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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.

在過去的幾年裡，新自動化技術取得了顯著的進步。這一變化及隨後的採納率將在新的一年繼續上升。最近的進展包括一些流行消費技術的工業化應用。這有助於加速信息技術(IT)和運營技術(OT)的不斷融合，以支持數字進程。

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.

根據《2018年前沿自動化技術發展趨勢》，IT/OT融合將加速，尤其是因為這涉及到工業物聯網（IIoT）解決方案、網絡安全、邊緣計算、增強現實（ AR）、人工智能（AI）、分析、數字雙胞胎以及開放式過程自動化（OPA）方面的進展。

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

這裡有五個關鍵技術趨勢，它們將在2018年對過程和離散自動化產生重大影響：

Intelligence at the Edge

邊緣智能

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.

隨著越來越多的數據密集型計算工作負載被推到網絡邊緣，實時遠程管理和簡化的邊緣基礎設施對於成功至關重要。 操作問題（如管理資產績效以提高產量，同時減少意外停機）將推動最終用戶部署邊緣計算。

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邊緣計算基礎設施的公司將能夠解鎖先前滯留在機器和流程中的其他數據。 他們也將能夠更快速地識別生產效率低下的問題; 將產品質量與生產條件進行比較; 更準確地指出潛在的安全、生產或環境問題。遠程管理將使現場操作人員能夠實時地與場外專家聯繫，以更快地解決甚至避免停機事件。這將有助於解放操作人員和IT人員，讓他們發揮各自角色，從而最大限度地利用其專長。

Advances in Industrial Cybersecurity Management

工業網絡安全管理的進展

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.

工業網絡安全管理解決方案將取得更多進展，以解決工業自動化設備、應用和工廠的獨特需求; 特別是這些與系統更新和網絡通信的嚴格限制有關。這些進展將結合商業類型IT網絡安全管理解決方案，但在某種程度上限制了對控制系統操作的任何負面影響。

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，這些新的工業網絡安全管理解決方案將擴展這一功能，包括獨特的、非基於PC的工業資產和控制系統協議。這些解決方案還將識別和管理特定於行業的網絡安全規則，例如NERC CIP，並利用新的集成策略，將IT、OT和IIoT的安全成果結合起來，最大限度地利用所有公司的網絡安全資源。

Open Process Automation Vision Gains Traction

開放過程自動化視覺越來越受歡迎

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

隨著開放過程自動化論壇吸引新的終端用戶和供應商成員，開放過程自動化(OPA)視覺將獲得更多的歡迎。

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.

由埃克森美孚公司發起並由開放集團管理，該倡議旨在建立一個概念驗證原型，建立標準並最終建立商業開放式過程自動化系統，從而最大限度地減少供應商特定技術並提高系統投資的總體回報，同時保持嚴格的安全性。這將通過指定高度分佈式的、模塊化的、可擴展的系統來實現，這些系統基於標準的可互操作組件架構，並具有內在的網絡安全性。

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.

其目標是最終用更小的OpEx程序取代大型CapEx自動化改造項目，這些項目僅需較少的分析、工程和規劃。 這些新開放系統的更新將作為維護活動進行管理。 這些新系統將由更小、更模塊化和更容易分佈的組件組成。這些系統將更好地授權技術人員，減少所需的培訓水平，並通過合作促進更多的利益。

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.

新技術正在加速虛擬和物理世界的融合，從而創造新的商業模式。製造商正在引入新的商業模式，在這些模式下，他們銷售數字服務和產品。例如，數字雙胞胎，這是一個設計、建造和維護的物理產品的虛擬複製。製造商通過實時狀態監測和預測分析來增強數字雙胞胎服務。 客戶使用設備和產品以及基於預測性和規範性分析的維護和運營優化服務。

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.

增強現實（AR）技術用於將虛擬設計與物理設備連接起來，以實現操作員培訓和可視化以及機器維護。 由於IIoT、雲計算、大數據和運營分析，基於人工智能（AI）的機器學習（ML）解決方案可以用於在不需要編程的情況下進行操作更改。

Distributed Analytics

分佈式分析

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.

工業物聯網支持的分佈式分析將進一步擴展數據處理和計算，使其接近數據源或通過數據源進行計算，通常通過智能雙向通信設備（如傳感器，控制器和網關）進行擴展。在許多情況下，分佈式分析的數據來自位於運營網絡邊緣的IIoT連接設備。

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.

這些設備可以就近或嵌入在各種邊緣機器和設備中，如機器人、車隊車輛和分佈式微電網。 分析可以嵌入到分佈式設備中，或者在雲環境中創建，然後發送到邊緣執行。從操作的角度來看，安全性、隱私性，與數據相關的成本以及監管限制常常是導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.

分佈式分析可以幫助支持現有客戶服務的新方式創造收入，並幫助他們開拓新客戶的收入。這包括通過改進、主動和高度自動化的基礎設施和資源管理來優化資產；在客戶需要的時間和地點，以高價值的產品和服務吸引客戶，提高客戶滿意度；以及通過更好、更快速的數據驅動決策改善運營靈活性和響應能力。

Recommendations

建 議

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.

成功的數字化轉型將是工業組織有效競爭和業務績效最大化的先決條件。在尋找開始數字化轉型過程的地方時，資產績效管理（包括避免計劃外停機時間）是一個值得關注的好地方。

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.

最終用戶和OEM應該擁抱，而不是抵制數字化進程。雖然運營技術（OT）和信息技術（IT）日益趨於一致，但這種數字化轉型仍然必須包含遺留資產，因為工廠不會在沒有經濟原因的情況下“破壞和取代”舊的但運行良好的設備。傳統資產必須保留一部分，並儘可能地集成到數字轉換的解決方案中。

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.

要想取得成功，需要對新興技術、方法和商業模式敞開胸懷，而OT和IT部門在各自的運營和企業層面，以及技術供應商和工業和政府財團之間，需要密切合作。雖然不是所有的技術、解決方案和方法都適合所有的公司，但重要的是要了解正在發生的事情、今天的可用情況、明天可能會出現的情況，以及同行組織正在做什麼，以確定在哪裡最佳地集中有限的人力和財力資源。

英文資料來源：ARC顧問 由中華工控網翻譯整理，任何媒體和個人全部或部分轉載必須註明出處。