The Internet of Things on an industrialized scale – digital transformation for industry
Every area of business and industry is becoming digitized. We expect technology-based start-ups to deploy digitization by default. However, older, traditional industries’ use of technology — especially the very latest, ground-breaking technology — is less common. That’s not because of a reluctance to embrace the new in those industries. Instead, it comes from an awareness of the importance of maintaining established & successful practice, ensuring safety, and ensuring return on investment.
But in manufacturing, utilities, mining, and aerospace, for example, there is gradually emerging a new breed of technology which already has game-changing effects.
The industrial internet things (IIoT) goes one step beyond what many people consider when presented with the concept of IoT. Forget the ideas of domestic devices — some of them clearly harmless fripperies such as so-called smart fridges – and think more about how technology can be used to interpret high-volume streams of data from existing machinery, plant, equipment, sensors, and controllers.
Where the average smartphone today possesses perhaps a few dozen sensors (step counters, light sensors, a simple microphone, face recognition) an industrial motor will, as standard, come with maybe a couple of thousand sensors.
The amounts of data being created, therefore, by modern industrial units are potentially massive.
It’s worth noting that industrial internet of things goes beyond just “smart” devices, and as a term encompasses data exchange and data analysis functions. A stand-alone device can be the smartest device on a factory floor, for instance, but unless it is appropriately networked into the rest of the digital infrastructure, it remains mute.
Additionally, unless real, practical, business-improving use can be made of the data produced by even a single unit, the internet of things remains pointless from the enterprise’s point of view.
Industrial internet of things-enabled devices and machinery can in many cases be used to control, as well as monitor. But this additional facility may not be used to optimum effect unless proper, intelligent use can be made of data – the attenuation of devices’ settings and performance may not be being done “blind,” but perhaps could be done better.
In many industries, investment in the supporting infrastructure explicitly required for the internet of things deployment is not a priority. As new plant, devices, and machinery become available, they often come equipped with the IoT capability.
Many enterprises are not making use of this built-in capability, or if they are, they are limiting themselves because of a lack of expertise, or industry-specific technological know-how.
Anyone with an eye on technology will be aware of the rise of cloud-based services. Thankfully for more-established industries, the cloud can now be leveraged to make sense of the reams of data which are flowing to and from the new generations of IIoT-equipped devices.
By pushing IIoT data out into the cloud, onto platforms designed to derive real business value from data, the next generation of industry can be born: there is even a term for this, the oft-quoted Industry 4.0.
The benefits of the cloud and the software (or platform) as a service (SaaS, PaaS) basis of many cloud provisions, mean clouds are built with a high degree of openness with regards their infrastructure. In engineers’ terms, the cloud is a tool with open sockets and ports, into which can be plugged further devices – extending function, making the solution more future-proof, realizing a return on investment.
In software or technology terms, we talk about APIs (application programming interfaces). The presence of APIs means that the data in the cloud can be added to, processed, or enhanced in an almost infinite number of ways.
Here’s an entirely imaginary scenario – although all the features and possibilities are not conjecture, and are in use right now, right across industries of all types.
A tidal power plant creating clean, eco-friendly electricity, produces large quantities of data from each of its moving parts as tides move through turbines, thus generating electricity.
Data flows from all facility’s components into the cloud. As well as the vital information with regards equipment performance, third-party (or built-in) algorithms can be interfaced with (via an API) which allow machine-learning algorithms to predict increasingly accurate trends in performance.
As the physical performance of machines deteriorates, the artificial intelligence routines can draw from immense data pools to determine why efficiencies are decreasing, and even suggest ways in which longer installation lifespans can be encouraged.
Facilities managers can draw on a wealth of external, but contributing data: marine information can be added into the mix, to see how prevailing conditions are affecting tidal flows right across the globe – with important knock-on effects, in the medium to long-term.
Or, anomaly processing routines can be accessed to see outliers on a day-to-day basis are affecting the overall performance of the whole facility, with data fed into this code from every part of the generating facility.
Whatever the industry in which you work, the process of digitizing is like an unstoppable force. It’s paramount that managers, as well as staff at ground level, become conversant with new technologies such as IIoT, capable of understanding the concept of the cloud, and at least knowing what possibilities are open thanks to APIs.
Luckily there are companies out there that have worked in industries of all types for many years and can bring to the table a mix of technical know-how and unique, industry-specific experience and background.
Here at Tech HQ, we feel that every enterprise or organization should be able to find an IIoT partner in one of the following:
Europe’s most significant industrial manufacturing company is also one of its oldest, at 170 years old. It has divisions in healthcare, utilities, building, finance, and automation, along with a significant interest in digital solutions.
The open nature of the company’s MindSphere cloud-based IIoT solution means that it can be deployed across any of its own particular areas of specialization, or indeed, in just about any industry.
The MindSphere cloud is accessed by MindConnect devices, which act as a gateway for an organization’ s devices, technology systems, and data repositories.
MindSphere is made up of different components, each of which can be used to drive value and provide insight & control, across any function. Components include asset management, fleet manager, user management, visualization tools, the MyMachines app (for intelligent tool machines) and an integral predictive learning facility.
There’s also an open API, so, by using well-published worldwide standards, just about any system can benefit from the centralized, cloud-based processing engine.
There are built-in integration portals to well-known applications across many areas of industry, plus there’s Cloud Foundry support which makes the build, testing & deployment of bespoke applications possible; all integrated into MindSphere.
To learn more about Siemens’s raft of IIoT technologies for industries of all types, and healthcare, click here.
GE Digital’s IIoT offering is known as Predix, available in the cloud – public or privately hosted. Connecting to remote assets and securely transferring operational data is often problematic in many industries.
Some solutions aggregate and filter data prior to sending to the cloud. Predix Platform comprises software stacks for edge and cloud, working in concord to provide data ingestion, analysis, intelligence gathering, and control.
There’s a user console for management and monitoring industrial data and assets, analyze anomalies and alerts. Extension of the base offering comes thanks to a rich set of APIs.
GE Digital’s customers can leverage machine learning algorithms, using the technology’s heavy data-lifting capabilities to detect anomalies, predict maintenance requirements and control prescriptively according to resulting outcomes.
Digital twins can also be developed; this allows intelligent emulations of real-world deployments in industry of all types. The advantage of digital twins is that not only are they electronic representations of physical plant or machinery used as emulation, but they can be significantly improved over time by feeding back in real-world data.
GE Digital’s digital twin facility lowers costs to a significant degree, not only in having not to duplicate expensive hardware and production facilities for testing but also by powering future changes to production practice.
Software AG’s cloud-based Internet of things platform is called Cumulocity. As a company, Cumulocity originated in Nokia and was acquired by fellow German company Software AG in March 2017.
The platform was originally developed in a machine to machine context and offers data collection and storage facilities, real-time analytics & visualizations, and a range of open APIs.
As well as being available on a platform as a service model (PaaS) it can also be deployed on customers’ premises.
Via certified hardware kits and software libraries, users can bring their own remote assets into the cloud with customization available through Cumulocity Event Language rules.
Software AG’s portfolio of internet of things software services includes streaming analytics, full IIoT integration, in-memory technologies, dynamic process management, and IoT edge device management.
There are complimentary products for the analysis, evaluation, and visualization of real-time, historical and predictive data. These ensure reliable remote monitoring and control of production machines.
The platform can be used for production diagnostics or in predictive maintenance roles, for example, and optimal use of artificial intelligence can be implemented in decision-making processes.
Cumulocity is used by household name brands such as Deutsche Telekom and Gardner Denver to power solutions in manufacturing fleet management, consumer electronics and many more.
*Some of the companies featured on this editorial are commercial partners of TechHQ
28 September 2020
28 September 2020
28 September 2020