China's textile machinery industry is undergoing a deep transformation from manufacturing to smart manufacturing. Jingwei Smart and Northwestern Polytechnical University (NPU) recently signed a strategic agreement to establish a joint innovation center for textile machinery digitalization. This is not a routine collaboration — the two parties will focus on three core directions: smart factory construction, AI integration, and composite talent cultivation, aiming to bridge the gap between lab research and production lines.
Background
Jingwei Smart, a state-owned enterprise with over 70 years of history, has accumulated full-chain application scenarios and industrial experience in textile machinery. NPU's expertise in aerospace smart manufacturing and artificial intelligence fills the digital capability gap in the textile machinery sector. The collaboration, facilitated by government agencies, signals that policy support for digital transformation in the industry is intensifying.
China's textile machinery market currently faces multiple pressures: rapidly evolving customer demands, rising production costs, and an aging skilled workforce. According to industry data, digital transformation investments in the textile sector grew over 20% in 2025, yet most companies remain at the stage of isolated upgrades, lacking systematic solutions. The Jingwei-NPU innovation center addresses this pain point directly — from industrial software and full-chain information systems to AI-driven R&D and maintenance, aiming to build a complete digitalization loop.
Industry Impact
For the domestic textile machinery supply chain, this collaboration sends two key signals. First, industry-academia cooperation is shifting from project-based to platform-based models. Past collaborations often involved short-term projects or technology transfers, but a joint innovation center means long-term resource integration, with customized industrial software and smart systems developed collaboratively, directly accelerating technological iteration.
Second, AI is truly entering all aspects of textile machinery production — from parameter optimization in R&D to quality inspection during manufacturing and predictive maintenance in service. This will change the traditional "hardware-heavy, software-light" mindset. For buyers, future competitiveness of textile machinery will depend not just on mechanical precision but on intelligent decision-making and data connectivity.
On the talent front, the center's focus on cultivating composite professionals with both textile machinery knowledge and digital skills will alleviate the industry's skill mismatch crisis. The textile sector currently faces a digital talent shortage of over 300,000 people. This industry-university model promises to deliver a pipeline of skilled workers who understand both technology and application scenarios.