Wanxiang Qianchao Brings Intelligence to Every Aspect of Daily Life

On the outer ring grinding production line at Wanxiang Qianchao’s manufacturing facility, the overall equipment effectiveness (OEE) reached 6.31% per day. The predictive maintenance system has cumulatively reduced unplanned downtime by 30.5%, and the AI vision-based safety monitoring system achieves a 96.2% accuracy rate in identifying safety violations. The health scores of key components—including the grinding wheel spindle, grinding wheel dresser, workpiece spindle, and hydraulic system—all remain stable at 100 points.

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One production line offers us a glimpse into the AI revolution, where Equipment is interconnected, with data flowing freely through side to side and decisions capable of being mutually validated. An intelligent path spanning the entire manufacturing value chain is leaving tangible marks on Wanxiang Qianchao’s production line.

Part1  Personalized doctor for the facilities

The maintenance of factory equipment used to rely on the experience of veteran and protection of fixed amount of time. Thus the over-protection and lack of protection problems were not rare to see, and unexpected failures were the primary cause of unplanned downtime.

• With industrial equipment AI agents at its core, Wanxiang Qianchao has equipped critical machinery with a wide range of sensing and data collection tools.
• By integrating health prediction algorithms with general-purpose large-scale model technology, the system monitors the operational data of critical equipment in real time and tracks equipment health around the clock.
• Through trend alerts and root cause analysis, the system supports maintenance decision-making, establishing a full-chain operations and maintenance system that encompasses ‘pre-event prediction, in-process diagnosis, and post-event optimization’.

Part2  Smart sentinel for Safety and Quality  

• 24/7 AI Visual Safety Monitoring

The Wanxiang Qianchao AI Visual Safety Monitoring System combines AI video recognition with IoT sensing to establish a multi-tiered risk early warning and response mechanism. It provides 24/7 intelligent detection and real-time alerts for scenarios such as failure to wear personal protective equipment, non-compliant operations, and unauthorized entry into high-risk areas in critical locations like production workshops, warehouses, and hazardous waste storage facilities.

• Eliminating Quality Risks Before They Occur

AI is integrated into group chats and the quality knowledge base to automatically monitor for quality anomalies in group conversations. By leveraging historical similar cases and big data on quality anomalies, the system can identify issues, analyze causes, assign responsibility, and implement corrective measures within minutes. This shifts quality control from post-incident handling to proactive prevention, shortening the quality response cycle.

Part3  Algorithm think tank for supply chain and crafts

• AI Material Manager

To address the challenges of non-production material master data management, such as ‘inaccurate data entry, slow review processes, and repeated rejections for revisions’, the AI Material Manager is deeply integrated with the existing BPM system. As soon as a user submits a request, the AI agent automatically performs multi-source searches and conducts intelligent pre-reviews with automatic validation. Errors are highlighted, and correction suggestions can be accepted with a single click, significantly reducing request processing time and improving process efficiency.

• Device Parameter Prediction Agent

To address the challenge of having to repeatedly adjust and verify equipment operating parameters during product changeovers, the company has developed an intelligent agent for predicting equipment parameters. Users just simply select the process name and dimensional parameters, and the agent uses a neural network to calculate and predict process parameters, automatically generating work instructions. It is estimated that this solution saves one hour per changeover in both debugging time and work instruction preparation time, thereby improving production line efficiency.

Part4  Digital Employee in Management Process

• Contract Management

AI comparing and risk-analyzing system covers overall process of contract completion, contract comparison, contract risk analysis, and helps business personnel quickly identify differences in items, flagging legal risks and promoting review efficiency and compliance level.

• Human Resources

AI assists in generating monthly self-evaluations and, based on a comprehensive analysis of multiple dimensions—including task completion quality, efficiency, impact, and difficulty—provides managers with objective suggested scores and performance rating recommendations. The system’s self-evaluation is linked to evaluations from departments and supervisors, making the performance evaluation process more scientific and fair.

• Execution and Brand Management

Intelligent monitoring and analysis of public opinion in the administrative sector involves crawling public opinion data, automatically analyzing the type and severity of public sentiment, providing response recommendations, and tracking follow-up actions. AI automatically collects public opinion data from multiple sources, tags sentiment (positive/neutral/negative), risk levels (none/low/medium/high), and offers handling recommendations to help enterprises stay abreast of public opinion trends and enhance their brand risk management capabilities.

Part5  Data Advisor for business decisions

Business operation generates data from production line, finance business system, production management system, etc. In the past, these data were scattered all over the place, and the analysis of operation situation counts on human work like compiling reports and identifying the root cause of problems.

However, Wanxiang Qianchao chooses to do like this

• Establish a unified core operational metrics system covering dimensions such as revenue, costs, and efficiency
• Integrate data from multiple sources—including OT, IT, ERP, and MES—into a dedicated data system; deploy intelligent agents to automatically detect metric anomalies, trace detailed data back to its source, and conduct in-depth root cause analysis
•  Establish a five-step closed-loop management mechanism—“problem identification → root cause analysis → countermeasure formulation → verification → prevention”—to intelligently analyze abnormal metrics, generate action items, and track their implementation
• Drive a gradual shift in business decision-making from “relying on experience and reports” to “analyzing data, identifying root causes, and ensuring closed-loop management,” providing managers with timely, objective, and traceable decision-making support.

After two years of practice, Wanxiang Qianchao AI development has yielded abundant results.

• AI empowers methodology
• Dual Foundation

Dual support from technology and data

• Four-Dimensional Scenario Selection

Business value, data foundation, technical maturity, and scalability

• Delivery via Intelligent Agents

One intelligent agent corresponds to one type of business problem

• Replication via Benchmark Packages

Replication and promotion of benchmark scenario templates

Data governance and AI initiatives have gained repeated authorized certifications

• 2026 China Industrial Data Governance ‘Leader’ Enterprise
• 2026 IDC China Industrial AI Leader Award: Innovation Pioneer in Industrial AI Agents
• Zhejiang Province Artificial Intelligence Application Benchmark Enterprise
• Zhejiang Province’s First Batch of High-Quality Datasets for Key Industries in the Industrial Sector
• Zhejiang Province Key Project for the Construction of High-Quality Datasets in the Artificial Intelligence Industry
• Compilation of Exemplary Cases for Zhejiang Province’s First Batch of High-Quality AI Industry Datasets (2026)

The implementation of artificial intelligence at Wanxiang Qianchao has progressed through three stages—proof of concept, scenario pilot, and scale replication—and has now entered a new phase of systematic advancement. Looking ahead, the company has outlined three progressive development directions,

• Basis Enhancement

Deepen data governance internally and improve end-to-end, closed-loop quality control. Extend supply chain collaboration externally to achieve standardized integration and trusted sharing of supplier and user data, while continuously expanding the coverage and depth of application of high-quality datasets.

• Industrial Transformation

Centered on the full value chain—from R&D, production, and supply to sales and service—we will focus on core areas such as production operations, quality control, and supply chain collaboration. Through scenario-based intelligent applications, we will continuously drive cost reduction, efficiency gains, and quality improvement, propelling a comprehensive shift in management models from experience-driven to data and algorithm-driven.

• Cutting-edge Initiatives

Continue to advance the development of digital twins and factory simulations to achieve virtual-physical mapping and simulation-based optimization of production processes; explore data-sharing and collaboration models across the industrial chain to drive efficiency gains for both upstream and downstream partners through data capabilities. We will evolve toward a smart ecosystem to build Wanxiang  Qianchao’s end-to-end digital and intelligent competitiveness.

Wanxiang Qianchao will keep on strengthening AI development, assuring that all the achievements comes form digital and intelligent revolution will be actually applied to each position and employee, and thereby build momentum for the corporate’s high-quality development.