AI Predictive Maintenance: Cutting Downtime & Maintenance Costs for Traditional Manufacturing
Designed for machine tools, food processing, plastics, textiles, metalworking, cement, paper, and heavy industrial sectors. Leverage precision vibration monitoring and AI fault prediction to gain real-time visibility into asset health and maximize production line stability.
Is Your Facility Facing These Operational Challenges?
In an increasingly competitive manufacturing landscape, every unexpected equipment failure triggers massive financial losses.
Yet, many facilities still rely on manual inspections and tribal knowledge—leaving them vulnerable to sudden breakdowns that compromise throughput and product quality.
- Equipment degradation causes breakdown frequency to surge year after year.
- Knowledge remains in the heads of veteran engineers, making maintenance hard to standardize.
- Sudden breakdowns lead to missed shipment deadlines and capacity losses.
- Time-consuming periodic checks fail to provide real-time asset health visibility.
- Rising repair expenditures directly erode operational profitability.
Trusted by Nearly 100 Listed Enterprises
Shift from Reactive Firefighting to Proactive Prevention: Pinpoint 21 distinct equipment failure modes to build a high-reliability smart factory.
💰 Prevented NT$10M+ in Downtime Losses
🛠️ 40% Reduction in Wasted Teardown Labor
🎯 95% Anomaly Detection Accuracy
🛡️ TS Explosion-Proof Certified
Elevating Asset Reliability & Manufacturing Efficiency
Prognosis Technology combines AI PHM (Prognostics and Health Management), vibration telemetry, and intelligent diagnostic technology to deliver a comprehensive equipment health platform tailored for traditional manufacturing.
By continuously monitoring the operational status of critical equipment in real time, the system delivers early anomaly warnings and precisely pinpoints root causes. This empowers enterprises to minimize unplanned downtime, extend asset lifespans, and boost maintenance efficiency—while optimizing energy efficiency and lowering carbon emissions. Ultimately, it comprehensively elevates production stability, operational profitability, and sustainable competitiveness.