Networked Intelligence for Mission-Critical Asset Maintenance
Keywords:
Cognitive maintenance, Resilience, Edge intelligence, Distributed reasoning, Manufacturing execution, Logistics, Control theory, Cyber–physical systems, Intrusion detection, Security management, Pollution management, Crisis management, Network management, Logistics management, Autonomous vehicles, Transport systems, Traffic control, Mission-critical networks, Condition-based maintenance, Predictive maintenance, Cloud computing, Fog computing, Edge computing .Abstract
A Distributed Cognitive Maintenance Framework enables network-operated devices to create knowledge through data-informed reasoning and local actions. For mission-critical environments, Machine-to-Machine communication speed, reliability, availability, and consistency must be secured and continuously monitored. External interfaces and device behaviour must comply with security considerations and avoid congesting network bottlenecks during abnormal operation. Data traffic volume has to be proportional to the information gained. Moreover, independent device adaptation must not cause functional degradation of peer devices nor reduce overall network preparedness to handle deviations.
Existing devices operating at the edge of a Fog/Cloud environment are capable of supporting data collection and inference. They can reason locally, adapt operation to local context, and create knowledge that may benefit others. Reasoning capability, decision process transparency, and redundancy through cooperation may enable the application of cognitive maintenance, where local actions, knowledge-discovery processes, and information-sharing are applied to ensure availability. Cognitive maintenance should be considered an alternative, complementary, or add-on to preventive maintenance, condition-based maintenance, and predictive maintenance approaches.
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