R., The role of industry associations in advancing the U.S. chemical sector: A case study of ACS and ACC. Journal of Industrial Policy and Innovation, 2022. 8(3): p. 205-215.
[134] Johnson, L. and F. Perez, Regulatory frameworks for chemical safety: The impact of EPA and OSHA on industrial sustainability. Environmental Regulation Review, 2021. 17(2): p. 88-102.
[135] Wang, Y. and D. Song, Smart Manufacturing in China: Trends, Practices and Implications for the Chemical Industry. Journal of Manufacturing Technology Management, 2020.
[136] Liu, Y. and L. Zhang, China’s Roadmap to Intelligent and Sustainable Chemical Industry: Role of Research Institutes and Digital Innovation. Sustainability, 2022.
[137] Xu, X., C. Zhang, and G.H. Tzeng, Developing Smart Chemical Manufacturing Through University–Industry Collaboration: A Case Study of Tsinghua and ChemChina. Technological Forecasting and Social Change, 2021.
[138] Smart Clothing Market – Size, Share, Growth Analysis | Forecast (2024–2030), in Virtue Market Research. 2023.
[139] Smart Clothing Market Size, Share & Industry Analysis, in Fortune Business Insights. 2025.
[140] The Rise of Smart Clothing: Fashion, Fitness, Healthcare and Top Companies, in DataNext.ai. 2023.
[141] Zhao, L. and Y. Wang, AI and IoT-driven digital transformation in the apparel industry: A case study of Nike and Levi's. Journal of Fashion Technology & Textile Engineering, 2022. 10(3): p. 55-68.
[142] Cheng, R., 3D printing and AI in personalized fashion: Innovations from Adidas, Nike, and Hugo Boss. International Journal of Advanced Manufacturing Technology, 2023. 127(5): p. 912-925.
[143] Liu, J. and S. Meier, Circular economy practices in sportswear: The case of Adidas and Nike Flyknit. Journal of Cleaner Production, 2021. 298: p. 126830.
[144] Patel, K. and M. Fischer, The role of robotics in modern apparel manufacturing. Robotics and Computer-Integrated Manufacturing, 2022. 75: p. 102276.
[145] Neff, G., Augmented reality in fashion retail: Enhancing customer experience through virtual fitting rooms. Fashion and Retail Technologies, 2021. 6(2): p. 121-135.
[146] Singh, R. and D. Lee, Laser-based denim finishing: Sustainable innovation at Levi’s. Journal of Sustainable Fashion, 2020. 3(4): p. 202-214.
[147] Zhang, Y. and S. Kim, Smart textiles in wearable health: Integration of sensors in clothing. Materials Today, 2023. 59: p. 32-45.
[148] Baker, T. and N. Reddy, Real-time digital supply chains in fashion: A case of Levi’s transformation. Supply Chain Management Review, 2021. 27(6): p. 344-356.
[149] Zhang, Y. and M. Liu, Digital transformation and AI adoption in China’s textile industry. Journal of Industrial Innovation, 2023. 15(2): p. 85-97.
[150] Li, K., Revolutionizing Textiles: AI Drives China’s Industry Leap, in ODMYA News. 2024.
[151] A Glimpse of 'Smart' Textile Factory in China's Jiangsu, in Xinhua. 2024.
[152] Inside China's Clothing Manufacturing: A Deep Dive into its Evolution and Future, in Odmya. 2023.
[153] Lu, Y., Industry 4.0: A Survey on Technologies, Applications and Open Research Issues. Journal of Industrial Information Integration, 2017. 6: p. 1-10.
[154] Kagermann, H., W. Wahlster, and J. Helbig, Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0, in acatech - German National Academy of Science and Engineering. 2013.#3 [155] Sony, M. and S. Naik, Key Ingredients for Evaluating Industry 4.0 Readiness for Organizations: A Literature Review. Benchmarking: An International Journal, 2019. 27(8): p. 2545-2566.#3 [156] Schwab, K., The Fourth Industrial Revolution. World Economic Forum. 2016.
[157] Liao, Y., et al., Past, Present and Future of Industry 4.0: A Systematic Literature Review and Research Agenda. International Journal of Production Research, 2017. 55(12): p. 3609-3629.