Varun M.S completed Predictive Maintenance: Industrial ML for Fault Detection

Built a compact rolling-bearing fault detector end to end: engineered time-domain features, trained a shallow decision tree on training bearings only, and evaluated it on a held-out set with catch-rate and false-alarm rate. The candidate also wrote a maintenance memo that defended the alarm threshold using their own measured trade-off and tied the dominant defect frequency to the bearing fault location.

• Leakage-Free Feature Engineering
• Honest Model Evaluation
• Compact Interpretable Modeling
• Cost-Based Operational Decision Making