Design a predictive maintenance system for industrial equipment using machine learning.

Instruction: Explain your approach to data collection, feature engineering, model selection, and how you would deploy and monitor the system in a production environment. Fictional plant: 100 assets, at most two inspections per day, inspections require 24 hours of notice, and a 09:00 risk score predicts failure within 48 hours. Three proposed inspections have expected avoided downtime of 8, 5, and 3 hours, equal inspection duration, and independent benefits. Describe selection, late alerts and evaluation.

Context: The question assesses the candidate's skills in applying machine learning to reduce downtime and maintenance costs in industrial settings, with a focus on real-world applicability and impact.

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I would start with the maintenance workflow because the system has to support real operational decisions: when to inspect, when to replace a part, and how much lead time the team needs to act without causing unnecessary downtime.

Then I...

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