Exhibition Review | The 2026 China Equipment Operation, Maintenance & Retrofit Conference Addresses Industry Pain Points Through Dual-Track Dialogue; Zhongyun Kangchong Leads a Paradigm Shift in Intelligent Equipment O&M

November 7, 2026 China Equipment Operation, Maintenance and Retrofit Conference The event kicked off with great fanfare in Taiyuan, Shanxi. Hosted by the China Association for Maintenance and Remanufacturing of Mechanical and Electrical Equipment, and organized by the Artificial Intelligence Branch and the Digitalization Special Committee of the Association, with support from the Comprehensive Technical and Economic Research Institute of Machinery Industry Instruments and Meters, the summit brought together over 60 representatives, including industry association leaders, leading experts from universities and research institutes, and top companies across the industrial chain. Focusing on cutting-edge issues such as transforming equipment operation and maintenance paradigms, implementing industrial AI technologies, piloting “equipment hospitals,” and building O&M data sets and intelligent agent systems, the gathering explored new pathways for high-quality development of China’s high-end equipment operation and maintenance sector.

Ning Guoyun, General Manager of Wuhan Zhongyun Kangchong Technology Co., Ltd., a leading industry expert, delivered keynote speeches at two major specialized sub-forums in succession. He shared in depth the company’s comprehensive technological expertise in industrial PHM, the results of its benchmark pilot operations as an “Equipment Hospital,” and top-level insights into co-building an industrial ecosystem, thereby providing a highly valuable practical model for advancing China’s intelligent equipment maintenance and operations sector.

In the morning, Jinrui Hall Workshop on Jointly Building High-Quality Datasets and Operations-Intelligent Agents The event was held with great ceremony, during which General Manager Ning Guoyun delivered a keynote address titled “Ecosystem Collaboration and Co‑Creation of Value in the New Paradigm of Intelligent Operations and Maintenance.” The report directly addresses the core challenges currently facing the development of China’s industrial intelligent operations and maintenance sector: many industrial AI projects suffer from the dilemma of “strong algorithms but weak implementation.” Silos of multi-source equipment data abound, dataset quality is uneven, condition‑monitoring samples lack proper annotation, software–hardware systems remain fragmented, and industry standards are absent. These issues result in insufficient generalization capabilities of AI models and persistently high rates of false alarms and missed detections. Consequently, numerous technical solutions remain confined to laboratory validation and cannot be scaled or deployed effectively in complex factory production environments.

Addressing common bottlenecks across the industry, the general manager of Ningguo Cloud presented a forward-looking industrial perspective: High-quality multimodal operations and maintenance datasets serve as the foundational infrastructure for the iterative evolution of intelligent O&M agents, while industry-chain ecosystem collaboration and joint standards development are essential to bridging the final-mile gap in industrial AI implementation. The report systematically explains that an operations and maintenance (O&M) intelligent agent is by no means a single algorithmic model, but rather a complex system integrating multi-source sensing, feature engineering, mechanism–AI fusion reasoning, an expert knowledge engine, and closed-loop iteration. It is essential to integrate multimodal data—including vibration, temperature, lubricant analysis, process conditions, maintenance work orders, and fault histories—establish standardized systems for data collection, annotation, governance, and evaluation, and accumulate high-quality industry datasets covering diverse operating conditions and all fault modes. At the same time, technological barriers among equipment manufacturers, software service providers, industrial and mining enterprises, and research institutes must be dismantled to build a collaborative innovation community involving industry, academia, research, and application. Together, they should advance the development of national and industry standards for algorithm evaluation, data specifications, and service assessment, achieve deep hardware–software co‑alignment, and ensure that algorithmic capabilities are genuinely translated into perceptible, quantifiable business value for factories. This will drive equipment O&M toward a new paradigm: autonomous, factory‑level intelligent agents, rather than isolated point‑monitoring and diagnostic approaches. The report resonated deeply with the experts in attendance and offers a systematic practical framework for building an O&M intelligent agent ecosystem across the industry.

In the afternoon, “Equipment Hospital” Pilot Practice Exchange Seminar Next up is Ningguo Yun, General Manager of a pilot unit among the first nationwide to build an “Equipment Hospital” under the China Machinery Maintenance Association. He will deliver a keynote presentation titled “From Fault Diagnosis to Health Management — Wuhan Zhongyun Kangchong’s Practice in Building and Operating an ‘Equipment Hospital,’” fully revealing the top-level design, technological foundation, end-to-end service system, and scalable operational outcomes of this benchmark domestic project. His insights will provide a complete, replicable, and widely applicable model for the national rollout of Equipment Hospital pilot programs.

Unlike the traditional passive model of repair shops, Zhongyun Kangchong has pioneered the introduction of “Create records for equipment, conduct health check-ups, prescribe treatments, and verify efficacy” The core concept of full‑lifecycle health management for equipment brings about a paradigm shift, moving from “reactive repair after failure” to proactive health management focused on “preventing problems before they occur.” Relying on the Hubei Provincial Innovation Center for Intelligent Operation and Maintenance of High‑End Equipment as a robust platform, the project aims to build… “Visible, accurately assessed, early prediction, effectively managed, continuously improved” A comprehensive technical framework encompassing five core capabilities establishes an end-to-end business closed loop covering “health check-up and record creation, monitoring and early warning, diagnosis and assessment, maintenance coordination, and efficacy validation.”

Technical aspects , the company leverages China’s first and only CNAS‑accredited IEPlat‑OS algorithm platform to build Mechanism + AI Dual-Driven Diagnostic Engine Over 120 specialized intelligent diagnostic algorithms run collaboratively. By integrating digital twins and multi-agent cross-validation technologies, it links three types of data—equipment status parameters, production process parameters, and product quality results—overcoming the industry’s longstanding problem that traditional fixed-threshold approaches cannot distinguish equipment degradation from operational disturbances. It can detect early-stage equipment degradation trends 10–30 days in advance and provides fault root-cause identification with confidence levels, risk-grading assessments, and actionable maintenance recommendations, truly solving five major practical problems in continuous production scenarios: accurate diagnosis, clear visibility, precise prediction, fast repair, and measurable reduction of losses.

In terms of the service system Zhongyun Kangchong has established a three-in-one equipment hospital operating framework—“Hospital‑Team‑Management”—implementing a diagnostic and treatment control mechanism featuring unified intake, unified work order assignment, unified delivery, and closed-loop follow-up. It has assembled multidisciplinary expert teams in vibration, lubrication oil analysis, acoustic signature, and AI, instituted an expert consultation system for complex faults, and accumulated extensive fault case records along with an industry knowledge base. A 24/7 remote diagnostics center has been built, delivering a full spectrum of services encompassing inspection and diagnosis, emergency repair, retrofitting and upgrades, remanufacturing, shared spare parts storage, contingency support, and personnel training. Meanwhile, it independently developed ITPM inspection, testing, and preventive maintenance strategy manuals for the four major disciplines—rotating machinery, stationary equipment, electrical systems, and instrumentation—forming a standardized, configurable maintenance strategy library that enables standardization of equipment operation and maintenance service processes, quantifiable outcomes, and traceable procedures.

Currently, the complete technology and service solution has been deeply implemented across key industrial sectors, including oil and petrochemicals, fine chemicals, cement and building materials, metallurgy and steel, power and energy, semiconductors, and discrete manufacturing. It encompasses a fully in-house developed full-stack architecture—spanning underlying hardware sensing, edge data acquisition, the IEPlat Tengyun intelligent operations and maintenance platform, PHM-specific AI chips, predictive maintenance all-in-one devices, and on-site expert O&M services—and supports multi‑endpoint collaboration across PC, large displays, and mobile devices. With flexible deployment options—including private cloud, edge computing, and enterprise‑wide group architectures—it effectively helps industrial enterprises reduce the risk of unplanned downtime and ensures continuous, stable production line operation.

Association leaders and industry experts attending the event highly praised Zhongyun Kangchong’s systematic achievements in piloting its “Equipment Hospital,” its robust technological capabilities resulting from deep AI integration, and its end-to-end service‑operation model. They engaged in lively discussions on pilot construction standards, data‑value extraction, and iterative service business models.

Founded in 2016, Wuhan Zhongyun Kangchong boasts a multidisciplinary team of nearly 150 professionals. The company has actively contributed to the development of five national standards and three industry standards, and holds a portfolio of cutting-edge proprietary core technologies, including PHM-specific AI chips, integrated predictive maintenance systems, and algorithm engineering platforms. It stands as a leading benchmark enterprise in China’s industrial equipment predictive maintenance and full lifecycle asset health management sectors.

Presenting a series of significant achievements at two concurrent sub‑venues of the national industry conference not only reflects the industry’s high regard for Zhongyun Kangchong’s technological innovation and engineering expertise, but also underscores the company’s commitment to driving industrial upgrading.

Going forward, Wuhan Zhongyun Kangchong will continue to focus on the core market of intelligent equipment operations and maintenance, iteratively upgrade its innovative “Equipment Hospital” service model, actively participate in building industry standards, and collaborate with upstream and downstream partners to co‑create high‑quality industrial O&M datasets and an AI‑driven O&M ecosystem, leveraging cutting‑edge industrial AI to drive high‑quality development in China’s high‑end equipment manufacturing sector.