Large medical equipment provider
Predictive Maintenance for Autoclave Equipment
Forward Deployed Engineer — Palantir
Flagged machines nearing failure before breakdown
- Deep Learning
- Time-Series Modeling
- Predictive Maintenance
- Physical AI
Problem
Autoclave breakdowns are disruptive and costly when they happen without warning — a large medical equipment provider had no way to see a machine trending toward failure before it actually broke down, leaving maintenance purely reactive.
Approach
Built an ML system that analyzed autoclave operating logs and trained a deep learning model to recognize the patterns that precede a breakdown, surfacing proactive alerts on machines heading toward failure instead of waiting for the failure event itself.
Outcome
Gave the maintenance team visibility into machines trending toward failure ahead of time, shifting autoclave upkeep from reactive to proactive.