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Top Technology Trends in Automation for 2018
2018年自動(dòng)化領(lǐng)域前沿技術(shù)趨勢

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.

在過去的幾年里，新自動(dòng)化技術(shù)取得了顯著的進(jìn)步。這一變化及隨后的采納率將在新的一年繼續(xù)上升。最近的進(jìn)展包括一些流行消費(fèi)技術(shù)的工業(yè)化應(yīng)用。這有助于加速信息技術(shù)(IT)和運(yùn)營技術(shù)(OT)的不斷融合，以支持?jǐn)?shù)字進(jìn)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(jù)《2018年前沿自動(dòng)化技術(shù)發(fā)展趨勢》，IT/OT融合將加速，尤其是因?yàn)檫@涉及到工業(yè)物聯(lián)網(wǎng)（IIoT）解決方案、網(wǎng)絡(luò)安全、邊緣計(jì)算、增強(qiáng)現(xiàn)實(shí)（ AR）、人工智能（AI）、分析、數(shù)字雙胞胎以及開放式過程自動(dòng)化（OPA）方面的進(jìn)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:

這里有五個(gè)關(guān)鍵技術(shù)趨勢，它們將在2018年對過程和離散自動(dòng)化產(chǎn)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(shù)據(jù)密集型計(jì)算工作負(fù)載被推到網(wǎng)絡(luò)邊緣，實(shí)時(shí)遠(yuǎn)程管理和簡化的邊緣基礎(chǔ)設(shè)施對于成功至關(guān)重要。 操作問題（如管理資產(chǎn)績效以提高產(chǎn)量，同時(shí)減少意外停機(jī)）將推動(dòng)最終用戶部署邊緣計(jì)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(jì)算基礎(chǔ)設(shè)施的公司將能夠解鎖先前滯留在機(jī)器和流程中的其他數(shù)據(jù)。 他們也將能夠更快速地識(shí)別生產(chǎn)效率低下的問題; 將產(chǎn)品質(zhì)量與生產(chǎn)條件進(jìn)行比較; 更準(zhǔn)確地指出潛在的安全、生產(chǎn)或環(huán)境問題。遠(yuǎn)程管理將使現(xiàn)場操作人員能夠?qū)崟r(shí)地與場外專家聯(lián)系，以更快地解決甚至避免停機(jī)事件。這將有助于解放操作人員和IT人員，讓他們發(fā)揮各自角色，從而最大限度地利用其專長。

Advances in Industrial Cybersecurity Management
工業(yè)網(wǎng)絡(luò)安全管理的進(jìn)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(yè)網(wǎng)絡(luò)安全管理解決方案將取得更多進(jìn)展，以解決工業(yè)自動(dòng)化設(shè)備、應(yīng)用和工廠的獨(dú)特需求; 特別是這些與系統(tǒng)更新和網(wǎng)絡(luò)通信的嚴(yán)格限制有關(guān)。這些進(jìn)展將結(jié)合商業(yè)類型IT網(wǎng)絡(luò)安全管理解決方案，但在某種程度上限制了對控制系統(tǒng)操作的任何負(fù)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(yè)網(wǎng)絡(luò)安全管理解決方案將擴(kuò)展這一功能，包括獨(dú)特的、非基于PC的工業(yè)資產(chǎn)和控制系統(tǒng)協(xié)議。這些解決方案還將識(shí)別和管理特定于行業(yè)的網(wǎng)絡(luò)安全規(guī)則，例如NERC CIP，并利用新的集成策略，將IT、OT和IIoT的安全成果結(jié)合起來，最大限度地利用所有公司的網(wǎng)絡(luò)安全資源。

Open Process Automation Vision Gains Traction
開放過程自動(dòng)化前景看好

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(dòng)化論壇吸引新的終端用戶和供應(yīng)商成員，開放過程自動(dòng)化(OPA)前景將獲得更多的歡迎。

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(fā)起并由開放集團(tuán)管理，該倡議旨在建立一個(gè)概念驗(yàn)證原型，建立標(biāo)準(zhǔn)并最終建立商業(yè)開放式過程自動(dòng)化系統(tǒng)，從而最大限度地減少供應(yīng)商特定技術(shù)并提高系統(tǒng)投資的總體回報(bào)，同時(shí)保持嚴(yán)格的安全性。這將通過指定高度分布式的、模塊化的、可擴(kuò)展的系統(tǒng)來實(shí)現(xiàn)，這些系統(tǒng)基于標(biāo)準(zhǔn)的可互操作組件架構(gòu)，并具有內(nèi)在的網(wǎng)絡(luò)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(biāo)是最終用更小的OpEx程序取代大型CapEx自動(dòng)化改造項(xiàng)目，這些項(xiàng)目僅需較少的分析、工程和規(guī)劃。 這些新開放系統(tǒng)的更新將作為維護(hù)活動(dòng)進(jìn)行管理。 這些新系統(tǒng)將由更小、更模塊化和更容易分布的組件組成。這些系統(tǒng)將更好地授權(quán)技術(shù)人員，減少所需的培訓(xùn)水平，并通過合作促進(jìn)更多的利益。

Merging of Virtual and Physical Worlds
虛擬和物理世界融合

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(shù)正在加速虛擬和物理世界的融合，從而創(chuàng)造新的商業(yè)模式。制造商正在引入新的商業(yè)模式，在這些模式下，他們銷售數(shù)字服務(wù)和產(chǎn)品。例如，數(shù)字雙胞胎，這是一個(gè)設(shè)計(jì)、建造和維護(hù)的物理產(chǎn)品的虛擬復(fù)制。制造商通過實(shí)時(shí)狀態(tài)監(jiān)測和預(yù)測分析來增強(qiáng)數(shù)字雙胞胎服務(wù)。 客戶使用設(shè)備和產(chǎn)品以及基于預(yù)測性和規(guī)范性分析的維護(hù)和運(yùn)營優(yōu)化服務(wù)。

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(qiáng)現(xiàn)實(shí)（AR）技術(shù)用于將虛擬設(shè)計(jì)與物理設(shè)備連接起來，以實(shí)現(xiàn)操作員培訓(xùn)和可視化以及機(jī)器維護(hù)。 由于IIoT、云計(jì)算、大數(shù)據(jù)和運(yùn)營分析，基于人工智能（AI）的機(jī)器學(xué)習(xí)（ML）解決方案可以用于在不需要編程的情況下進(jìn)行操作更改。

Distributed Analytics
分布式分析

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(yè)物聯(lián)網(wǎng)支持的分布式分析將進(jìn)一步擴(kuò)展數(shù)據(jù)處理和計(jì)算，使其接近數(shù)據(jù)源或通過數(shù)據(jù)源進(jìn)行計(jì)算，通常通過智能雙向通信設(shè)備（如傳感器，控制器和網(wǎng)關(guān)）進(jìn)行擴(kuò)展。在許多情況下，分布式分析的數(shù)據(jù)來自位于運(yùn)營網(wǎng)絡(luò)邊緣的IIoT連接設(shè)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(shè)備可以就近或嵌入在各種邊緣機(jī)器和設(shè)備中，如機(jī)器人、車隊(duì)車輛和分布式微電網(wǎng)。 分析可以嵌入到分布式設(shè)備中，或者在云環(huán)境中創(chuàng)建，然后發(fā)送到邊緣執(zhí)行。從操作的角度來看，安全性、隱私性，與數(shù)據(jù)相關(guān)的成本以及監(jiān)管限制常常是導(dǎo)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.

分布式分析可以幫助支持現(xiàn)有客戶服務(wù)的新方式創(chuàng)造收入，并幫助他們開拓新客戶的收入。這包括通過改進(jìn)、主動(dòng)和高度自動(dòng)化的基礎(chǔ)設(shè)施和資源管理來優(yōu)化資產(chǎn)；在客戶需要的時(shí)間和地點(diǎn)，以高價(jià)值的產(chǎn)品和服務(wù)吸引客戶，提高客戶滿意度；以及通過更好、更快速的數(shù)據(jù)驅(qū)動(dòng)決策改善運(yùn)營靈活性和響應(yīng)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(shù)字化轉(zhuǎn)型將是工業(yè)組織有效競爭和業(yè)務(wù)績效最大化的先決條件。在尋找開始數(shù)字化轉(zhuǎn)型過程的地方時(shí)，資產(chǎn)績效管理（包括避免計(jì)劃外停機(jī)時(shí)間）是一個(gè)值得關(guān)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(yīng)該擁抱，而不是抵制數(shù)字化進(jìn)程。雖然運(yùn)營技術(shù)（OT）和信息技術(shù)（IT）日益趨于一致，但這種數(shù)字化轉(zhuǎn)型仍然必須包含遺留資產(chǎn)，因?yàn)楣S不會(huì)在沒有經(jīng)濟(jì)原因的情況下“破壞和取代”舊的但運(yùn)行良好的設(shè)備。傳統(tǒng)資產(chǎn)必須保留一部分，并盡可能地集成到數(shù)字轉(zhuǎn)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(shù)、方法和商業(yè)模式敞開胸懷，而OT和IT部門在各自的運(yùn)營和企業(yè)層面，以及技術(shù)供應(yīng)商和工業(yè)和政府財(cái)團(tuán)之間，需要密切合作。雖然不是所有的技術(shù)、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(fā)生的事情、今天的可用情況、明天可能會(huì)出現(xiàn)的情況，以及同行組織正在做什么，以確定在哪里最佳地集中有限的人力和財(cái)力資源。