Pavan Kumar completed Predictive Maintenance: Industrial ML for Fault Detection

Built an end-to-end rolling-bearing fault detector from vibration data: visualized the faulty waveform, engineered time- and frequency-domain features, trained a shallow decision tree on training bearings only, and evaluated it on held-out bearings with catch-rate and false-alarm metrics. The work also localized the fault to the outer race via BPFO and defended an alarm threshold with a maintenance-focused memo grounded in the candidate’s own results.

• Leakage-Free Feature Engineering
• Honest Held-Out Evaluation
• Physics-Based Fault Localization
• Cost-Aware Threshold Selection