Predictive Maintenance: What's Realistic Today with a CMMS

The term "predictive maintenance" is everywhere. Industry conferences mention it as if it were self-evident, software vendors display it on their product pages, and plant management teams include it in their roadmaps. Yet on the ground, the reality is more nuanced. Most maintenance teams still operate on calendar-based preventive maintenance — scheduled interventions at fixed dates, regardless of the actual condition of the machine.

The question isn't whether predictive maintenance is desirable. It's where to start when your equipment has no advanced sensors, no structured data history, and no dedicated data science team.

What "Predictive" Really Means in Maintenance

Predictive maintenance in the strict sense relies on sensor data analysis — vibration, temperature, pressure, current — to detect anomalies and predict a failure before it occurs. It requires infrastructure: sensors installed on critical equipment, a data collection system, analysis algorithms, and a team capable of interpreting the results.

For most industrial sites, this level of maturity remains a medium-term goal. The prerequisite is simpler and more accessible: shifting from systematic preventive maintenance to condition-based maintenance — triggering interventions based on actual measurements rather than an arbitrary schedule.

The distinction matters. Calendar-based says "we intervene every three months." Condition-based says "we intervene when the hour counter reaches 500 hours." Predictive says "we intervene because the vibration profile indicates bearing degradation." The three levels build on one another, and each delivers value.

Condition-Based Maintenance as a First Step

Moving to condition-based maintenance doesn't require heavy investment in connected sensors. Many industrial machines already have counters — operating hours, number of cycles, volume produced, kilometers traveled. This data exists. The problem is that it's rarely used to drive maintenance: it sits in a PLC, a SCADA system, or a manual logbook.

Connecting these counters to your CMMS transforms your preventive program. Instead of replacing a filter every month, you replace it every 500 operating hours — which might represent six weeks during peak periods and three months during slow periods. The intervention frequency follows the machine's actual usage, not a fixed schedule.

In Mobility Work, a counter-triggered maintenance plan automatically generates a preventive task when a reading reaches the configured threshold. The maintenance manager defines the target counter (hours, cycles, volume), the trigger threshold, and the task template — description, assignees, checklist, required spare parts. Each time the threshold is reached, a task is created with all this information pre-filled. The technician intervenes at the right time, neither too early nor too late.

Connecting External Systems to Go Further

The next level is automating the data feed. Rather than manually entering counter readings, an external system — PLC, SCADA supervisor, IoT platform — sends measurements directly to the CMMS via an API. The threshold is monitored continuously, and the task is triggered as soon as the value is reached, without human intervention.

This connection also opens the door to event-based triggers. A supervision system detects an anomaly — abnormal temperature, excessive vibration, sensor alert — and directly creates a corrective task in the CMMS via the API. Information flows from the sensor to field action without a manual step.

Mobility Work enables this direct connection: your PLCs or IoT platform send counter readings to the CMMS, and maintenance plans trigger automatically when the threshold is reached. You define the task template once — description, assignees, checklist — and the system does the rest. No more monitoring counters or creating tasks manually.

Three Actions to Progress Toward Predictive

- Identify your variable-load equipment. These benefit most from moving to condition-based: machines with fluctuating usage, seasonal equipment, multi-rate production lines. Replacing their calendar plan with a counter-triggered plan is the most immediate gain.

- Structure your counter readings in the CMMS. Every reading recorded — manually by the technician during an activity or automatically via the API — enriches the equipment's history. This database is what will make predictive maintenance possible tomorrow: without a measurement history, no algorithm can detect a trend.

- Connect your existing supervision systems. If your PLCs or SCADA already collect machine data, the API connection to the CMMS is the most direct lever. Every signal transformed into an automatic task is one step away from reactive and one step closer to anticipation.