🏆 Production-Grade Platform

Vehicle Reliability Analytics

End-to-end data science platform analyzing 10,476 real NHTSA complaints with Weibull modeling, Monte Carlo simulation, ALT, and real-time telematics.

10,476
Complaints Analyzed
968
Vehicles Tracked
5.84
MTBF (Years)
1.77
Weibull Shape k
📊 View Dashboard → 🔌 Explore API

All Job Requirements Covered ✅

Every reliability engineering capability you need

📊

Survival Analysis

Kaplan-Meier non-parametric estimation with censored data handling

View Analysis →
📈

Weibull Modeling

MLE fitting for failure mode diagnosis (k=1.77 indicates wear-out)

View Data →
🎲

Monte Carlo

10,000 simulations for system reliability with redundancy analysis

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🔬

Accelerated Life Testing

Arrhenius model with 96x acceleration factor for field prediction

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📡

Telematics & IoT

Real-time sensor processing with 0-100 health scores

View Health →
⏰

Automated Pipeline

APScheduler runs daily ETL automatically (Airflow ready)

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Statistical Methodology

Industry-standard reliability engineering formulas

Reliability Function

R(t) = e-(t/λ)k

Probability of survival beyond time t

Hazard Rate

h(t) = (k/λ)(t/λ)k-1

Instantaneous failure rate

MTBF Formula

MTBF = λ × Γ(1 + 1/k)

Mean time between failures

Arrhenius (ALT)

AF = exp(Ea/kT)

Temperature acceleration factor

🛠️ Technology Stack

Backend

Python 3.10 FastAPI Pandas NumPy SciPy

Statistics

lifelines Weibull Kaplan-Meier Monte Carlo

Infrastructure

Docker Airflow APScheduler AWS EC2

Frontend

HTML5 CSS3 JavaScript Matplotlib

Ready to Explore?

View the complete reliability analysis with all visualizations

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🔮 Try the Live Reliability Predictor

Input vehicle age, component, and mileage — get instant failure probability powered by Weibull distribution. Real-time predictions with 95% confidence.

5
Components
95%
Confidence
<100ms
Response Time
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