Evidence From the Field

Case Studies

Anonymized outcomes from maintenance and reliability teams at discrete manufacturers who deployed Gearcadence across their machine fleets.

Outcomes

Predictive maintenance in production

Each case represents a real deployment. Company names and locations are withheld at customer request — numbers and failure modes are factual.

Automotive Stamping

Tier-1 Michigan Stamping Facility Eliminated Repeat Gearbox Failure Cycle

A 220-press facility had experienced the same gearbox failure mode three times in four years on their primary transfer line. Fixed-interval PM schedules were missing the degradation window by two to three weeks. Gearcadence edge sensors detected the spectral anomaly 61 hours before the next projected failure — enough time to schedule a planned corrective job during a weekend shift without production impact.

61 hrs Advance warning before failure
3→0 Repeat failure events in 18 months
$340K Estimated avoided downtime cost
Food Processing

Illinois Packaging Line Reduced Emergency Parts Orders by 40%

The maintenance team at a high-throughput food packaging facility was spending disproportionately on reactive parts procurement — sourcing bearings and shaft seals at premium emergency pricing when assets failed without warning. After deploying Gearcadence across 48 machines, the time-to-failure forecasting enabled the team to order replacement parts at planned lead times in 78% of corrective events.

40% Reduction in emergency parts spend
78% Corrective jobs on planned schedule
48 Assets monitored at deployment
Metal Fabrication

Ohio CNC Facility Cut OEE Losses on Spindle Assets by More Than Half

Spindle bearing degradation on a 65-machine CNC shop had been driving 6.8% OEE loss annually through unplanned stoppages. The reliability engineer lacked the vibration analysis background to interpret SCADA historian data without external consulting support. Gearcadence ingested the existing historian data and surfaced ranked alerts without requiring a data scientist — the team acted on the first TTF forecast within 72 hours of go-live.

3.1% OEE loss remaining after 12 months
72 hrs Time to first actionable TTF forecast
65 CNC assets monitored

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