Most equipment failures look sudden, but they rarely are. Long before a machine quits in the middle of a pour or a haul cycle, it leaves a trail of small warnings: voltage drift, rising temperatures, pressure fluctuations, irregular duty cycles. For years, those signals were effectively invisible. Now they’re not.
Advances in maintenance technology are enabling contractors to spot early indicators and intervene before a breakdown derails a crew’s day.
“We’re changing our mindset from being reactive to proactive, and then predictive,” says Rocco Marrari, vice president of sales, Pedigree Technologies.
Reactive maintenance waits for something to fail. Proactive approaches introduce scheduled service. Preventive maintenance adds condition monitoring to catch abnormal behavior early. Predictive maintenance builds on all of that, using data patterns to determine what needs attention and when.
The shift is already paying off. Fleets using data-driven maintenance strategies have reported higher equipment uptime and fewer unplanned disruptions, as issues are addressed before they escalate.
Advances in maintenance technology are enabling contractors to spot early indicators and intervene before a breakdown derails a crew’s day.
TURNING DATA INTO ACTION
For contractors, the challenge is knowing what data matters and when to act on it. Without a clear process, even well-instrumented fleets can find themselves reacting to failures instead of preventing them.
“Data is great… but unless you’re able to utilize that correctly… that is just noise,” Rocco explains.
Turning that data into action is what defines predictive maintenance in practice. It starts with creating a clear process. Increasingly, fleets are moving toward a single, centralized view of equipment health, allowing teams to identify patterns, prioritize risks and respond earlier.
Data in action means:
- Prioritizing alerts based on severity and risk
- Scheduling maintenance based on actual equipment conditions
- Generating work orders tied to specific issues
- Assigning technicians with clear direction and context
“Each alert should tell someone exactly what to do next,” Rocco says.
When those steps are connected, maintenance becomes predictable. Repairs can be planned around operations instead of interrupting them, reducing downtime and keeping machines in service when they’re needed most.
PROOF IN THE FIELD
The value of predictive maintenance becomes clear in real-world conditions.
In one case, a loader with unstable voltage from an overcharging alternator showed no immediate signs of failure. Over time, the issue was damaging onboard electronics, including electronic control module (ECM) and controller area network (CAN) components. Through voltage trend analysis, the problem was identified early, well before a catastrophic failure.
By addressing the issue proactively, the fleet avoided more than $8,000 in module replacements, equipment rental expenses and several days of downtime. The repair was completed under controlled conditions, not as a mid-shift emergency.
At scale, the gains multiply. Centralizing data across mixed assets allows teams to coordinate maintenance more effectively, improve equipment availability and reduce unplanned disruptions across the fleet.
FROM INSIGHT TO CONTROL
As fleets adopt predictive maintenance strategies, the goal becomes straightforward: reduced surprises and more control over when and how repairs occur.
Rocco has seen fleets using these approaches report equipment uptime improvements of up to 28%, underscoring the operational impact of acting early.
“We want fewer failures, planned repairs instead of emergencies and higher uptime across the fleet,” Rocco notes. “If we’re getting data and not acting on it, it’s a waste of time.”
Rocco shared these insights and more at the CONEXPO-CON/AGG 2026 session Advanced Maintenance Technology: Preventing Failures Before They Happen. Watch the full session by purchasing On Demand Education Access from the CONEXPO-CON/AGG 2026 show.
PHOTO CREDIT: SHUTTERSTOCK/PARILOV
