Data analytics Framework using Cyber Physical System (CPS) approach for industrial IoT devices.

The ever growing use of sensors, IoT based networked devices and machines on the factory shop floor has resulted in the continuous generation of high volume data which is known as Big Data. A number of efforts have emerged to look at how Big data from the devices and equipment on the factory shop floor can be analysed in the right context and for a meaningful purpose. Amongst these efforts, Cyber-Physical System (CPS) has received a lot of attention. CPS focuses on the integration of computational applications with physical devices, being designed as a network of interacting cyber and physical elements. CPS control and monitor real-world physical entities and infrastructures generally using feedback from sensors they monitor. This research will look at designing a new framework for processing large amounts of data generated by sensors and equipment in an industrial environment. The framework will look at implementing an intelligent data analytics hub using the CPS approach.

This research will involve

• A comprehensive critical evaluation of the current CPS models/architectures and the simulation tools for structured and unstructured data sets for manufacturing systems.
• A comprehensive critical evaluation of the current cloud/big data analytical tools for analysing structured and unstructured data from manufacturing systems.
• The design of a CPS model/architecture for the current devices installed in the high value-added manufacturing environment and an intelligent data analytic hub such that it will cater for both structured and unstructured data sets.
• Develop appropriate mathematical models to capture the key characteristics of the various CPS architectures and proposed models for data analysis.
• To implement and evaluate the resulting architecture on appropriate hardware platforms in test beds installed in the high value-added manufacturing environment.