Crossover Talks Jiaxing: Minth Group AI Smart Manufacturing in Action
AI in practice—seeing is believing. Step onto the factory and witness the change.
As artificial intelligence becomes a key driver of industrial upgrading, manufacturers are rolling out digital transformation strategies. Yet the real challenge is not whether companies recognize AI’s importance, but how to make AI truly land and deliver measurable results on the shop floor.
Jointly organized by Profet AI, Minth Group, and the Ningbo Intelligent Manufacturing Industry Association, Crossover Talks Jiaxing: Minth Group AI Smart Manufacturing in Action focused on real-world implementation, bringing participants directly into the factory demonstration base to see how AI is reshaping manufacturing.
Upgrading Core Knowledge, Turning It into Productivity
Profet AI Co-founder & CEO Jerry pointed out that manufacturing today resembles the “three suns” in the sci-fi novel The Three-Body Problem, simultaneously facing three major uncertainties: shifting global tariffs, geopolitical conflicts, and the rapid advance of AI. In this environment, resilience is the only way forward, and applying AI on the ground is the key breakthrough.
Jerry emphasized that the heart of manufacturing lies in the practical experience of frontline staff and domain experts—their skills in machine tuning, process design, and tacit knowledge represent core competitiveness. Profet AI’s mission is to transform this expertise into scalable data models and assets through Domain Twin™, enabling companies to replicate consistent processes and quality across different sites and factories—converting experience into productivity.
From Knowledge Retention to Standardization and Assetization
Profet AI Pre-sales Director Eugene added that in today’s “high-uncertainty” era, most manufacturers face three pressing challenges: insufficient process capability, overly long product R&D cycles, and the loss of critical know-how when veteran employees leave.
AI’s value should not remain in strategy papers or R&D labs; it must be applied on the ground. By converting tacit experience into explicit knowledge, trial-and-error can evolve into traceable, standardized processes. With Domain Twin™, enterprises can embed critical parameters, process logic, and best practices directly into models, enabling even new employees to ramp up quickly.
Eugene stressed that AI adoption doesn’t have to start with complex algorithms. Instead, it should begin with clear pain points, building interpretable and reusable solutions—a first step in moving from experience-driven to data-driven.
From Workshops to Results: 35% Yield Improvement & Cultural Shift
Chen Yikai, Deputy General Manager of Excellence Wire Ind. Co., Ltd., shared their hands-on AI journey. Excellence Wire, a specialist in crystal heads and network jumpers, had already invested years in lean and digital initiatives. But after visiting Minth’s Future Factory in 2024, they witnessed for the first time how AI could concretely optimize processes and boost yield—prompting them to launch adoption projects.
Unlike traditional classroom training, they implemented a workshop model, involving 13 departments across the company to integrate AI into daily workflows. Despite challenges like difficult topic selection, incomplete data, and unclear outcomes, with the consulting team’s guidance they broke through barriers.
The result: In the “foil stripping” process of their C6A FTP product line, yield improved from 50% to 85%, saving about 100 hours of labor per month. More importantly, company culture shifted from experience-based decisions to data-driven decisions, with AI becoming part of the organizational DNA.
AI+ Driving Deep Transformation: Minth’s Component Process AI Applications
Even Zhang, Senior Digital Transformation Project Manager at Minth Group, shared the group’s transformation experience. Through systematic AI training, both management and frontline staff developed a shared language, creating a top-down and bottom-up transformation dynamic. In 2024, Minth gathered 64 proposals and successfully rolled out 10 AI projects, including one focused on yield improvement in “bending arc dimensions.”
The cross-departmental project, completed over three months, ran fully on the Profet AI AutoML platform—from data collection and model building to shop-floor validation—ultimately identifying key process factors and applying them in production, significantly enhancing stability.
Minth is also advancing short-, medium-, and long-term strategies to refine models and expand adoption across its 70+ factories worldwide. Even highlighted that the greatest challenge is building user trust in AI. Minth addressed this by introducing phased training, sharing success stories, and cultivating in-house AI “seed instructors” to empower global sites to independently drive projects, paving the way for global smart manufacturing upgrades.
From the Factory Floor, Glimpsing the Future
This industry exchange demonstrated clearly: AI is not a distant vision—it is a tool that can be transformed into real productivity on the factory floor.
The collaborations between Profet AI, Minth Group, and Excellence Wire show that AI adoption can start with concrete pain points, crystallize expertise into models, and turn pilot successes into organizational capabilities.
Amid global competition and shifting markets, manufacturing resilience stems from ongoing experimentation and continuous innovation. To make AI real, you need to step into the factory and witness it firsthand. That is the truest takeaway from Jiaxing—and a tangible roadmap toward the future of smart manufacturing.
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