A fog computing industrial cyber-physical system for embedded low-latency machine learning Industry 4.0 applications

Industrial cyber-physical systems are the primary enabling technology for Industry 4.0, which refers to an emerging data-driven paradigm focused on the creation of manufacturing intelligence using real-time pervasive networks and operational data streams. These cyber-physical systems enable objects and processes residing in the physical world (e.g. manufacturing facility), to be tightly coupled and evaluated by advanced predictive analytics (e.g. machine learning models) and simulation models in the cyber world, with the intention of realising self-configuring operations. Thus, this research presents an industrial cyber-physical system based on the emerging fog computing paradigm, which can embed production-ready PMML-encoded machine learning models in factory operations, and adhere to Industry 4.0 design concerns pertaining to decentralisation, security, privacy and reliability.