Question 18
Scenario 2: Smart Manufacturing Quality Control System
An automotive manufacturer implements an IoT-based quality control system that monitors production line metrics, detects defects in real-time, and optimizes manufacturing processes across multiple assembly plants.
System Architecture:
● IoT sensors at production stations (coordinates provided for each plant)
● Quality control hub: (42.3601^(o) N, 71.0589^(o) W)
● Real-time data streams: temperature, pressure, vibration, visual inspection
● ML models for defect prediction and process optimization
Based on the above data, answer the given subquestions.
For deploying the quality control system across geographically distributed manufacturing plants with strict latency and reliability requirements, which architecture approach ensures optimal performance?
Centralized cloud-only deployment
Edge computing with local ML inference, container orchestration, and federated data synchronization
Single server per plant without redundancy
Manual quality control without automated systems