Top Technology Trends in Automation for 2018

By Craig Resnick

Category:
ARC Report Abstract

Following several decades of largely incremental advances in automation technology, we’ve seen significant activity in this area within the last couple years and this will continue into the coming year.  Many of the recent advances have been end user-driven; most stem from the ongoing convergence of information technology (IT) and operational technology (OT) to support digital transformation.

ARC believes that, in 2018, we’ll see an acceleration in IT/OT convergence, particularly as this relates to the acceptance of and proliferation of Industrial Internet of Things (IIoT)-enabled solutions, cybersecurity, and continued movement on the Open Process Automation (OPA) front.

In no particular order, this ARC Insight briefly summarizes five key technology trends that we believe will have a major impact on both process and discrete automation in 2018.  We also include some thoughts on how end users can best take advantage of these trends to succeed in the years to come. 

ARC invites your feedback and will share additional insights in future ARC client reports as these and other trends play out over the course of the year.  In addition, several keynote and other presentations the upcoming 2018 ARC Industry Forum in Orlando, Florida will address many of these trends.  Please join us in Orlando (or at other ARC Forums around the world) if you’d like to learn more and share your own thoughts.

Intelligence at the Edge

As more data-intensive compute workloads are pushed to the network edge, real-time remote management and a simplified edge infrastructure are crucial for success. Operational issues, such as managing asset performance to improve production while reducing unplanned downtime will drive end users to deploy edge computing.

Companies that take advantage of self-managed, edge computing infrastructures will be able to unlock the data that has long been stranded inside machines and processes. They also will be able to quickly identify production inefficiencies; compare product quality against manufacturing conditions; and pinpoint potential safety, production, or environmental issues. Remote management will enable on-site operators to connect immediately with off-site experts to more quickly resolve, or even avoid, downtime events. This will free operations people and IT staff to perform their respective roles, making best advantage of their specific expertise.

Advances in Industrial Cybersecurity Management

Additional advances in industrial cybersecurity management solutions will be deployed to address the unique requirements of industrial automation equipment, applications, and plants; particularly as these relate to the stringent constraints on system updates and network communications. They will incorporate commercial-type IT cybersecurity management solutions, but in a manner that limits any negative impacts on control system operation.

More importantly, these new industrial cybersecurity management solutions will extend this functionality to include unique, non-PC-based industrial assets and control system protocols. These solutions will also recognize and manage industry-specific cybersecurity regulations, such as NERC CIP, and leverage new integrated strategies that combine IT, OT, and IIoT security efforts, maximizing the use of all corporate cybersecurity resources.

Open Process Automation Vision Gains Traction

The open process automation (OPA) vision will gain additional traction, with the Open Process Automation Forum adding new end user and supplier members.ExxonMobil's Open Process Automation Architecture Vision

Initiated by ExxonMobil and managed by The Open Group, this initiative aims to build a proof-of-concept prototype, establish standards for, and ultimately build commercial open process automation systems

that minimize vendor-specific technologies and increase overall return on system investment, while maintaining stringent safety and security.  This would be achieved by specifying highly distributed, modular, extensible systems based on standards-based architecture for interoperable components, with intrinsic cybersecurity.

The objective is to eventually replace large CapEx automation retrofit programs with smaller OpEx programs that require less analysis, engineering, and planning. Updates to these new open systems will be managed as a maintenance activity. These new systems will consist of smaller, more modular and more easily distributed components. These systems will better empower technical personnel, reducing the level of training required and facilitating additional benefits through collaboration.

ARC clients can refer to the December 2017 ARC Strategy Report, An Open Process Automation Compendium, for more information on this initiative. 

Merging of Virtual and Physical Worlds

New technologies are accelerating the merging of the virtual and physical worlds, enabling the creation of new business models.  Manufacturers are introducing new business models under which they sell digital services along with product. Examples include digital twins, which are a virtual replication of an as-designed, as-built, and as-maintained physical product.  Manufacturers augment the digital twin service with real-time condition monitoring and predictive analytics. Customers use the equipment and products along with maintenance and operational optimization services based on predictive and prescriptive analytics.

Augmented reality (AR) technologies are used to connect virtual design to physical equipment for operator training and visualization, as well as for machine maintenance. Thanks to IIoT, cloud, Big Data, and operational analytics; artificial intelligence (AI)-based machine learning (ML) solutions can tach to make operational changes without the need for programming.

Distributed Analytics

Industrial IoT-enabled distributed analytics will further extend data processing and computing close to or at the data source, typically through intelligent, two-way communication devices, such as sensors, controllers, and gateways. In many instances, the data for distributed analytics comes from IIoT-connected devices located at the edge of the operational network.

These devices can be located near or embedded in a wide variety of edge machines and equipment, such as robots, fleet vehicles, and distributed microgrids. The analytics can be embedded within distributed devices or created in a cloud environment and then sent to the edge for execution. From an operational perspective; security, privacy, data-related cost, and regulatory constraints are often the reasons cited for keeping the analytics local.

Distributed analytics can help support revenue generation from new methods of serving existing customers and ways to reaching new ones.  These include asset optimization through improved, proactive, and highly-automated management of infrastructure and resources; higher satisfaction and retention by engaging customers with high-value products and services where and when they need them; and improved operational flexibility and responsiveness through better and faster data-driven decisions.

 

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