Manufacturing Case Study
Driftmoor Group
A predictive maintenance system that flagged equipment failure risk weeks early.
-18%Downtime
The Challenge
Where things stood before
When Driftmoor Group first reached out, limited visibility into production issues until they'd already become expensive was the issue sitting at the top of their list.
Their team suspected the root cause but hadn't had the bandwidth to actually address it properly.
The Solution
What we built
We started by getting a clear picture of exactly where things were breaking down before proposing anything.
The result was straightforward: a predictive maintenance system that flagged equipment failure risk weeks early, built specifically around what Driftmoor Group needed.
- Structured so Driftmoor Group's own team could maintain it going forward
- Tested thoroughly before launch to avoid post-launch surprises
- Benchmarked against clear, agreed-upon success metrics from day one
- Delivered within a 4-week timeline without cutting scope
Results
The impact, by the numbers
-18%
Downtime
+36%
Reporting Accuracy
-23%
Maintenance Response Time
+53%
Throughput
Tech Stack
Built with
PythonPyTorchNode.jsMQTT
Eastwick Group
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