Digital twin
Digital twins are virtual representations of physical products, systems, or processes. They are created using digital models that mirror the characteristics and behavior of their real-world counterparts. These virtual twins are updated in real-time or periodically throughout the life-cycle of the product or system, capturing data and enabling analysis, simulation, and optimization. In the fashion industry, digital twins can be used to enhance various aspects of the product life-cycle, from design and production to retail and post-user stages.
Design and development
Digital twins can be used during the design phase to visualize and simulate garments or fashion collections. Designers can create virtual prototypes that closely resemble the physical products, allowing them to evaluate different design options, materials, and fit. This helps reduce the need for physical samples and iterations, saving time, cost, and resources.
Supply chain optimization
Digital twins enable real-time monitoring and optimization of supply chain processes in the fashion industry. By creating virtual representations of production facilities, logistics networks, and inventory systems, companies can simulate different scenarios, analyze performance, and identify opportunities for improvement. This helps optimize production planning, reduce waste, and enhance overall supply chain efficiency.
Personalized customer experience
Digital twins can be used to create virtual avatars or models that represent individual customers. By capturing data on body measurements, preferences, and style, companies can offer personalized recommendations for sizing, fit, and styling choices. This enhances the online shopping experience, reduces returns, and improves customer satisfaction.
Sustainability and circular economy
Digital twins facilitate the implementation of sustainable practices in the fashion industry. By capturing data on the materials used, energy utilization, and environmental impacts, companies can analyze and optimize the sustainability performance of their products. Digital twins can also aid in tracking and managing the entire life-cycle of garments, from production to recycling or upcycling, promoting circular economy practices.
Smart retail and inventory management
Digital twins can be utilized in retail stores to optimize inventory management and improve customer experience. By creating virtual representations of products and store layouts, companies can simulate and analyze customer flow, optimize shelf space, and forecast demand. This enables more efficient stock replenishment, reduces overstocking or understocking, and enhances the overall shopping experience.
Post-user engagement
Digital twins can be used to engage customers even after purchase. For example, by creating digital twins of fashion items in the hands of customers, companies can offer styling tips, care instructions, and customization options. This fosters a deeper connection with customers, promotes product longevity, and encourages sustainable utilization habits.
Overall, digital twins offer immense potential for the fashion industry by enabling virtual simulations, real-time monitoring, and optimization throughout the product life-cycle. They help enhance design, streamline supply chains, personalize customer experiences, promote sustainability, and improve overall operational efficiency
Case studies
Tommy Hilfiger’s digital showroom
Tommy Hilfiger implemented a digital twin-based virtual showroom that revolutionized their design and development process. Using 3D digital models and virtual simulations, designers and buyers could visualize and evaluate collections without the need for physical samples. This streamlined the design process, reduced costs, and accelerated time-to-market. More about Tommy Hilfiger’s Digital Showroom
Zara’s smart retail system
Zara, a global fashion retailer, utilizes digital twins and RFID technology to optimize inventory management and enhance the in-store shopping experience. Digital twins of garments are created and linked to RFID tags, enabling real-time tracking and monitoring of stock levels. This helps Zara to efficiently manage inventory, restock popular items, and provide customers with accurate information on product availability. More about Zara’s Smart Retail System
Levi’s virtual stylist
Levi’s introduced a virtual stylist powered by digital twins to enhance the online shopping experience. Customers can create a virtual avatar, input body measurements, and visualize how different Levi’s products would fit and look on them. This personalized experience helps customers make informed purchasing decisions, reducing returns and improving customer satisfaction. More about Levi’s Virtual Stylist
Adidas speedfactory
Adidas developed a digital twin-driven manufacturing process in their Speedfactory initiative. By creating digital twins of shoe designs, they were able to optimize production efficiency and customize footwear based on individual customer preferences. The digital twins enabled real-time monitoring and adjustments, resulting in faster production cycles and increased product personalization. More about Adidas Speedfactory
References
Botín-Sanabria, Diego M., et al. “Digital twin technology challenges and applications: A comprehensive review.” Remote Sensing 14.6 (2022): 1335.
Wagner, Ralf, and Agnieszka Kabalska. “Sustainable value in the fashion industry: A case study of value construction/destruction using digital twins.” Sustainable Development (2022).
Alam, Mohammed Didarul, Golam Kabir, and Mehdi Mirmohammadsadeghi. “A digital twin framework development for apparel manufacturing industry.” Decision Analytics Journal (2023): 100252.
Riedelsheimer, Theresa, Lisa Dorfhuber, and Rainer Stark. “User centered development of a Digital Twin concept with focus on sustainability in the clothing industry.” Procedia CIRP 90 (2020): 660-665.
Casciani, Daria, Olga Chkanikova, and Rudrajeet Pal. “Exploring the nature of digital transformation in the fashion industry: opportunities for supply chains, business models, and sustainability-oriented innovations.” Sustainability: Science, Practice and Policy 18.1 (2022): 773-795.