Case Study | Installing an “Early-Warning Radar” on Equipment Enables Controllable Management of Bearing Wear Risks in Hoist Motors

In the cement production process, elevators play a critical role in the vertical conveyance of raw materials and finished products, serving as core equipment within the material-handling system. The operational condition of the associated drive motor directly determines whether the entire conveying line can run continuously and reliably. When motor bearings experience wear‑related failures, the early signs often manifest as a gradual increase in vibration acceleration, making such issues highly concealed. If left undetected and unaddressed, the fault will progressively worsen, leading to bearing overheating, cage fracture, and, in severe cases, rotor–stator contact. These conditions can result in unplanned, sudden elevator shutdowns and material blockages, inflicting significant production losses on the enterprise.

Recently, a major cement company has leveraged Zhongyun Technology Intelligent Operations and Maintenance Platform , successfully implemented precise early‑warning for bearing wear faults in hoist motor bearings. Based on the platform’s diagnostic findings, the enterprise scheduled a planned shutdown for maintenance, replaced the bearings, and thereby averted the significant production risks of unexpected equipment downtime and disruptions to material handling, fully demonstrating the practical value of predictive maintenance in industrial operations.

1. Vibration data surged unexpectedly, and the platform promptly triggered an alert notification.

In mid-June 2026, the Zhongyun Technology intelligent operations and maintenance platform detected through online monitoring that the vertical vibration acceleration at the output end of the hoist motor No. 02d03 had rapidly increased from 5 m/s² to 45 m/s², exceeding the system’s preset trend threshold and triggering an equipment alarm.

The platform immediately pushes alert notifications to on-site operations personnel, clearly indicating the fault location, alert severity, and the time of the anomaly, thereby precisely pinpointing the affected component. This provides on-site technicians with a clear roadmap for troubleshooting and enables early detection of potential faults.

II. Multi-dimensional data analysis and assessment for precise identification of bearing wear faults

Upon receiving an alert from the platform, the Zhongyun Technology expert diagnostics team retrieved the equipment’s historical operating data and conducted a comprehensive analysis, taking into account the equipment’s rated speed and mechanical‑structural parameters. Through in-depth examination of vibration waveforms and spectral characteristics, they identified periodic impact‑type vibration signals in the monitored waveforms and detected typical bearing fault‑related frequency components in the spectrum. Based on this integrated assessment, they concluded: The motor’s output-end bearing exhibits wear and looseness. It is recommended that enterprises schedule shutdowns during production downtimes to conduct on-site verification.

III. Planned Shutdown and Maintenance Verification to Eliminate Equipment Safety Hazards

Based on the diagnostic recommendations provided by the platform, the enterprise’s operations and maintenance team scheduled a planned shutdown for inspection on August 15. On-site disassembly and verification confirmed that the bearing clearance at the motor’s output end exceeded the allowable limit, fully consistent with the platform’s diagnostic findings.

The on-site maintenance team promptly initiated bearing replacement and simultaneously performed alignment and re‑centering of the motor and gearbox. Following completion of the overhaul, commissioning, and startup, platform monitoring data showed that the vibration acceleration at the motor’s output end had decreased from 40 m/s² during the fault period to below 10 m/s², with the equipment’s vibration condition returning to stable levels and all potential safety hazards completely eliminated.

IV. Lessons from the Case: Installing an “Early-Warning Radar” on Critical Industrial Equipment

The successful resolution of the potential bearing wear issue in the hoist motor has fully closed the loop across the entire process—“online early warning–intelligent diagnostics–planned maintenance–performance verification”—demonstrating the core capabilities of the intelligent operations and maintenance platform.

1. Proactive Trend‑Based Early Warning: Continuously monitors equipment vibration trends in real time, issuing alerts at the earliest signs of potential faults to provide ample time for maintenance and prevent unexpected unplanned shutdowns at their source.

2. Data-Driven Precision Diagnostics: Leveraging specialized data analysis of vibration spectra, waveforms, and other metrics, this approach accurately identifies fault locations and fault types, minimizing unnecessary disassembly and troubleshooting while reducing operational and maintenance labor costs.

3. Ensuring production through a closed-loop business process: Establishing a comprehensive closed loop encompassing early warning, diagnostics, maintenance, and performance verification, balancing equipment safety with production continuity to help enterprises maintain stable and controllable operations.

Most industrial equipment failures do not occur suddenly; rather, they result from the long-term accumulation and evolution of hidden risks. Moving forward, Zhongyun Technology will continue to deepen its expertise in the field of intelligent industrial operations and maintenance, leveraging online equipment‑monitoring data as its core. It will provide fault‑early‑warning and professional diagnostic services for a wide range of critical conveying equipment in the cement and building‑materials industries, helping industrial enterprises transition from traditional “reactive repair” to scientifically grounded “predictive maintenance,” thereby strengthening the foundation of safe production.