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How Jack Technology and Siemens Plan to Use AI and Humanoid Robots to Change How Clothes Are Made

June 19, 2026 - 23:37

How Jack Technology and Siemens Plan to Use AI and Humanoid Robots to Change How Clothes Are Made

The global apparel industry, long reliant on low-cost manual labor, is facing a technological shift. Jack Technology, a major Chinese sewing machine manufacturer, has partnered with German industrial giant Siemens to introduce artificial intelligence and humanoid robots into garment production lines. The collaboration aims to automate tasks that have traditionally been difficult to mechanize, such as handling soft fabrics and performing precise stitching.

Under the partnership, Siemens will provide its digital automation systems and AI software, while Jack Technology will integrate these tools into its next-generation sewing and cutting equipment. The companies are also exploring the use of humanoid robots to perform repetitive, physically demanding jobs like lifting fabric rolls and moving cut pieces between stations. The goal is not just to speed up production but to reduce waste and improve consistency in quality.

Industry analysts note that clothing manufacturing has lagged behind other sectors like automotive or electronics in automation due to the flexibility required to work with textiles. However, advances in computer vision and machine learning are now making it possible for robots to adapt to variations in material and design. Jack Technology and Siemens believe their combined system could allow factories to switch between different garment styles with minimal downtime.

The initiative comes as apparel brands face pressure to shorten supply chains and bring production closer to consumer markets. While the companies have not announced a specific timeline for commercial deployment, they plan to test the system in pilot factories in China and Southeast Asia within the next two years. If successful, the technology could reshape how clothes are made, potentially reducing the industry's dependence on low-wage labor while increasing output flexibility.


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