The automation industry appears to be evolving at a faster rate right now than at any time in its history. Commercial technologies continue to infiltrate the industrial automation space, especially wireless and mobility solutions, but what are the technology trends to watch? Change is still driven by return on investment (ROI), for which – in many cases – the time period continues to shrink for project justifications. The Industrial Internet of Things (IIoT), for example, offers tremendous potential to transform and improve business processes, but prospective end users need help to quantify and justify the associated investment, and – in some cases – the associated risk.
One of the biggest end user challenges remains unscheduled downtime. IIoT-enabled solutions, such as remote monitoring and predictive maintenance, can help minimize, if not totally eliminate this, which would deliver a rapid ROI.
Digital transformation, enabled in part by the increasing convergence of operational technology (OT) and information technology (IT), is key for all organizations today, including both end users and OEMs. However, this transformation must embrace legacy assets, as plants will not “rip and replace” old, but otherwise well-functioning, equipment without financial cause. We’re seeing an explosion in the number and variety of analytics applications and suppliers. Historians, MES, and other non-control applications continue to move “to the Cloud,” which enables significant reductions in IT infrastructure and support costs, but also raises the perceived risk of data security, which must be closely scrutinized.
In other trends that we’re following, the control room will continue to be staffed less by onsite operators and increasingly by remotely located operators. In discrete manufacturing plants, robots will further collaborate with workers, as well as other robots. And as all companies are dealing with a loss of talent through retirements and attrition, they must cater to the Millennials, most who very familiar with the latest technologies, but face a steep learning curve when it comes to the manufacturing processes. Cybersecurity solutions will also continue their evolution to be embedded into industrial hardware, software, and communications.
Advanced Analytics, Artificial Intelligence, and Machine Learning Becoming IIoT Enablers
Organizations have long used business intelligence (BI) platforms and enterprise manufacturing intelligence (EMI) tools to discover and understand the underlying reasons and details about what happened and why. Now, with the industrial space becoming much more complex, dynamic, and infused with Big Data, manufacturers are turning to advanced analytics, artificial intelligence, and machine learning to support predictive and prescriptive analytic solutions. By connecting previously stranded data from smart sensors, equipment, and other assets with advanced applications and predictive analytics in the Cloud, IIoT is becoming a strategic enabler to improve manufacturing performance.
More Industrial Devices Are Living on the Edge
One key part of this new growing infrastructure are edge devices or intelligent gateways. These collect, aggregate, filter, and relay data close to industrial processes or production assets. They will also be capable of running analytics, detecting anomalies in real time, and raising alarms so operators or controllers can take appropriate actions. Moving analytics to the edge of the network, and thus closer to the data sources, can help improve manufacturing process quality and production yields. Inexpensive sensors and processors enable more production data to be collected and some data to be processed at the edge. Edge computing with embedded analytics is also an alternative if it’s not viable to run the analytics in the Cloud, or the OEM does not choose a cloud-based solution.
The “edge” of the industrial network is becoming populated by Ethernet, wireless, and cellular gateways; Ethernet switches and routers; and small computers, such as Raspberry Pi’s. These edge devices help bridge IT and OT environments; bringing legacy sensors, devices, controllers and assets into automation or enterprise architectures. Today’s edge devices target device-to-cloud integration to further industrial internet-based strategies designed to improve business performance. These include protocol conversion gateways for interfacing disparate networks to device-to-cloud integration.
Your Assets Have a Digital Twin
Digitalization provides the ability to produce a digital copy of an asset, known as the Digital Twin. This enables companies to perform simulation, testing, and optimization in a virtual environment before committing actual resources. A digital twin is virtual representation of a physical asset. This includes an archive of historical and real-time data, drawings, models, bills of material, engineering and dimensional analysis, manufacturing data, and operational history that can be used as a baseline when benchmarking performance.
Similarly, real-time data acquired via integrated sensors or external sources is used for analytic tasks, including condition monitoring, failure diagnostics, prescriptive and predictive analytics. Knowledge gained adds value to asset life; improving efficiency, reducing downtime, anticipating failures, and for continuous improvement at the design and manufacturing levels. With a digital twin, closed-loop design can now extend through the entire product lifecycle.
Leveraging Augmented and Virtual Reality (AR/VR)
As manufacturers hire new employees, they are implementing simulator-based training to convey plant knowledge; leveraging technologies, such as gaming, augmented/virtual reality, and 3D immersive, with wearable devices, such as the Microsoft HoloLens. This allows real plant and job functions, controls, and assets to be replicated, providing a high-fidelity experience. Simulation improves learning and is effective in developing skills to deal with unanticipated plant situations, thus increasing workers’ confidence in performing their job functions and ability to deal with an emergency. Other simulation applications include testing and validating new software, supporting system migrations, and program testing and validation.
More Disruptive Technology Trends
Increasingly, we’re seeing basic manufacturing functions -- such as material and energy procurement, product quality, and production management -- provided by third parties “…as a Service.”
“Bring Your Own Device” (BYOD) enables operators, supervisors, and managers to use their personal mobile devices to monitor plant and factory performance.
Message Queueing Telemetry Transport (MQTT), a machine-to-machine (M2M) data transfer protocol, will grow in its use as a messaging protocol for IIoT. MQTT is designed as a lightweight publish/subscribe messaging transport, used for connections with remote locations where a small code footprint is required and/or network bandwidth is at a premium. For example, it has been used for mobile applications because of its small size, low power usage, minimised data packets, and efficient distribution of information to one or many receivers.
3D printing/additive manufacturing enables components to be fabricated layer-by-layer in three dimensions based on digital engineering data. It works well with plastics, metals, and ceramic materials, and provides a practical solution for creating components on-demand, versus having them manufactured elsewhere, shipped, and kept on inventory.
Social networks and platforms will continue to grow on the factory floor, enabling virtual user groups within and between plants, as well as with the technology suppliers and end users.
End users and OEMs alike should embrace, rather than resist, positive disruptive change. This change will result in, for example, consumer devices and non-industrial products being broadly adopted in automation applications. IIoT’s initial focus should be on asset management and avoiding downtime. Automation suppliers must help their customers calculate the ROI justification needed to invest in these new IIoT solutions. Legacy assets must remain a part of, and be integrated into these latest IIoT technology solutions, wherever possible.
Most industrial assets will have a digital twin that can help reduce costs of deployment and improve performance over the asset’s lifecycle – from initial design, through manufacturing, installation and commissions, operation and maintenance, and – ultimately – final decommissioning.
Robotics will continue their ability to perform repetitive, strenuous, and/or hazardous tasks; but are evolving to working more collaboratively in close proximity to humans as needed, thanks to advances in safety technology.
Improved cybersecurity technologies and approaches, such as Achilles Certification. will help to somewhat lessen those concerns so that cybersecurity will no longer remain the single greatest headwind to IIoT-enabled solutions in industrial and critical infrastructure environments. Achilles Communications Certification offers two levels of certifying the network robustness of industrial devices. It provides manufacturers of devices and systems in critical infrastructure markets an independent verification that the certified device meets communications robustness benchmarks that are industry-recognized and mandated by major critical infrastructure operators. However, all it would take is another major damaging cyber-attack on industry to bring back those concerns.
ARC anticipates that analytic applications will multiply, and many analytics companies will be acquired by the large automation suppliers.
Barriers to cloud adoption will continue to fall, with control applications eventually running in the Cloud in the distant future. The future process automation system and the applications that run on it will be more open, standards-based, and interoperable; closely following the Collaborative Process Automation System (CPAS) model that ARC created way back in 2002.
Knowledge capture remains challenging for industrial organizations as they struggle to retain the knowledge and expertise of retiring workers, while leveraging the unique talents that Millennials bring to the workforce. ARC believes that augmented/virtual reality will go a long way to helping organizations both capture existing knowledge, while empowering the new workforce to innovate and improve business, environmental, and safety performance across industries.
All in all, these trends and changes make this a very exciting time to be in the automation space, and the future is likely to be even brighter.
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Keywords: Analytics, Artificial Intelligence, Machine Learning, IIoT, Edge, Digital Twin, Augmented Reality, Virtual Reality, Disruptive Technologies, SaaS, Virtualization, Big Data, Convergence, BYOD, Robotics, Cybersecurity, ARC Advisory Group.