Report | 2018 Outlook on Cutting edge Technologies in the Field of Automation

Over the last several years, there has been significant advances in and adoption of new automation technologies. This rate of change and subsequent adoption will continue to ramp up in the coming year. Many of the recent advances include industrializing some popular consumer technology. This helps accelerate the ongoing convergence of information technology (IT) and operational technology (OT) to support digital transformation.

New automation technologies have made significant progress over the past few years. This change and subsequent adoption rates will continue to rise in the new year. Recent advances include the industrial application of some popular consumer technologies. This helps accelerate the convergence of information technology (IT) and operational technology (OT) to support the digital process. 

Top Technology Trends in Automation In 2018, there will be an acceleration of this IT/OT convergence, particularly as this relateds to the acceptance of and proliferation of Industrial Internet of Things (IIoT)-enabled solutions, cybersecurity, edge computing, augmented reality (AR), artistic intelligence (AI), analytics, digital twins, and progress on the Open Process Automation (OPA) front.

According to the Trends in Frontier Automation Technology in 2018, IT/OT convergence will accelerate, especially as this involves advances in industrial Internet of Things (IIoT) solutions, cybersecurity, edge computing, augmented reality (AR), artificial intelligence (AI), analytics, digital twins, and open process automation (OPA) .

In no particular order, here are five key technology trends that will have a major impact on both process and discrete automation in 2018:

Here are five key technology trends that will have a significant impact on process and discrete automation in 2018:

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

As more and more data-intensive compute workloads are pushed to the edge of the network, real-time remote management and simplified edge infrastructure are critical to success. Operational issues such as managing asset performance to improve output while reducing unexpected downtimes will drive end users to deploy edge computing.

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

Companies that leverage self-managed edge computing infrastructure will be able to unlock other data previously stuck in machines and processes. They will also be able to identify inefficiency issues more quickly; compare product quality with production conditions; and point out potential safety, production or environmental issues more accurately. Remote management will enable field operators to contact off-site experts in real time to resolve and even avoid downtime events faster. This will help liberate operators and IT personnel to play their respective roles, thereby maximizing the use of their expertise.

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 related to the stringent constraints on system updates and network communications. These advances will incorporate commercial-type IT cybersecurity management solutions, but in a manner that limits any negative impacts on control system operation.

Industrial cybersecurity management solutions will make more progress to address the unique needs of industrial automation equipment, applications and factories; in particular these are related to the strict restrictions on system updates and network communications. These advances will combine business-type IT cybersecurity management solutions, but to some extent limit any negative impact on control system operations.

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.

More importantly, these new industrial cybersecurity management solutions will extend this capability to include unique, non-PC-based industrial assets and control system protocols. These solutions will also identify and manage industry-specific cybersecurity rules such as NERC CIP and leverage new integration strategies to combine IT, OT, and IIoT security outcomes to maximize the use of cybersecurity resources of all companies. 

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

Open Process Automation (OPA) vision will gain more popularity as the Open Process Automation Forum attracts new end users and supplier members.

Initiated by ExxonMobil and managed by The Open Group, this initiative aims to build a proof-of-concept prototype, established 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, extended systems based on standards-based architecture for interoperable components, with intrinsic cybersecurity.

Initiated by ExxonMobil and managed by Open Group, the initiative aims to create a proof-of-concept prototype, establish standards and ultimately establish a commercial open process automation system that minimizes supplier-specific technologies and improves the overall returns on system investments while maintaining strict security. This will be achieved by specifying highly distributed, modular, scalable systems based on a standard interoperable component architecture with inherent network security.

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.

The goal is to eventually replace large CapEx automation transformation projects with smaller OpEx programs that require less analysis, engineering and planning. Updates to these new open systems will be managed as maintenance activities. These new systems will consist of smaller, more modular and easier to distribute components. These systems will better empower technicians, reduce the level of training required, and promote greater benefits through collaboration.

New technologies are accelerating the merger 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 products. 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.

New technologies are accelerating the integration of the virtual and physical worlds, thus creating new business models. Manufacturers are introducing new business models where they sell digital services and products. For example, Digital Twins, which is a virtual reproduction of physical products designed, built and maintained. Manufacturers enhance digital twin services with real-time status monitoring and predictive analytics. Customers use equipment and products as well as maintenance and operational optimization services based on predictive and standardized 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 be used to make operational changes without the need for programming.

Augmented reality (AR) technology is used to connect virtual design with physical devices for operator training and visualization and machine maintenance. Due to IIoT, cloud computing, big data, and operational analytics, machine learning (ML) solutions based on artificial intelligence (AI) can be used to make operational changes without programming.

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.

Distributed analytics supported by the Industrial IoT will further extend data processing and computing to get it close to or through data sources, usually through intelligent bidirectional communication devices such as sensors, controllers and gateways. In many cases, the distributed analysis data comes from IIoT connected devices located at the edge of the operating 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.

These devices can be near or embedded in various edge machines and devices such as robots, fleet vehicles and distributed microgrids. Analytics can be embedded in distributed devices, or created in a cloud environment and sent to the edge for execution. From an operational perspective, security, privacy, data-related costs, and regulatory limitations are often what causes localization of analytics.

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.

Distributed analytics can help create revenue by supporting new ways of serving existing customers and help them develop revenue for new customers. This includes optimizing assets through improved, proactive and highly automated infrastructure and resource management; engaging customers with high-value products and services at the time and place they need, and improving operational flexibility and responsiveness through better and faster data-driven decisions.

Successful digital transformation will be a prerequisite for industrial organizations to compete effectively and maximize business performance. When looking for a place to start the digital transformation process, asset performance management (including avoiding unscheduled downtime) is a great place on which to focus.

Successful digital transformation will be a prerequisite for effective competition and business performance in industrial organizations. Asset performance management, including avoiding unplanned downtime, is a great place to watch when looking for a place to start the digital transformation process.

End users and OEMs alike should embrace, rather than resist, digital transformation. While the increasing convergence of operational technology (OT) and information technology (IT) serves an enabler, this digital transformation must still embrace legacy assets, as plants will not “rip and replace” old, but otherwise well-functioning, equipment without financial cause. Legacy assets must remain a part of, and be integrated into the solutions for digital transformation wherever possible.

*** End users and OEMs should embrace, not resist the digital process. While operational technology (OT) and information technology (IT) are becoming increasingly aligned, this digital transformation must still contain legacy assets, as factories do not “destroy and replace” old but well-running equipment without economic reasons. Traditional assets must retain a portion and be integrated as much as possible into digital conversion solutions.

Succeeding here will require both an open mind for emerging technologies, approaches, and business models; and close collaboration between OT and IT groups at the respective operations and enterprise levels, as well as with technology suppliers and industrial and governmental consortiums. While not all technologies, solutions, and approaches will be right for all companies, it's important to understand what's going on, what's available today, what's likely to be available tomorrow, and what peer organizations are doing to be able to determine where to best focus your limited human and financial resources.

To be successful, it requires openness to emerging technologies, approaches and business models, and OT and IT departments need to work closely together at their respective operational and enterprise levels, as well as between technology suppliers and industrial and government consortiums. While not all technologies, solutions and approaches are suitable for all companies, it is important to understand what is happening, what is available today, what may be coming tomorrow, and what peer organizations are doing to determine where to focus their limited human and financial resources.

Source: Reprinted from Industrial Control Headlines