410,000 in benefitsNT$10K Investment, NT$410K in Government Subsidies
Subscribe now and AI device health management goes live instantly.
You can monitor equipment health independently without needing to hire additional equipment engineers.
Government subsidy
NT$100,000
Company-paid
NT$10,000
Challenges and Pain Points
It's difficult to keep track of the equipment status.
Without quantitative metrics, it is difficult for managers to accurately grasp the real-time health status of all plant equipment.
Unexpected Downtime Causes Costly Disruptions
It's impossible to predict when equipment will fail, leading to unexpected production line interruptions and wasted inventory of spare parts.
Sensitive data leak risk
Traditional cloud solutions cause businesses to worry about core production data leaks, affecting their competitive advantage.
Lack of AI professional operations and maintenance team
Small and medium-sized enterprises find it difficult to recruit and retain teams of expensive data scientists and AI engineers.
Why choose the NeoEdge X Innolux PRiSM AI Predictive Maintenance Platform solution?
Traditional equipment maintenance consumes significant manpower and upfront investment, often failing to detect abnormal signs in real-time.
Once an unexpected downtime occurs, the losses are difficult to estimate.
NeoEdge X PRiSM AI Predictive Diagnostics Platform
Combining time-frequency features, Health Indicators (HI), and Remaining Useful Life (RUL) analysis for early anomaly detection.
No need to build an internal testing team; subscribe and use immediately, greatly lowering the adoption barrier.
Through continuous AI monitoring and prediction, downtime is transformed into planned maintenance, directly improving uptime.
All data analysis is completed at the enterprise's internal edge, ensuring production secrets never leave the facility.
AI dual-track monitoring, device status at a glance
From single metrics to systematic health analysis, NeoEdge X PRiSM offers real-time detection and long-term forecasting, providing data-driven maintenance decisions.
Equipment Health Index
Real-time quantitative health status, track all plant equipment at a glance.
Remaining Useful Life
Predict remaining useful life, avoid unexpected downtime, proactively plan maintenance schedules, and reduce spare parts inventory costs.
Data does not leave the factory.
Analysis results are kept within the company, balancing information security and efficiency.
Subscribe and use, cloud remote assistance
Gain professional support without building your own team through remote monitoring with NeoEdge Central.
Application scenarios validated by over 1,000 devices
From reactive maintenance to proactive prediction, algorithms and models have achieved breakthrough results in real production environments.
80%+
Abnormal detection rate
Precise early warning of equipment degradation
1,000+
On-site equipment proof validation
Algorithm reliability is well-documented
60%
Save maintenance costs
Reduce losses caused by unplanned downtime
30 days in advance
Maintenance alert
Deploy maintenance resources in advance
Data source: Innolux cooperation case