Smart Factory Data Analytics Flashcards
7 cards from real SACA practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Smart Factory Data Analytics flashcards as text
Which technique is used to detect anomalies in sensor time-series data by modeling the expected data distribution and flagging statistical outliers?
Answer: Isolation Forest
Isolation Forest is an unsupervised anomaly detection algorithm well-suited to high-dimensional sensor time-series data in smart factories.
In a smart factory context, what does OEE stand for?
Answer: Overall Equipment Effectiveness
OEE (Overall Equipment Effectiveness) measures how effectively manufacturing equipment is used, combining availability, performance, and quality.
A data pipeline ingests 10,000 sensor readings per second. Which storage architecture is best suited for real-time querying and historical trend analysis?
Answer: Time-series database with a data lake tier
A time-series database handles high-frequency ingestion and fast range queries, while a data lake tier stores historical data cost-effectively for trend analysis.
What is the primary purpose of a digital twin in smart factory data analytics?
Answer: To simulate and monitor physical assets using real-time data
A digital twin is a virtual replica of a physical asset that uses real-time sensor data to simulate behavior, enabling monitoring, prediction, and optimization.
Which data quality issue occurs when the same event is recorded multiple times in a factory data stream due to network retransmission?
Answer: Duplicate records
Duplicate records arise when network retransmission causes the same sensor event to be written more than once, requiring deduplication in the pipeline.
In predictive maintenance, a model is trained on vibration data to forecast bearing failure. Which metric best evaluates this model given that missed failures are far more costly than false alarms?
Answer: Recall
Recall (sensitivity) measures the proportion of actual failures caught by the model, making it the priority metric when missing a failure is very costly.
What does edge computing contribute to smart factory data analytics?
Answer: It processes data close to the source to reduce latency and bandwidth usage
Edge computing runs analytics near the sensors, enabling millisecond-level response and reducing the volume of raw data sent to the cloud.