Name: AISPHM
Brand: ASUS
SKU: 24029

Advanced vibration-analysis solution empowers predictive maintenance and equipment health management.

ISO 10816-3 compliant and advanced frequency analysis
Real-time AI analysis and on-site motor modeling
EdgeX development framework accelerates secondary data utilization
Intuitive notifications for motor-vibration anomalies
Continuous software enhancements and updates
Flexible architecture adjustment for on-premise and cloud

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A test sensor attached on the pump for fault-check, equipment downtime management, and industry diagnosis. Along with a monitor showing ASMPH application.

Predicting health, preventing problems

ASUS IoT AISPHM is a revolutionary solution for predictive maintenance and health management. Leveraging real-time AI and state-of-the-art vibration analysis, AISPHM is specially designed to detect early-stage issues in rotating equipment, ensuring unparalleled reliability and performance in the most demanding factory environments — delivering immediate, intuitive alerts and the adaptability of a flexible architecture for optimized operational efficacy, either on-premise or in the cloud.

This innovative approach empowers industries to anticipate and swiftly resolve issues, reducing downtime and maintaining uninterrupted production flow. AISPHM stands out by preserving the health and longevity of industrial equipment, delivering continuous advancements, and providing ultimate peace of mind.

Low to no code for exceptional simplicity

Your Path to Operational Excellence

Combining ISO-10816-3 with FFT Spectrum AI Modeling

Dedicated AI models are established for each device, continuously monitoring their operational status. Any deviations from the original AI model are recorded as abnormal events.

Web-based Private and Public Cloud Architecture

A fully containerized architecture enhances deployment flexibility across multiple platforms, including PCs, smartphones, and tablets.

Cost-effective CPU-based Modeling and Inference

Intel i5/i7 machines can support data processing for up to 120 sensors without the need for additional GPU resources.

Supports the EdgeX Open Source Framework

For diverse industrial applications, modules can be developed for data reuse without the need for extensive code refactoring.

Data visualization meets predictive intelligence

Based on the production line, machine train, machine and the sensor measurement point, managers can quickly grasp vibration history data and sensor connectivity status, event notifications — as well as perform advanced inspections or lubrication tests based on anomaly types.

AISPHM dashboard print screen, showing the number of abnormal, number of pending events, the location of abnormal equipment.

Versatile framework for wired and wireless sensors

ASUS IoT provides the necessary hardware, software and algorithms for a versatile framework that supports both wired and wireless sensors. In particular, ASUS IoT PE100A offers connectivity for 12 wired sensors, while the PHM can simultaneously handle data modeling and anomaly detection for hundreds of sensors.

Make Prognostic and Health Management Simple

Application Scenarios

A rotor probe, fixed-speed motor, test meter, sensor, pump, fault-check device for defect detector, equipment downtime management, and industry diagnosis.

Creating vibration-data records for key machinery

By analyzing vibration data, AISPHM allows managers to conduct trend analyses on vital machinery. This proactive approach aids in early issue detection, ensuring timely interventions and machinery longevity.

Technician inspector alignment pump and electric motor, Repairing work in factory

Evaluate the effectiveness of repairs on rotating equipment

AISPHM excels in comparing data before and after motor repairs, pinpointing discrepancies, enabling users to gauge repair effectiveness and uncover potential underlying maintenance issues.

Section of industrial electric motor, 3D rendering isolated on white background

AI-enhanced non-destructive monitoring for abnormal resonance and temperature

AISPHM leverages AI to analyze data for non-destructive anomaly detection, specifically identifying unusual resonance and temperature patterns, ensuring equipment integrity without invasive checks.