AI-Driven Predictive Maintenance and Equipment Health Management

Prognosis AI Fault Prevention Diagnostic Software utilizes advanced AI algorithms to automatically identify 18 types of equipment anomalies. Traditionally, sensors only collected raw data, which required experienced technicians to interpret and analyze. With Prognosis AI diagnostic software, complex sensor data is transformed into clear and intuitive diagnostic results, allowing even non-technical users to easily understand equipment conditions and make informed maintenance decisions.

Solving Equipment Maintenance Challenges

Raw Data Only

Sensor systems typically provide only numerical raw data, which must be analyzed manually by specialists.

Long Analysis Time

Equipment data must be accumulated over a long period before accurate diagnostics can be performed.

AI-Driven Predictive Maintenance

The system provides 18 intuitive diagnostic results, allowing enterprises to quickly and accurately evaluate equipment conditions and detect potential problems early.

Imbalance

Uneven weight distribution of rotating components causes vibration during operation.

Bent Shaft

A shaft may become deformed due to overload or damage, affecting equipment performance.

Misalignment

Two rotating shafts are not properly aligned, leading to vibration, wear, or abnormal noise.

Mechanical Looseness

Motor components are not firmly secured, reducing performance and accelerating wear.

Oil Whirl

Instability caused by pressure changes in the lubricating oil film inside bearings.

Oil Whip

Oscillation caused by dynamic pressure changes between the shaft and bearing.

Inner Race Damage

Wear or cracks on the inner bearing race affecting operational stability.

Outer Race Damage

Wear or cracks on the outer bearing race affecting motor performance.

Rolling Element Damage

Damage to bearing balls that impacts mechanical operation.

Air Gap Eccentricity

Uneven spacing between rotor and stator reduces motor efficiency.

Broken Rotor Bar

Broken rotor bars prevent the motor from operating normally.

Phase Problems

Incorrect electrical phase conditions affecting motor efficiency or operation.

Gear Eccentricity

Gear rotation axis deviates from its center, causing vibration and noise.

Gear Misalignment

Misaligned gear shafts increase wear and reduce transmission efficiency.

Broken Gear Tooth

Damaged gear teeth affect power transmission.

Gear Wear

Worn gear teeth reduce power transmission capability.

Gear Shaft Bending

Blade Abnormalities

Wear, damage, or foreign objects on rotating blades cause imbalance and reduce mechanical stability.

18 AI Diagnostic Technologies for Accurate Root-Cause Identification

Visualized Data

Operational data is displayed in graphical formats, allowing maintenance teams to quickly monitor equipment conditions.

Big Data Analytics

AI and big data technologies analyze equipment aging patterns and predict remaining lifespan.

Intelligent Alert Mechanism

When abnormal conditions are detected, the system can trigger alerts through email notifications, warning lights, or other alarm systems.

Customization

The software can be customized according to specific enterprise requirements and operational environments.

Intuitive Equipment Monitoring Platform： From Real-Time Alerts to Automated Diagnostic Reports

Prognosis AI diagnostic software provides real-time monitoring dashboards. Within 3–5 minutes after activation, the system can generate diagnostic results to help maintenance teams quickly assess equipment conditions.
Key Features Date Mode
關鍵特徵值
AI RUL Estimation
設備餘命估算
Equip Abnormal PHM Mechanism
設備異常預防診斷機制
Automatic Threshold Setting
自動警報設定
Equip FFT AI Degrade Percentage Analysis
設備頻譜AI老化比例分析
Comprehensive Diagnostic Reports
Cloud Integration

If you would like a detailed introduction or technical consultation, please contact us.