IIC Journal of Innovation 6th Edition - Page 40

Spotlight on the Industrial IoT Analytics Framework temporarily, where the readings can be scanned and evaluated depending on the type of analytics. The stored values may be discarded or archived for further calculations. Data scientists can explore the archived data using statistics to compute correlations, and apply algorithms to classify and cluster the evidence over time. Industry subject matter experts have a good understanding of the context and condition of the process and assets, and can interpret Industrial analytics functionality is deployable throughout the IIoT architecture that is covered in the Industrial Internet Reference Architecture (IIRA). The IIRA addresses the need for a common architecture framework to develop interoperable IIoT systems for diverse applications across a broad spectrum of industrial verticals. The capabilities needed for successful industrial analytics solutions Figure 2. Analytics Mapping to the Industrial Internet Reference Architecture are shown in Figure 2 with respect to the other concerns in the IIRA. Each capability is realized by a set of functions defined by use cases that meet the stakeholders’ expectations, especially with regard to non- functional requirements. and validate the readings and recommend cleansing filters. It is this combination of data science and subject matter expertise that produces the best result The fundamental prerequisite for industrial analytics is availability and access to data from the industrial process and related assets. Data is collected close to the process through connections and stored, at least This release of the Industrial IoT Analytics Framework is only the beginning of a journey to create a comprehensive study of all aspects of how analytics can be used in the Industrial Internet; there is still a lot of work IIC Journal of Innovation I N C ONCLUSION - 39 -