Industrial IoTFactorynext

$2.3M cost avoidance per annum

AI-driven maintenance scheduling to prevent costly equipment failures.

Challenge

Unplanned downtime was costing Factorynext millions annually. Traditional scheduled maintenance was either too frequent (wasting parts) or too late (causing failures).

Approach

We implemented a predictive maintenance system using vibration and thermal sensor data. The system identifies early signatures of wear and schedules maintenance precisely when needed.

  • Saved $2.3M in the first year by avoiding unplanned equipment failure.
  • Increased overall equipment effectiveness (OEE) by 14%.
  • Extended machine life cycles by an average of 22%.

Results

$0M
Annual Cost Avoidance
0%
OEE Increase
We've moved from reactive to proactive. The ROI was clear within the first six months.
Head of Operations, Factorynext

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