The digitization of industry requires interoperability for data sharing and process automation. We delve into how Edge Computing plays a critical role in achieving interoperability by executing data processing at the source, rather than sending it to a centralized location, and at the same time reducing latency, increasing security, and improving the scalability of the system.
Interoperability is the ability of two or more systems to work together, to communicate, share data and, in short, to understand each other. This is a key concept for companies that need their information systems, data and processes to interact with those of their suppliers or customers, because sharing and re-using information is the best way to mitigate errors.
This interoperability is the last necessary step in the industrial sector to achieve the long-awaited digital transformation and help companies to increase their efficiency, reduce errors and optimize costs thanks to the overall improvement of their processes.
Within the Industry4.0 paradigm, companies are engaged in automation, digitalization and virtualization of their operations and processes. The use of hardware and software is so common that no business can be understood without them. However, there is still a long way to go, in the field of Industry 4.0 because of interoperability challenges.
The heterogeneity of systems, some proprietary and others from different manufacturers and providers adds new difficulties to integration. On top ofthis, is the obsolescence of industrial equipment across many sectors and so, it is clear the need for IT and OT systems convergence.
IT/OTconvergence is the integration of information technology (IT) systems with operational technology (OT) systems. IT systems are used for data-centric computing and OT systems monitor events, processes anddevices, and make adjustments in enterprise and industrial operations. The difference between IT and OT systems is that IT is focused on data andcommunication, whereas OT is focused on behaviors and outcomes. Connectivity is an inherent trait of IT systems, whereas OT systems (particularly older ones)tend not to be natively connectable.
In short,operational technology (OT) would be the hardware and software, as well as all the management protocols of a given industry; while information technology (IT) are the systems and networks that carry and process the data (servers, storage,communication networks, etc.).
Thus, collecting data would be OT, while transforming that data into actionable knowledge is the job of IT. If communication between the two is not fluid, it will be difficult to produce the value that companies need, to carry on in a complete and scalable way theirdigital transformation.
IoT sensors with their data collection capabilities, is one of the keys to interoperability. While OT devices are not normally 'connected' technologies , the use of IoT sensors is the mean to collect,transfer and analyze data.
Interoperability in industry can be approached from different fronts: Process interoperability (accommodating each department to the way the other works), data interoperability (bringing together data networks to serve, also, OT operations) and physical interoperability (new devices and systems designed to integrate both worlds).
While it is true that IT systems and OT systems are increasingly converging, and that one is designed for the other and vice versa, especially with the advent of IoT devices connecting both worlds, there is still a long way to go.
With regard to the implementation of interoperability in the IT/OT area, there are three areas to work on:
Throughout the implementation process, security, is another big challenge when it comes to implementing IT/OT interoperability. Not only from the cybersecurity point of view but, from the need to collaborate between different teams that have never worked together before. There is also the age of different types of systems. Hardware tend to be much older than the software and has more potential of security breaches.
If IT/OT convergence is applied, it will provide no only a greater control and visibility across the enterprise, enabling workers to do their jobs more efficiently, but more security and reliability in the decision making.
In supply management companies are already implementing this total integration of systems through sensors and connectivity solutions. Industry 4.0 itself is based on the premise of integration. One ofthe major drivers of Industry 4,0 is the increasing use of data and analytics.
With the help of advanced technologies such as the Industrial Internet ofThings (IIoT) and machine learning at the Edge, manufacturers will be able to collect andanalyse vast amounts of data from all aspects of their operations. This will allow them to make more informed decisions, optimize processes, and reduce costs.
In manufacturing, IT/OT convergence is key to be more efficient both, in increasing efficiency and productivity. Smart Manufacturing, is about factories being fully digitized, autonomous, and ready to adapt to changing conditions in real time.
Imagine a factory that can respond to changes in demand or supply in real-time, and can produce highly customized and high-quality products. Or in logistics, where it will be much easier to adjust production to the availability of transport trucks, for example, and to coordinate deliveries to the millimeter. That's the power of combining IoT, Edge Computing and AI.
At Barbara we help the industry accelerate its digital transformation by implementing automated decision making in their operations by bringing intelligence directly inside industrial equipments and installations. Developed with cybersecurity by design, and compatible with Edge applications to optimise industrial processes and asset management, Barbara´s Edge Platform is the perfect enabler to address the industry’s biggest challenges and accelerate industrial intelligence.
If you like to learn more on how to make your machines smarter, get in touch.