Cloud-Orchestrated Edge AI for Autonomous Quality Management in Smart Manufacturing
DOI:
https://doi.org/10.15662/IJEETR.2024.0606017Keywords:
Smart Manufacturing Systems, Autonomous Quality Control, Intelligent Quality Inspection, Edge Artificial Intelligence, Cloud-Based AI Orchestration, Edge–Cloud Integration, Real-Time Anomaly Detection, Predictive Quality Analytics, Industrial Internet of Things (IioT)Abstract
The rapid evolution of smart manufacturing demands intelligent, real-time quality management systems capable of operating with minimal human intervention. This study presents a cloud-orchestrated edge artificial intelligence (AI) framework designed to enable autonomous quality management in smart manufacturing environments. The proposed architecture integrates edge-based AI models for low-latency defect detection, anomaly classification, and process monitoring with cloud-based orchestration for centralized coordination, model lifecycle management, and large-scale data analytics.
By deploying inference tasks at the edge, the system ensures real-time decision-making and reduced network dependency, while the cloud layer facilitates continuous model training, performance optimization, and cross-site knowledge sharing. The framework supports scalable deployment across distributed production units, enhances data security through localized processing, and enables adaptive quality control through dynamic model updates.
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