Workflow — Equipment Maintenance Review

Predictive flags from the work the reliability team does not have time to do.

PM logs, work-order history, vibration analysis reports, oil analysis reports — anomaly detection across maintenance history, MTBF calculation, identification of equipment trending toward failure. Predictive work-order generation into Maximo, Fiix, or UpKeep. Replaces reliability-engineering bandwidth that is the constraint on most plants — this is the work that doesn't happen because nobody has time.

Take the AI Assessment Get a Per-Asset ROI Model

$45–$95

Per hour, reliability engineer (loaded)

Bottleneck

Reliability bandwidth on most plants

60–85%

Log-review work off the reliability desk

What This Replaces

The Reliability Team That Never Has Time for Predictive Work

The work the reliability engineer does on every asset — and the cost of leaving it undone.

The labor

Equipment maintenance log review today moves through reliability engineers at $45–$95 per hour fully loaded. Most plants are reactive — engineers spend their time fighting fires, not running predictive work. The MTBF calculations, trend analyses, and proactive work-order generation that would prevent the next breakdown sit on a backlog because nobody has bandwidth. A mid-size plant with hundreds of critical assets generates millions of data points a year that get logged but never analyzed.

The cycle time

Reactive maintenance is fast — a part fails, a tech replaces it, the line restarts. Predictive maintenance is slow — somebody has to read the vibration report, compare it to baseline, calculate MTBF, schedule the proactive work-order before the failure event. That work routinely doesn't happen because the reliability engineer is in a war room, not at a desk. Every undetected trend toward failure is a future unplanned-downtime event with 100x the cost of the predictive work-order.

The Workflow

Input · Analysis · Output

What goes into maintenance log review, what we do to it, and what shows up in the CMMS.

Input

Maintenance logs + condition data

Preventive-maintenance (PM) logs
Work-order history per asset
Vibration analysis reports
Oil analysis reports
Thermography readings
Operator-reported anomalies
Asset criticality and BOM context

Analysis

Detect, calculate, predict

Anomaly detection across maintenance history
MTBF (mean time between failure) calculation per asset
MTTR (mean time to repair) per asset and per failure mode
Equipment-trending-toward-failure detection
Vibration / oil / thermography signature analysis
Per-asset reliability dashboard inputs
Confidence score per finding; exceptions to reliability engineer queue

Output

Predictive WOs into the CMMS

IBM Maximo (REST APIs)
Fiix (REST APIs)
UpKeep (REST APIs)
Predictive work-order generation per asset
Reliability dashboards with trend evidence
Failure-mode trend reports
Per-asset audit trail with evidence per WO

Side by Side

Equipment Maintenance Review Today vs. With Last Rev

The numbers that matter: cycle time, asset coverage, accuracy, and unplanned-downtime reduction.

Dimension	Reliability Engineer (Time-Constrained)	Last Rev Maintenance Review
Cycle time, log review across asset base	Quarterly or never (bandwidth-bound)	Continuous against full asset base
Asset-base coverage	Top 10–20% of assets reviewed for trends	100% of asset base trend-analyzed continuously
MTBF / MTTR consistency	Spreadsheet-maintained, drift over time	Per-asset MTBF / MTTR refreshed continuously
Vibration / oil / thermography signature analysis	Per-report manual review by senior reliability engineer	Per-report signature analysis with prior-baseline comparison
Predictive WO generation	Spotty — reliability bandwidth-bound	Generated continuously with the trend evidence cited
CMMS integration	Manual WO entry into Maximo / Fiix / UpKeep	Direct via documented Maximo / Fiix / UpKeep APIs
Audit log per finding	Engineer notes, no log-content lineage	Source log + trend basis + model version + confidence per finding

How It Works

From Maintenance Log to Predictive Work-Order

Five steps. Every one logged. Every one reversible if your confidence threshold isn't met.

Submission Lands

PM logs, work-order history, vibration analysis, oil analysis, thermography readings, and operator-reported anomalies pulled from Maximo, Fiix, UpKeep, or your CMMS — paired with asset criticality and BOM context.

Extraction & Classification

Anomaly detection across maintenance history. MTBF and MTTR calculation per asset. Equipment-trending-toward-failure detection. Vibration / oil / thermography signature analysis with prior-baseline comparison. Per-asset reliability dashboard inputs.

Validation Against Reliability Bar

Findings validated against the plant's reliability playbook and per-asset criticality rules. Anything below your confidence threshold per finding is routed to the reliability engineer review queue — your call which queue, ours or yours.

Push to CMMS

Predictive work-order generation per asset into IBM Maximo, Fiix, or UpKeep via the documented integration. Reliability dashboards with trend evidence. Failure-mode trend reports for the reliability and maintenance teams.

Audit Log Persisted

Every anomaly detection, MTBF / MTTR calculation, and predictive WO basis logged with the source log, model version, and confidence score. Reliability-audit-ready, RCM-program-ready, and yours.

Compliance & Defensibility

Built to Meet the Quality Bar Reliability Programs Already Run On

RCM and SAE JA1011 / JA1012 conformance

Reliability-Centered Maintenance (RCM) program requirements supported through structured per-asset audit trails. SAE JA1011 / JA1012 RCM evaluation criteria reflected in the workflow. The audit log produces what was extracted and analyzed for each predictive WO.

ISO 55000 asset-management posture

Asset-management requirements (ISO 55000 / 55001 / 55002) supported through structured asset-criticality, MTBF / MTTR, and trend-analysis records. Audit-ready for asset-management certification surveillance.

Maintenance defensibility

When customer or regulatory audits require evidence of preventive-maintenance discipline (FDA 21 CFR Part 820 medical device, AS9110 aerospace MRO, IATF 16949 auto), the audit log produces what was tracked and trend-analyzed across the asset base. Cleaner chain of custody than the reliability engineer's spreadsheet today.

Plant data and condition-data residency

Maintenance logs and condition-monitoring data may reference proprietary process IP. Deployable on-prem, in your VPC, or in our SOC 2 environment. Encryption in transit and at rest; retention policies tied to your reliability and maintenance recordkeeping rules.

Common Questions

What Manufacturers Ask About Equipment Maintenance Review

Those are the systems where work orders, asset registers, and maintenance history live. The competitor on this page is the reliability-engineering bandwidth that's the binding constraint on predictive maintenance — typically reliability engineers at $45–$95 per hour fully loaded, with the predictive analysis work routinely sitting on a backlog because the team is in reactive mode. We integrate directly into your existing Maximo / Fiix / UpKeep deployment and deliver predictive work-orders with the trend evidence cited.

Most plants are in a reactive maintenance posture because the reliability engineer is bandwidth-constrained. We absorb the routine log-review work continuously, surface trend-toward-failure findings with the evidence cited, and generate predictive work-orders so your reliability engineer triages the findings and approves the work-orders. Reliability engineers shift from log-reading to investigation and program design — the higher-leverage work the role is supposed to do.

Our pilot success threshold is anomaly-detection and trend-analysis accuracy at parity with or above your incumbent reliability engineer process, measured on the same shadow-data sample of historical maintenance logs. Anything below your defined confidence threshold per finding is routed to the reliability engineer review queue.

Per-asset vibration baselines, oil-analysis chemistry trends, and thermography-pattern baselines are tracked. New reports are compared against per-asset baselines — anomalies surface with the prior-baseline reference and the per-failure-mode signature cited. We don't make the engineering call on borderline patterns; we surface the basis so the reliability engineer makes the determination.

Both data sources are first-class inputs. IIoT sensor streams (vibration, temperature, current draw, runtime hours) integrate alongside traditional vibration / oil / thermography reports. The analysis adapts to whatever data your asset base produces.

Yes — through the documented integration surface each platform supports. Maximo via REST APIs; Fiix via REST APIs; UpKeep via REST APIs. IIoT platforms (PTC ThingWorx, AWS IoT, Azure IoT Hub, GE Predix) integrate via their published APIs. Your IT and reliability teams review and approve service accounts. We do not require platform-side custom development.

Maintenance-review pilots typically run 6–8 weeks: 1–2 weeks of integration and per-asset-class criticality and baseline mapping with the reliability team, 4 weeks of shadow-mode running on real maintenance logs with no CMMS-side WO writes, 1–2 weeks of supervised cutover on a constrained scope (one production line, one asset class). Production rollout is staged after the pilot meets your accuracy and reliability-management sign-off.

We benchmark against your current reliability-engineering cost — typically $45–$95 per hour fully loaded with most of the cost going to reactive work. Our target is 25–45% of that cost for the routine log-review portion at higher coverage and continuous cycle time. Pricing structures around volume tiers and outcome SLAs (unplanned-downtime reduction, predictive-WO precision), not hourly billable rates.

Two Ways to Start

Take the AI assessment for a structured read on equipment-maintenance-review feasibility. Or talk to us if you already know reliability bandwidth is the constraint on your predictive maintenance program.

Self-serve · 8 minutes

Take the AI Assessment

A short structured assessment that maps your monthly maintenance event volume, CMMS, and reliability staffing model to AI feasibility and ROI.

Talk to a specialist

Get a Per-Asset ROI Model

Send us your monthly maintenance event volume, your CMMS, and your reliability staffing model. We'll come back with a per-asset unit-cost comparison and a 6–8 week pilot plan in 5 business days.

Other Workflows

More Manufacturing Workflows We Replace

The same approach, applied to the other document-heavy labor lines on your quality and operations budget.

Calibration Certificate Processing

Calibration certs → GAGEtrak, IndySoft, ProCal — with NIST chain validation and out-of-tol recall alerts.

Safety Incident Processing

Incident narratives, photos, witness statements → OSHA 300/300A determination and EHS record.

NCR / 8D / CAPA Processing

8D reports drafted from NCR — root cause, containment, corrective action — into MasterControl, ETQ.

Visual Quality Inspection

Defect classification at line speed. SPC charts that update before the shift ends.