IIC Journal of Innovation 12th Edition | Page 90

Shades of Digital Twinning operations with business-value: better ROI, lower maintenance costs and other operational benefits. IoT is becoming the core driver of process improvement. Upper management may not necessarily care about the architecture of the IoT, but it does need to have the right information at the right time. The architecture is important to ensure that the maximum benefit from IoT is realized. I O T G ROWING P AINS : A D IGITAL T WIN P ERSPECTIVE The Internet of Things (IoT) is proliferating with the advent of affordable and accessible processors and sensors enabling more businesses to discover the value in connecting devices to their Information Technology (IT) systems. Sensors for devices are readily available and the cloud has become ubiquitous. Low-cost data storage and analysis for processing vast amounts of data are all merging with new wireless protocols into a powerful force for digital industrial transformation. The focus for IoT and digital twin techniques has been on data collection, visualization and comparison with behavioral models: the twins. These are needed for catching anomalies that indicate imminent failure, but they may also show what factors lead to failure. This information can be used to mitigate failures by changing system behavior. This means changing software; using a device shell on a self-aware system with version and life-cycle management. The IoT is ushering in the fourth industrial age—Industry 4.0—in an evolution of manufacturing and production from centralized to decentralized and a merger of Operational Technology (OT) with IT. The rise of smart manufacturing is being propelled by connecting ever more powerful devices for factory control directly to the network. As these devices gather and preprocess operational data, the ability to mirror machines and their control in digital models has given rise to the concept of Digital Twins. Pairing of a digital twin and a physical device enables virtual analysis and monitoring to predict and prevent issues before they impact operations. An IoT system could be built without standards. Standards, however, are necessary to build interoperable IoT systems. Different aspects of an IoT system have different requirements for standardization. Simulation models could benefit from CAD model standards whereas device proxies need standard protocols to talk with the device. Particularly, industrial systems are often composed of components from diverse sources. Standards will be necessary for them to interact. Defining how IoT devices are developed, tested, deployed and used across operations, as well as the interoperability for updating and improving functions, will provide individual smart manufacturing 1 Some standards for industrial data exchange exist, such as OPC-UA 1 ; but they need updating for security, if nothing else. https://opcfoundation.org/markets-collaboration/ids/ IIC Journal of Innovation - 85 -