A reliability-first CMMS, not just work-order dispatch.
SMMS (Smart Maintenance Management System) is a CMMS built for reliability work: ISO 14224 failure taxonomy at capture, built-in RCFA with MTTR phase breakdown, tenant-configurable FMEA, criticality scoring, MTBF/MTTR by asset class, condition-based triggers, and meter-based PM with a re-fire guard.
What does a reliability engineer need that a basic CMMS doesn't provide?
A work-order-dispatch tool tells you what got fixed and when. A reliability program needs more: failure data structured well enough to compute MTBF and MTTR by asset class, not just by ticket count; an investigation workspace for the failures worth investigating, not just closing; a documented, defensible way to rank which failure modes deserve attention before they happen (FMEA); and preventive maintenance that triggers off real usage or condition signals instead of a blind calendar interval. Those four things — data quality, investigation, prioritization, and PM strategy — are the evaluation criteria a reliability engineer applies to any CMMS shortlist, and they're the four capability blocks below.
Four capabilities, one connected data model
Coded at capture, not reconstructed later
Every closeout resolves to the ISO 14224 Annex B vocabulary — failure mode, mechanism, cause, and detection method — enforced by database constraints, not a notes field a technician may or may not fill in carefully.
The ISO 14224 standard, implementedBuilt-in RCFA with MTTR phase breakdown
5-Why, fishbone, evidence and timeline capture, versioned investigations — plus the rare capability: MTTR modeled as phases with delay and impact entries, so you can see where repair time actually goes.
Root cause analysis in SMMSFMEA with database-enforced RPN integrity
Tenant-configurable Severity/Occurrence/Detection scales, computed RPN, and CHECK-constrained risk bands — the ordering between your Low/Medium/High thresholds is a schema guarantee, not a UI suggestion.
FMEA software in SMMSMeter-based PM with a re-fire guard
PM triggers on meter readings (runtime hours, cycles, mileage) with a unique-constraint guard against duplicate re-fires, plus opt-in, off-by-default human-in-the-loop PM proposals — nothing schedules itself onto your calendar without a tenant admin turning it on.
How PM connects to FMEA risk scoresA reliability program running on the connected data model
A reliability engineer at Meridian Fabrication Works (a synthetic demo tenant) pulls the MTBF trend for the Cooling System asset class and sees it drifting down. Filtering by coded failure mode shows three "Bearing Failure" events in the last two quarters — enough of a pattern to open an RCFA. The investigation's 5-Why traces the cause to a lubrication interval that was too long for the duty cycle; the finding updates the FMEA worksheet's Occurrence score for that failure mode, which pushes its RPN above the tenant's "high" threshold. That, in turn, is the justification for tightening the meter-based PM trigger's lubrication interval — one thread of evidence running from coded failure data to a changed PM schedule, without leaving the platform or re-keying anything into a separate spreadsheet.
Limitations
SMMS is pre-revenue with no deployed customer sites — every capability claim on this page is about what the product does today, not about customer outcomes, adoption numbers, or testimonials, because none of those exist yet to cite honestly.
- There is no dedicated vibration or oil-analysis data plane — condition-based maintenance in SMMS means meter readings and condition-based triggers, not a vibration-sensor or oil-sample ingestion platform.
- Predictive-analytics claims are limited to what ships: threshold-based triggers on real meter and condition data, not a machine-learning failure-prediction model.
- There is no Weibull analysis or other advanced statistical reliability modeling — see the FAQ below for what to pair SMMS with if that's a hard requirement.
Frequently asked questions
Can SMMS calculate MTBF and MTTR?
Yes — MTBF and MTTR are computed from your coded failure and work-order history, broken down by asset class. MTTR specifically is modeled as phases (with delay and impact entries), not a single blended number, so you can see which phase of a repair is actually slow.
Does SMMS support Weibull analysis?
No. SMMS does not include Weibull distribution fitting or other advanced statistical reliability modeling today. If Weibull analysis is a requirement for your program, plan to pair SMMS with a dedicated reliability-statistics tool for that specific analysis.
Can I export failure and reliability data for my own analysis?
Yes — failure history, work order records, and RCFA/FMEA data export via CSV/Excel/PDF and the REST API, so a reliability engineer who wants to run their own statistics in an external tool can pull the underlying coded data rather than being limited to SMMS’s own dashboards.
Is criticality scoring built in, or do I have to build it myself?
Criticality scoring is a built-in asset attribute you configure per your own risk framework — it is not a separate module you have to bolt on. It flows into the same asset hierarchy your ISO 14224 taxonomy, failure history, and FMEA worksheets already reference.
What does SMMS mean by "condition-based triggers"?
Condition-based triggers and meter-based PM — not a dedicated vibration or oil-analysis sensor platform. If your program needs raw vibration or oil-analysis data collection, that is not a native SMMS data plane today; SMMS focuses on turning meter readings and manual condition checks into scheduled preventive work.
Every capability, in depth
Bring your reliability program, not just your work orders.
Request a demo and we'll walk your reliability team through the full connected data model — or take the free RMI QuickScan first to see where your program stands today.