Industry 4.0 & Data Analytics Flashcards
6 cards from real DMD practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Industry 4.0 & Data Analytics flashcards as text
What is 'digital thread' in advanced manufacturing?
Answer: A connected data flow that links all phases of a product's lifecycle from design through manufacturing to service
The digital thread creates a seamless data connection across the entire product lifecycle, enabling traceability and insight from design intent to as-built and in-service states.
In manufacturing analytics, what is 'time-series analysis' used for?
Answer: Analyzing data points collected over time to identify trends, cycles, and anomalies in machine or process behavior
Time-series analysis identifies temporal patterns in sequential data, enabling manufacturers to detect trends, seasonal variations, and anomalies in process data.
What is the purpose of SCADA (Supervisory Control and Data Acquisition) in digital manufacturing?
Answer: To monitor and control industrial processes in real time by collecting data from sensors and sending control commands
SCADA systems provide real-time monitoring and remote control of industrial processes by aggregating sensor data and enabling operators to adjust parameters.
Which approach uses AI to automatically adjust machine parameters during production to optimize output quality?
Answer: Closed-loop adaptive control
Closed-loop adaptive control uses real-time sensor feedback and AI algorithms to continuously adjust machine parameters and maintain optimal quality output.
What is 'condition-based maintenance' (CBM) in digital manufacturing?
Answer: Performing maintenance only when sensor data indicates a component is approaching failure, not on a fixed schedule
CBM uses real-time monitoring data to trigger maintenance actions when a component's condition reaches a defined threshold, reducing unnecessary maintenance and downtime.
What is 'machine learning inference' in a manufacturing context?
Answer: Using a trained ML model to make real-time predictions or classifications on new production data
Inference is the deployment phase of machine learning where a pre-trained model is applied to live data to generate real-time predictions (e.g., defect detection).