Harita J completed Predictive Maintenance: Industrial ML for Fault Detection

Built an end-to-end rolling-bearing fault detector using leakage-free training on bearing vibration features, a compact depth-capped decision tree, and held-out evaluation with catch-rate and false-alarm rate. The candidate also produced a maintenance decision memo that justified a 0.60 alarm threshold using explicit cost trade-offs and translated the result into plain language for operations staff.

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