Your question is Real-Time Manufacturing Anomaly Detection. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How would you design an end-to-end pipeline for real-time anomaly detection in a manufacturing plant?
Explain how you would ingest and validate sensor data, detect anomalies with low latency, generate actionable alerts, and support offline retraining. Cover system sizing, online versus batch processing, model selection, evaluation without perfect labels, monitoring, drift, training-serving skew, and failure handling. State the clarifying questions and assumptions you would need before committing to an architecture.