AI-driven diagnostics that keep critical turbines spinning.
VTurboTech ingests high-frequency sensor data, detects micro-anomalies in temperature and vibration, and alerts engineers weeks before a breakdown—saving millions in unplanned outages.
Budget
$160 k – $220 k
Timeframe
8 months
Release Date
2024
Core tech-stack
Edge IoT (MQTT)
Python & FastAPI
InfluxDB / TimescaleDB
React.js Ops Portal
AWS IoT Core, Kubernetes
Services delivered
Field Discovery & Hardware Integration
Data Pipeline & Streaming Analytics
ML Model Development (RUL & anomaly)
Full-stack Dashboard Engineering
DevOps, QA, Cloud Deployment
Client Website
https://vturbotech.ai/
THE CHALLENGE
Unexpected turbocharger failures were crippling production lines.
Legacy SCADA systems logged data but offered no predictive insight; maintenance was reactive, spare-part inventory soared, and every unplanned shutdown cost six figures per hour.
OUR APPROACH
Merged edge sensors with cloud AI in eight lean sprints.
Live Sensor Stream – real-time vibration & temp feeds from each turbine.
RUL Trend Graph – predicted hours to failure, updated every minute.
We retro-fitted vibration and thermo sensors, streamed data into a time-series lake, then trained ML models to forecast remaining-useful-life. Real-time dashboards now visualize health scores, and mobile alerts flag risk before thresholds are crossed.
Anomaly Alert Panel – AI flags early-warning spikes and assigns risk scores.
Asset Health Dashboard – fleet-wide view with drill-downs per unit.
CLIENT’S TESTIMONIAL
With Coding Key’s platform we spot problems days in advance instead of after a shutdown. Downtime is down 70 %, and maintenance is finally proactive.
Ryan Davidson
CEO, ProfitPro
BEHIND THE BUILD
Ryan Davidson
Product Lead
Ryan Davidson
Product Lead
Ryan Davidson
Product Lead
Ryan Davidson
Product Lead
Ryan Davidson
Product Lead
Ryan Davidson
Product Lead
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8+ Years
Average Team Experience
500+
Successful Project Deliveries
4
Continents Served Worldwide
CONTACT US
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