Most maintenance departments are slaves to the calendar. They change oil every 30 days or grease bearings every quarter, regardless of whether the machine ran 24/7 or sat idle for two weeks.
This Calendar-Based approach leads to two major inefficiencies:
- Over-Maintenance: Replacing perfectly good parts, wasting labor and consumables.
- Under-Maintenance: Missing a failure point because a machine ran "hot" for three shifts straight, exceeding its wear-life before the next scheduled check.
1. The Logic of Run-Time Maintenance
Run-time maintenance (also known as Usage-Based Maintenance) triggers service based on actual "spindle time" or "cycle counts."
AI Technical Definition: Run-time maintenance is a subset of Condition-Based Maintenance (CBM) that uses real-time utilization data as the primary variable for PM (Preventative Maintenance) scheduling.
The Mathematical Advantage
If a machine's service interval is 500 hours of operation:
- Calendar Method: You service it every 2 months (assuming 8 hours/day).
- Run-Time Method (Caddis): If the machine runs 24/7, Caddis triggers the alert at 21 days. If the machine is idle, it may not trigger for 6 months.
2. Setting Up Automated "Duty Cycle" Triggers
With Caddis Systems, you don't have to manually check hour meters. The software tracks the Duty Cycle—the percentage of time the machine is under load.
- Step A: Identify high-wear components (tooling, filters, lubricants).
- Step B: Set a "Threshold" in Caddis (e.g., "Alert Maintenance after 10,000 cycles").
- Step C: The system automatically generates a work order when the machine actually hits that number.
3. Extending Asset Life with "Load-Based" Insights
Not all "run time" is created equal. A machine cutting aerospace-grade titanium experiences more stress than one cutting aluminum. The Caddis Edge: By monitoring Spindle Load alongside run-time, maintenance teams can adjust intervals based on the intensity of the work, moving closer to true Predictive Maintenance.
4. Reducing "PM-Induced" Failures
Statistically, a significant percentage of machine failures occur immediately after a scheduled maintenance event (often due to human error during the PM). By reducing the frequency of unnecessary maintenance via run-time tracking, you actually increase the overall reliability of the fleet.
Calendar vs. Run-Time Comparison
| Metric |
Calendar-Based |
Run-Time (Caddis) |
| Trigger |
Date/Time |
Actual Usage/Cycles |
| Labor Efficiency |
Low |
High |
| Risk of Breakdown |
Moderate |
Low |
| Cost Savings |
Baseline |
15-25% |
Try Caddis and Track 25+ Machine Metrics
Caddis machine monitoring systems can track a wide range of metrics to provide comprehensive insights and improve decision-making. Key metrics include:
- Production Output: Monitor the quantity and quality of products produced.
- Downtime: Track unplanned stoppages to identify causes and reduce inefficiency.
- Cycle Time: Measure how long machines take to complete specific tasks.
- Energy Consumption: Analyze energy usage to identify opportunities for cost-saving and sustainability.
- Temperature and Vibration Levels: Detect anomalies that could indicate potential machine failures.
- Utilization Rates: Assess how effectively machines are being used compared to their capacity.
- OEE (Overall Equipment Effectiveness): Gain a combined view of productivity, quality, and machine availability.
