Govinda Akumal

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Govinda Akumal

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Govinda Akumal

Industry 4.0: Automation, Robotics & 3D Manufacturing · SRH Berlin University of Applied Sciences

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Projects

Certified

Self-directed project

Predictive Maintenance: Industrial ML for Fault Detection

Condition-Monitoring Engineer · AI / ML · July 2026

92/ 100

A ProoV case study · educational project, not employment

Built an end-to-end rolling-bearing fault detector from vibration data: engineered time-domain and envelope-spectrum features, trained a depth-capped decision tree on training bearings only, and evaluated it on a held-out set with explicit catch-rate and false-alarm metrics. The final memo defended a 0.40 alarm threshold using the student’s own cost numbers and correctly localized the fault to the outer race via BPFO.

Graded against

  • Feature engineering (signal to honest numbers)25%
  • Held-out evaluation (honest measurement)25%
  • Cost-based threshold decision + memo25%
  • Compact model + embedded-budget justification15%
  • Plain-language explanation10%

Passed · pass mark 60/100

What stood out6
  • Used kurtosis as the root split and stated a shallow tree depth of 1 with 3 nodes, which fits the embedded-budget constraint.
  • Reported held-out catch-rate and false-alarm rate explicitly and tied the threshold choice to miss-vs-inspection costs.
  • Correctly mapped the dominant defect frequency to BPFO and the outer race in the maintenance memo.
  • Leakage-Free Feature Engineering
  • Honest Held-Out Evaluation
  • Physics-Based Fault Localization
The work I submitted19 tasks

11 tasks · 6.4k characters · Python · 8 written answers · 437 words

  • Initial Prediction50 characters
  • Load Plot Signal205 characters
  • Load Plot Signal CodePython · 1.8k characters
  • Example Rms WorkedPython · 697 characters
  • Time Features143 characters
  • Freq FeaturesPython · 1.3k characters
  • Fault Location239 characters
  • Train Classifier363 characters
  • Evaluation Heldout288 characters
  • Threshold Decision334 characters
  • Decision Memo1.0k characters
  • Initial Prediction6 words
  • Load Plot Signal15 words
  • Load Plot Signal Code163 words
  • Example Rms Worked72 words
  • Time Features10 words
  • Freq Features126 words
  • Fault Location14 words
  • Train Classifier31 words

Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.

Verified certificateTamper-proof · issued by ProoV
1Project completed
1Verified certificate
92Average score
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