TAepcphlincoaltoiognys IIoT Intelligence starts at the edge for industrial automation Edge computing is becoming the sensor on-ramp to the IIoT. Once communication, security, and Internet computing technologies find their way into computing at the edge, the IIoT will begin to reach its potential and make an ever greater impact in the world of industrial factory automation. ON THE TRAIN TO WORK, Lee opened an email on her smartphone sent from a controller operating a surface-mount tool at her factory. Attached to the email was a quality control report that suggested changing the tool’s solder temperature. To generate that email suggestion, the controller had securely sent yesterday’s production data to a cloud-based analytics system to compare current and historical data for the machine. Next , i t ac ces sed the machine manufacturer’s website and obtained the latest recommended settings. Finally, it built a production efficiency report with a suggested solder temperature for today’s production run that would increase yield by 7 percent over yesterday’s run. Lee clicked a link in the email and connected to the controller’s mobile operator interface over a secure, encrypted channel. Lee logged in and navigated to the machine’s solder temperature setpoint, where she entered the recommended value. All this took place before she got to the office. At the network edge The controller operating the surface-mount tool at Lee’s factory operates at the edge of the factory’s network. Systems like these are increasingly able to leverage cloud-based resources to perform edge computing—if computing resources exist as needed along the path from a sensor to the cloud—and if these computing resources reduce the total amount of data to be sent to the cloud for storage, processing, and analysis. As a result, businesses can more quickly identify real opportunities for operational efficiency improvement and meaningful revenue generation. To foster such business benefits, data from the physical world of machines and equipment must be available to the digital world of the internet and information technology systems, quickly, easily, and continuously. Successful industrial internet of things (IIoT) applications require operational technology (OT) professionals to make data from their systems, which monitor and control the physical world, accessible to the data processing systems of information technology (IT) professionals. Once the data is there, cognitive prognostics algorithms running on IT systems can analyze it, refining raw physical data into actionable information that can predict outcomes in real time. The results can be used to improve inventory management and predictive maintenance and reduce asset downtime. But before such benefits can be realized, three problems need to be solved: connectivity, big data, and IIoT architecture. Lee’s factory has a new kind of programmable industrial controller (EPIC), which goes a long way toward solving these three problems. The connectivity problem The internet of things runs on vast amounts of data, generated by the physical world and then transported and analyzed by the digital world. It’s an attempt to achieve perpetual connectivity and communication between people and things and even between things and other things. But in the industrial world, most of these things were never designed to serve this new purpose. They were designed and installed 30 industrial ethernet book 4.2018 SOURCE: OPTO 22 The challenge of edge computing is to provide access to data that brings IT and OT solutions together.
Industrial Ethernet Book 105
To see the actual publication please follow the link above