field log 02 / entry 04·ml + full-stack
predictive maintenance
sensor data · fault forecasting
industry-partnered project · specifics abstracted for privacy
the problem
industrial cooling equipment fails in ways routine maintenance schedules miss, and unplanned downtime is expensive. the question: could sensor history flag a fault before it happened?
what i built
a dashboard that runs sensor data through a statistical pipeline built on generalized extreme value (gev) and generalized pareto (gpd) models, which target the rare tail events that precede failures, then surfaces the resulting risk.
a next.js front end over a documented fastapi backend, with a one-click analysis run per machine.
stack
next.js/typescript/fastapi/python
outcome
a working dashboard, end to end. the partner and their data stay private, so this entry is deliberately abstracted to the method and stack.