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THE IoT


and the result is generally isolated to a single machine.


How does IT differ from OT? Perhaps the most important distinction between IT and OT can be explained in hardware vs software. In the OT space, hardware is king, with countless devices, robots and machines produced to do individual tasks. OT software, however, is very limited in its scope, normally able to run a small number of necessary functions required to operate the machinery. IT is the exact opposite; hardware is far more generic, yet software is far more comprehensive. For instance, industrial computers, as long as they are technically adequate, can run a multitude of applications. Communications devices are relatively simple from a hardware perspective but vary hugely in their software capabilities. The task orientation for OT is hardware, and for IT it is software.


Lifespan and longevity is also different for IT applications. Where OT relies on stable, long-lifetime products and components, IT has to work differently. Technology moves at a fast pace, and with this development comes different opportunities… and threats. As new UIs and processing software becomes available, upgrades can sometimes only be facilitated with upgrade to operating systems, CPUs and other hardware.


Benefits of converging OT with IT With the surge of devices aimed at the Industrial Internet of Things (IIoT), the harvesting, analysis and reporting on data has opened the doors to transparency and control not seen before in industrial environments, and with the addition of cloud-based data storage, national and international data can be monitored and acted upon in real time.


OT to IT convergence allows more effective collaboration between various operations in businesses, for instance, connecting manufacturing to engineering, and then on to sales. Transparency and reporting on the production line gives the sales department the tools to manage customer expectations. Similarly, if a customer requests a change in


There are various applications and methods to calculate this OEE value. For instance, Moxa’s UC8112 ARM-based embedded PC runs their ThingsPro software, which essentially uses Python applications to bridge the gap between OT hardware and sensors, and reporting and maintenance UIs.


“ MAY 2021 | ELECTRONICS TODAY 35 ”


specification, this can be delivered immediately and acted upon by the manufacturing team, rather than a more manual process which is prone to human error. Automatic alerts can be sent from inspection robots to engineering to highlight a run of defects which could be caused by malfunctioning machinery further down the production line. If this information can be pushed to the relevant departments in real time, they can be acted upon quickly, minimising waste and downtime. Asset management is another useful tool available to OT/IT integrated systems. Predictive maintenance is one of the key benefits of integrating IT technology into legacy OT machinery. A great example we’ve seen at Impulse is the integration of a small device, no bigger than a matchbox, into legacy lathes used in metal machining. These tiny devices simply stick to the outside of the machine and monitor acoustic levels and temperature, alerting operators of a change in either of these. These changes indicate vibration or wear and allow maintenance to replace components nearing their end of life before they fail. Predictive maintenance is one of the most popular uses of IT in the OT space, as it both removes the need for routine maintenance and cursory checks and minimises downtime by alerting of impending issues before they occur.


Overall equipment effectiveness Finally, Overall Equipment Effectiveness, or OEE, is a popular method of monitoring the health and effectiveness of OT machinery. The method is to analyse three key components of the machine’s operation and use them to form a figure of efficiency: availability, or the amount of uptime the machine has had over a certain time period, performance, which is denoted by the speed in which a machine is able to perform its function, and quality, which is generally a comparison of good to bad output per unit, or the “first pass yield”. OEE is calculated by multiplying these three values together, which gives equipment owners and operators the ability to tweak processes, alter operation, and make hardware adjustments, with a view to improving this figure and


seeing it happen in real time. By improving the OEE value of one or more machines, the productivity and efficiency of the overall production facility is therefore increased. There are various applications and methods to calculate this OEE value. For instance, Moxa’s UC8112 ARM-based embedded PC runs their ThingsPro software, which essentially uses Python applications to bridge the gap between OT hardware and sensors, and reporting and maintenance UIs. Of course, Python applications can be developed to run on a raw Linux installation without the need for any third-party software, but what ThingsPro brings is a templated system which can be accessed via Python code, which does the hard work of connecting to IO, creating tags and more users, straight out of the box. With increased data transfer comes increased security risks.


When physical machinery can be hacked, that’s when things can become dangerous, so OT networks need to be protected in just the same way as the most sensitive of data. There are many processes, barriers and security measures that can be put in place, down to a simple locking mechanism on the PC itself, but OT / IT security goes much further than physical access. You can learn more about how to secure your OT network from the Impulse knowledge base, where we highlight some of the key physical and software barriers that can be put in place when securing an OT network.


Bridging the gap between OT machinery and IT data tools can do nothing but improve productivity and efficiency. From a simple sensor through to a full suite of devices, taking measures to improve transparency and monitoring of OT devices opens the door to much more efficient operating procedures, the end product being a potential reduction in overheads and downtime.


Impulse can help with the transition to an Industrial IoT solution, providing hardware from the server to the edge to facilitate simple monitoring applications through to full-scale AI deep learning systems.


Impulse Embedded www.impulse-embedded.co.uk


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