Darshil Patel

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Darshil Patel

Mechanical Engineering · Nirma University

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Projects

Certified

Self-directed project

Predictive Maintenance: Industrial ML for Fault Detection

Condition-Monitoring Engineer · AI / ML · August 2026

84/ 100

A ProoV case study · educational project, not employment

Built an end-to-end rolling-bearing fault detector using vibration snapshots, physics-based time and frequency features, and a compact decision tree sized for embedded use. The work includes a held-out evaluation and a maintenance memo that justifies the alarm threshold with explicit cost trade-offs, catch-rate, and false-alarm figures, while identifying the outer-race fault from the dominant defect frequency.

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 a depth-capped decision tree and explicitly stated depth 2 with 5 nodes against an embedded budget.
  • Selected kurtosis as the strongest time-domain fault indicator, which aligns with impulsive bearing damage.
  • Wrote a maintenance memo that ties the threshold to concrete euro costs and names the outer race from the BPFO peak.
  • Included a plain-language analogy to explain why damaged bearings produce distinctive vibration patterns.
  • Leakage-Aware Model Building
  • Physics-Informed Feature Selection
The work I submitted17 tasks

9 tasks · 5.6k characters · Python, JavaScript · 8 written answers · 452 words

  • Initial Prediction62 characters
  • Load Plot Signal CodePython · 1.8k characters
  • Example Rms WorkedPython · 697 characters
  • Time Features143 characters
  • Freq FeaturesPython · 1.1k characters
  • Train Classifier363 characters
  • Evaluation Heldout283 characters
  • Threshold Decision335 characters
  • Decision MemoJavaScript · 835 characters
  • Initial Prediction9 words
  • Load Plot Signal Code163 words
  • Example Rms Worked72 words
  • Time Features10 words
  • Freq Features117 words
  • Train Classifier31 words
  • Evaluation Heldout24 words
  • Threshold Decision26 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
Certified

Self-directed project

Driving Supply Chain Sustainability via Data Governance

Product Compliance Specialist · General · August 2026

78/ 100

A ProoV case study · educational project, not employment

Built a structured battery-passport compliance package for a single cell, including regulated-field classification, access-tier design, a working lifecycle carbon calculation, and a supplier gap audit. The submission shows practical judgment in separating known, computable, and missing data, then turning the remaining gaps into actionable upstream requests with deadlines and required formats.

Graded against

  • Supply-chain gap attribution and supplier requests30%
  • Judgment under regulatory ambiguity20%
  • Access-tier design judgment15%
  • Carbon-footprint methodology and calculation15%
  • Passport data-model completeness and traceability10%
  • Internal consistency across the package10%

Passed · pass mark 60/100

What stood out6
  • Ran an actual carbon-footprint calculation and interpreted the result correctly, emphasizing that upstream raw materials dominate the footprint.
  • Produced a coherent access-tier split across public, legitimate-interest, and restricted views rather than treating all passport data as equally visible.
  • Attributed every remaining gap to a supplier tier and drafted two concrete requests with field names, regulatory basis, format, and deadlines.
  • Leakage-Free Compliance Classification
  • Honest Regulatory Ambiguity Judgment
  • Lifecycle Carbon Calculation
The work I submitted16 tasks

8 tasks · 6.6k characters · Python · 8 written answers · 519 words

  • Passport Field Defences1.2k characters
  • Passport Field Classification649 characters
  • Carbon Footprint CalculationPython · 1.3k characters
  • Access Tier Design894 characters
  • Supply Chain Gap Audit316 characters
  • Supplier Data Request1.4k characters
  • Passport Verdict Reveal298 characters
  • Final Submission570 characters
  • Passport Field Defences147 words
  • Passport Field Classification1 word
  • Carbon Footprint Calculation130 words
  • Access Tier Design1 word
  • Supply Chain Gap Audit1 word
  • Supplier Data Request143 words
  • Passport Verdict Reveal32 words
  • Final Submission64 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
2Projects completed
2Verified certificates
81Average score
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