AI Predictive Maintenance:
Eliminating Unplanned Downtime for High-Tech Equipment
Purpose-built for Optoelectronics & Display Panels, PCB, High-Tech Electronics, and Automated Fabs. Integrating MEMS tri-axial vibration sensors with AI diagnostic software to deliver early warnings for critical component anomalies—building highly reliable smart factories.
Why Leading Fabs Choose Prognosis
💰 NT$3M Annual O&M Cost Reduction
Delivers direct economic ROI per facility, significantly slashing annual operational and maintenance overhead.
👥 40% Reduction in Labor Costs
Precise fault pinpointing eliminates unnecessary walk-throughs and drastically optimizes technician deployment.
🛠️ NT$80,000+ Saved on Inspection Costs
Planned smart O&M replaces traditional, blind manual equipment teardowns with targeted servicing.
⚙️ 30% Extended Rotating Asset Lifespan
Proactive maintenance prevents catastrophic, unexpected damage to motors, spindles, and bearings.
Are These Challenges Costing Your Facility?
Unaddressed operational blind spots lead to severe financial losses:
Prognosis Technology delivers cutting-edge vibration sensing and predictive fault management tailored to the stringent demands of modern electronics manufacturing.
We deeply understand high-tech process challenges. Our mission is to elevate asset efficiency and reliability—safeguarding product yield, process precision, and operational continuity.
AI Predictive Maintenance Tailored for High-Tech Fabs
Prognosis Technology merges precision vibration telemetry, AI fault prediction, and real-time diagnostic algorithms into a unified equipment health management platform.
By continuously monitoring the operational status of critical, high-precision assets in real time, the system rapidly identifies vibration anomalies, forecasts latent faults, and delivers actionable maintenance recommendations. This empowers enterprises to reduce unplanned downtime, extend equipment lifespans, and cut maintenance costs, while safeguarding process precision, product quality, and line stability—ultimately driving overall manufacturing efficiency and smart manufacturing competitiveness.