How would you develop and deploy a machine learning model to predict and prevent machine failure in a manufacturing setting?

Instruction: Outline the end-to-end process, from data collection and feature engineering to model development, evaluation, and deployment, including how you would monitor and update the model.

Context: The question assesses the candidate's ability to apply machine learning in an industrial context, focusing on predictive maintenance and operational efficiency.

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I would start with the operational question, not the model: how much lead time the plant needs, what type of failure matters most, and what action the team can take when risk is high. A predictive maintenance model is only useful if it helps maintenance planning, spare-parts decisions, or downtime...

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