Operational Technology Viewpoints

Enterprise cloud providers, such as AWS, Google, and Microsoft, are targeting the data-rich industrial IoT edge as a primary means of delivering analytics-driven business improvement.

Requirements at the Industrial IoT edge are driving renewed tiering between thick vs. thin edge devices and intelligent endpoints.

Blockchain in industry provides clear business benefits. Examining 24 pilot programs found sweet spots with improved revenue and margins.

Prospects for growth in industrial IoT solutions are looking up as Industrial IoT Edge 2.0 emphasizes ease of use, self-service, turnkey operation to address the complexity associated with early installations, which has been a significant growth governor to date.

The industrial IoT edge 2.0 vision has migrated from a pervasive infrastructure technology to one that emphasizes outcome-driven use cases.

The use of a wide variety of mobile devices can expand the reach of mobility in EAM systems.  In addition, handheld smart devices have grown in capability alongside EAM and field service systems with technologies like GPS, GIS, RFID, and embedded cameras. 

Business models are changing in the age of IIoT. Many industrial enterprises are moving from large capital expenditures toward a "pay-as-you-go" model; commonly referred to as equipment-as-a-service (EaaS), or in some cases “Servitization”.

MES is the backbone for lower cost, higher quality and faster production for the Smart Factory of the future.  It is the future for newer more complex, innovative and more personalized products. 

Interpretable machine learning models provide insight into relationships between inputs and outputs. This enables them to not only produce predictions but also explain them.

Data or information modeling enable information interoperability by specifying the content of specific information and where it is stored.  Models for asset information enable these types of data to be managed efficiently.