Most fleets run on a simple, expensive rule: fix it when it breaks. A machine goes down, a crew goes idle, and a mechanic scrambles to a job that could have been scheduled days earlier. Predictive maintenance flips that rule — but you don't get there with a big-bang rollout. You get there one machine at a time.
Here's the 90-day path we walk sites through when they move from reactive repairs to AI-monitored uptime.
Days 1–30: Get every machine talking
You can't predict what you can't see. The first month is about connecting the fleet — telematics from every OEM, plus a camera on the yard — into one feed. Mixed brands are the norm, and that's the point: one monitoring layer instead of five OEM portals and three logins.
If a machine can't tell you it's struggling, the only alert you get is the one from the operator standing next to it.
Days 31–60: Turn fault codes into actions
A raw SPN/FMI code on a dash means nothing at 6am. The second month is about translation — mapping each fault to the action a mechanic should actually take:
- "Hydraulic oil temp trending high on the 395 — schedule a cooler flush before Friday."
- "DEF quality fault on the A60 — order the part now, it's a two-day lead time."
- "Repeated idle-time spikes on the loader — coaching opportunity, not a repair."
Plain English, with the next step attached. That's the difference between data and a decision.
Days 61–90: Let dispatch run itself
By the third month the system isn't just watching — it's acting. When a fault crosses a threshold, Dozer reads the code, checks the part, and dispatches a mechanic who can actually fix it on the first trip. No wrong tech, no second visit, no crew standing around.
The bottom line
Predictive maintenance isn't a moonshot — it's a sequence. Connect the fleet, translate the noise, automate the response. Ninety days in, the daily walkaround stops being the thing that catches problems, because the problems get caught while everyone's still asleep.