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On Cyber-Physical Systems, IIoT and Digital Twins
With GEM PRECARE IIoT Platform for OEE and Predictive Maintenance
The Cyber Physical System (CPS), Internet of Things (IoT) and Digital Twin are all central concepts in Industry 4.0, often used interchangeably in discussions about Industry 4.0. It is therefore worthwhile to examine what each means and how they relate to each other.
The phrase ‘Cyber Physical System’ is said to have been coined for the first time in 2006 by Helen Gill of the National Science Foundation (NSF). The origin of the phrase ‘Internet of Things’ is generally ascribed to Kevin Ashton while at MIT in 1999, whereas the origin of the phrase ‘Digital Twin’ is generally ascribed to Michael Grieves while at University of Michigan in 2001. The phrase ‘Industrial Internet of Things’ was a recent addition to indicate the use of IoT in industrial applications as opposed to consumer applications.
A CPS is generally defined as a combination of physical (mechanical) components, transducers (sensors and actuators), and information technology (IT) systems (network/communication systems and computation/analysis/control systems). Some definitions include the human, such as the machine operator. In other words, a CPS is a physical world system (machine only or machine plus human) that is connected to the cyber world. A CPS can be either a closed-loop or open-loop system; meaning that it may sense the real-world parameters of the physical system and control it, or it may just sense the real-world parameters and make these available for analytical purposes.
IoT or IIoT is generally defined as a combination of any of the following: trackable objects (such as RFID tags), data objects (such as sensors), interactive objects (such as actuators) and smart objects (such as software components that act on sensor data for any purpose, including pre-processing, control, analytics, etc.).
A Digital Twin is a digital replica of a physical asset. The definition of a Digital Twin emphasizes the connection between the physical and the digital replica, and the data that is generated using sensors. A Digital Twin integrates transducers, artificial intelligence/machine learning, data analytics and context awareness. An example of context awareness is an intelligent thermostat, which senses who is present, so that the person’s preferences for ambient conditions can be taken into consideration.
The CPS concept emerged primarily from a systems engineering and control perspective, whereas the IoT concept emerged primarily from a networking and IT perspective with origins in the RFID context. The Digital Twin concept on the other hand, emerged from an artificial intelligence/machine learning perspective. Nonetheless, all three can be and are being used interchangeably, given that the definitions of the three concepts are converging over time.
GEM Precare agent technology IP straddles all three definitions and therefore GEM refers to CPS, IoT/IIoT and Digital Twin interchangeably. GEM agents acquire data on status, operation, ambient conditions, operator-in-the-loop, as well as other aspects of the operation of a machine, resulting in a multi-dimensional Digital Twin representation of a machine. The agents assign semantical meaning to the data, creating an exact digital replica of the machine’s visible/non-visible signaling interface. GEM agents can be additive to an existing in-the-loop controller, such as a PLC, they can be integrated into the in-the-loop-controller, or they can include the in-the-loop controller.
GEM agent technology IP is application-agnostic and can be deployed in any industrial or consumer application. In addition, GEM has developed market leading subject matter experience in particular in smart manufacturing, with focus on semiconductor and electronics manufacturing.
GEM Precare agents seamlessly connect manufacturing equipment to the GEM Precare Industry 4.0 IIoT platform, which provides manufacturers literally overnight with an upgrade to smart manufacturing without the cost of overhauling their factory floors with new equipment. The solution provides manufacturers with important KPIs, such as OEE, availability, performance, quality, MTBF, MTBA as well as the ability to predict when to conduct equipment maintenance.
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