# Predictive Maintenance Use Case

Detect early failure signals, monitor equipment health, and enable condition-driven maintenance across industrial environments in real time.

## Applicable across industries and environments

QubiSense Predictive Maintenance is designed for operations in which equipment reliability, production continuity, and maintenance efficiency directly impact performance and costs.

### Industries

- Manufacturing and Industrial Automation
- Automotive and EV Production
- Packaging and Process Industries
- Energy and Utilities
- Oil and Gas Operations
- Heavy Machinery and Infrastructure

### Use Environments

- Equipment health monitoring
- Predictive maintenance and diagnostics
- Production line optimization
- Asset performance tracking
- Multi-agency and cross-team operations
- Distributed industrial operations

## When equipment fails without warning

Unplanned downtime is one of the most expensive risks in industrial operations. Most maintenance strategies rely on fixed schedules or reactive repair cycles. These approaches miss early warning signs and fail to account for real operating conditions. Machines continuously generate signals. The problem is not visibility. It is identifying failure patterns early enough to act.

QubiSense processes machine signals at the edge to detect early indicators of failure.

Instead of waiting for breakdowns or relying on static schedules, it enables real-time, condition-driven maintenance decisions.

## Trigger

Vibration, temperature, or electrical parameters deviate from normal patterns

Edge AI identifies early indicators of wear, imbalance, or stress

Predictive alerts are generated, and maintenance actions are initiated

## What QubiSense Edge AI actually does

- Captures vibration, temperature, acoustic, and electrical signals at the source
- Detects bearing wear, imbalance, and mechanical stress through pattern analysis
- Identifies motor overheating and electrical anomalies
- Flags abnormal usage patterns that accelerate degradation
- Generates real-time risk scores for equipment
- Enables local decision-making without dependency on centralized systems

## What happens in real time

### Early Alerts

Maintenance teams receive early warnings of potential failures..

### Smart Prioritization

Equipment is prioritized based on real-time condition.

### Proactive Scheduling

Maintenance actions are planned ahead to prevent issues..

### Reduced Downtime

Minimizes production disruptions and operational impact.

### Auto Documentation

Generates compliance logs and maintenance records automatically.

### Continuous Monitoring

Tracks equipment performance in real time for ongoing visibility.

## Operational Flow

Capturesignal analyzepatterns Identify Risk Maintain continuity Initiate maintenance Generate alerts

## What this enables

- Up to 30 percent reduction in unplanned downtime
- 20 to 40 percent lower maintenance costs
- Extended asset life through optimized servicing
- Improved production stability and equipment effectiveness
- Better planning through predictable maintenance cycles

## Act Before Failures Escalate

Operations do not fail due to a lack of monitoring. They fail when early signals are missed or ignored. By enabling real-time insight into equipment health, QubiSense allows organizations to prevent failures, reduce downtime, and maintain consistent operational performance.