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Top Technology Trends in Automation for 2018

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.


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

根据《2018年前沿自动化技术发展趋势》,IT/OT融合将加速,尤其是因为这涉及到工业物联网(IIoT)解决方案、网络安全、边缘计算、增强现实( AR)、人工智能(AI)、分析、数字双胞胎以及开放式过程自动化(OPA)方面的进展。

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


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.

随着越来越多的数据密集型计算工作负载被推到网络边缘,实时远程管理和简化的边缘基础设施对于成功至关重要。 操作问题(如管理资产绩效以提高产量,同时减少意外停机)将推动最终用户部署边缘计算。

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 inefficiencies; 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.

那些利用自我管理的边缘计算基础设施的公司将能够解锁先前滞留在机器和流程中的其他数据。 他们也将能够更快速地识别生产效率低下的问题; 将产品质量与生产条件进行比较; 更准确地指出潜在的安全、生产或环境问题。远程管理将使现场操作人员能够实时地与场外专家联系,以更快地解决甚至避免停机事件。这将有助于解放操作人员和IT人员,让他们发挥各自角色,从而最大限度地利用其专长。

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. These advances will incorporate commercial-type IT cybersecurity management solutions, but in a manner that limits any negative impacts on control system operation.

工业网络安全管理解决方案将取得更多进展,以解决工业自动化设备、应用和工厂的独特需求; 特别是这些与系统更新和网络通信的严格限制有关。这些进展将结合商业类型IT网络安全管理解决方案,但在某种程度上限制了对控制系统操作的任何负面影响。

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.

更重要的是,这些新的工业网络安全管理解决方案将扩展这一功能,包括独特的、非基于PC的工业资产和控制系统协议。这些解决方案还将识别和管理特定于行业的网络安全规则,例如NERC CIP,并利用新的集成策略,将IT、OT和IIoT的安全成果结合起来,最大限度地利用所有公司的网络安全资源。 

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.


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.

其目标是最终用更小的OpEx程序取代大型CapEx自动化改造项目,这些项目仅需较少的分析、工程和规划。 这些新开放系统的更新将作为维护活动进行管理。 这些新系统将由更小、更模块化和更容易分布的组件组成。这些系统将更好地授权技术人员,减少所需的培训水平,并通过合作促进更多的利益。

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 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.

新技术正在加速虚拟和物理世界的融合,从而创造新的商业模式。制造商正在引入新的商业模式,在这些模式下,他们销售数字服务和产品。例如,数字双胞胎,这是一个设计、建造和维护的物理产品的虚拟复制。制造商通过实时状态监测和预测分析来增强数字双胞胎服务。 客户使用设备和产品以及基于预测性和规范性分析的维护和运营优化服务。

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.

增强现实(AR)技术用于将虚拟设计与物理设备连接起来,以实现操作员培训和可视化以及机器维护。 由于IIoT、云计算、大数据和运营分析,基于人工智能(AI)的机器学习(ML)解决方案可以用于在不需要编程的情况下进行操作更改。

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.

这些设备可以就近或嵌入在各种边缘机器和设备中,如机器人、车队车辆和分布式微电网。 分析可以嵌入到分布式设备中,或者在云环境中创建,然后发送到边缘执行。从操作的角度来看,安全性、隐私性,与数据相关的成本以及监管限制常常是导致分析本地化的原因。

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.



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.


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.


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.




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