Design Thinking to support emerging AI Technologies in the Garment Industry

Design thinking is a future skill that is becoming increasingly important in a wide range of industries. As organizations seek to become more customer-centric and responsive to changing market needs, design thinking is emerging as a powerful tool for creative thinking, innovation and problem-solving. This skill set is especially beneficial for professionals in the garment industry, particularly those who are adopting the latest AI technologies to improve their operations.

Technology has played an important role in the apparel industry in recent years. Here are some examples of how technology is being used in the industry:

• 3D Printing: 3D printing has revolutionized the way apparel products are designed and manufactured. It allows designers to create prototypes and samples quickly and at a lower cost than traditional manufacturing methods. It also allows for greater customization and personalization of products.

• Augmented Reality: Augmented reality (AR) allows customers to see how apparel products will look on them before they make a purchase. This technology is particularly useful for online retailers, who can use AR to create virtual try-on experiences for their customers.

• Smart Fabrics: Smart fabrics contain sensors and other technology that can track biometric data, monitor environmental conditions, and perform other functions. These fabrics can be used in a variety of apparel products, from sportswear to medical garments.
• Sustainability: Technology is also playing a role in promoting sustainability in the apparel industry. For example, blockchain technology is being used to create more transparent and traceable supply chains, while 3D printing is reducing waste in the manufacturing process.

In addition to the above, here are a few of the latest AI technologies that are being used in the garment industry:

1.?????Computer Vision: Computer vision is a technology that uses machine learning algorithms to enable computers to interpret and understand visual information. In the garment industry, computer vision is being used to automate quality control processes by identifying defects and irregularities in fabric, stitching, and finished garments.

2.?????Predictive Analytics: Predictive analytics is a technology that uses data mining, machine learning, and other statistical techniques to analyze historical data and make predictions about future events. In the garment industry, predictive analytics is being used to forecast demand for garments and to optimize production schedules.

3.?????Digital Twin: A digital twin is a virtual representation of a physical object or system. In the garment industry, digital twins are being used to simulate the production process and identify potential bottlenecks or inefficiencies before they occur.

4.?????Smart Textiles: Smart textiles are fabrics that incorporate sensors, actuators, and other electronic components to enable them to sense and respond to the environment. In the garment industry, smart textiles are being used to create garments with built-in health monitoring capabilities, such as heart rate monitoring and blood pressure monitoring.

5.?????Automated Sewing: Automated sewing technology uses computer-controlled machines to sew garments. These machines can be programmed to create a wide range of stitch patterns and styles, and can operate at high speeds, reducing production time and costs.

Design thinking can play a critical role in further development and implementation of such artificial intelligence (AI) technologies in the apparel industry. Here are some ways in which this skill set can help:

Understanding User Needs: Design thinking can help AI developers understand the needs and preferences of apparel industry stakeholders, including designers, manufacturers, retailers, and customers. By empathizing with these stakeholders, AI developers can gain insights into the specific pain points and challenges they face, and design AI solutions that meet their needs.

Defining the Problem: Once user needs have been identified, AI developers can use design thinking to define the specific problem they are trying to solve. This involves synthesizing the user research data to identify key trends and patterns, and to define the AI challenge they will tackle.

Ideation and Prototyping: In this stage, AI developers can use design thinking techniques like brainstorming and rapid prototyping to generate a wide range of AI ideas and to create prototypes of their solutions. They can also use "design provocations" to push themselves to think outside the box and come up with truly innovative ideas.

Testing and Refinement: Once prototypes have been developed, AI developers can test their solutions with real users to gather feedback and refine their designs. This feedback can help developers make adjustments to their AI solutions to better meet the needs and preferences of their stakeholders.

Iteration: Finally, design thinking encourages an iterative approach to problem-solving, which means that AI developers can continue to refine and improve their solutions based on ongoing feedback from users. This iterative approach can help ensure that AI solutions are continually optimized to meet changing stakeholder needs and preferences.

Overall, by applying design thinking principles to the development and implementation of AI technologies in the apparel industry, AI developers can create solutions that are more user-centered, effective, and sustainable. This can lead to increased efficiency, cost savings, and improved customer satisfaction, which are all critical factors for success in the highly competitive apparel industry.

By

Nayantara Chatterjee

Co-founder & Director, Vidyadhara Consultancy LLP