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Wanxiang Qianchao's data governance practices have been recognized as one of Zhejiang Province's first batch of high-quality datasets for key industrial sectors

2026-04-08

Recently, at the Zhejiang Digital Commerce Development Promotion Conference jointly hosted by the Zhejiang Provincial Department of Economy and Information Technology and the Zhejiang Provincial Data Bureau, the first batch of high-quality datasets for key industrial sectors in Zhejiang Province was officially released. Wanxiang Qianchao's "Equipment Operation Monitoring and Equipment Inspection Dataset" was selected, marking a new stage in the company's exploration of value realization in industrial data elements.

Currently, artificial intelligence technology is advancing at an accelerating pace. Data elements are transitioning from auxiliary production factors to core production factors, and the competitive focus is shifting from algorithm development to the supply of high-quality data. Practically validated high-quality datasets can effectively support core scenarios such as smart manufacturing, production optimization, supply chain collaboration, and product R&D innovation, driving improvements in production efficiency and business model innovation. The first batch of high-quality datasets for key industrial sectors in Zhejiang Province focuses on the "415X" advanced manufacturing clusters, aiming to create benchmarks for industrial data resources, promote the compliant circulation and efficient reuse of data elements in the industrial sector, and emphasize data quality, application effectiveness, and compliance security.

Wanxiang Qianchao's selected dataset is based on the equipment lifecycle management needs of the automotive parts manufacturing industry. Addressing pain points such as reliance on manual experience for traditional equipment maintenance and unplanned downtime caused by sudden failures, the dataset integrates multi-source heterogeneous data, including real-time equipment operation text data, high-frequency vibration time-series data, temperature sensor data, maintenance work order text, and equipment knowledge documents. It covers four core industrial data types: equipment operation, failure, maintenance, and knowledge. The dataset is deeply adapted to real production environments and can support the development of three major AI models for a complete intelligent maintenance system encompassing "pre-failure prediction – in-process diagnosis – post-failure optimization." In practical applications, it has achieved a 5% improvement in overall equipment effectiveness, a 10-15% reduction in inventory, a 15-20% reduction in failure repair time, and a 10-15% reduction in failure rates. This provides a replicable paradigm for intelligent equipment management in discrete manufacturing and drives the transformation of enterprise production maintenance models from "experience-driven" to "data-driven."

Building on its industrial expertise and existing digital and smart construction achievements, Wanxiang Qianchao will continue to deepen its data asset development, accelerate the deep integration and large-scale application of "AI+" across the full value chain in manufacturing, and strive to build a new manufacturing system driven by data and led by intelligence, injecting continuous digital and smart momentum into high-quality development.

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