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Will Your OT Data Sink or Swim in the IT Ocean?
你的OT數據是否會在IT海洋中沉浮？

Why is Operational Technology data (OT data) continuing to make major inroads into the Informational Technology (IT) world? What factors are causing OT data to leave its comfort zone and stepping into a new frontier? And why is this step imperative for the next generation of industrial automation?

為什么運營數據（OT數據）會進入IT世界？是什么讓OT數據離開舒適區、進入新領域？為什么這一步對于下一代工業自動化至關重要？

According to Moxa, the reasons OT data is leaving its safe nest are closely tied to today's operational needs. It has to do with how we’re using OT data. To better understand, let’s consider the evolution of OT data, starting with Industry 2.0. This era saw the introduction of electricity and assembly-line production, which prompted the invention of controllers to better manage devices on the factory floor as mass production gained traction. By using a simple on-and-off switch, these controllers helped complete simple routine tasks. Back then, data was few in quantity and stayed within the confines of the devices that generated them. In its infancy, OT data of the Industry 2.0 era was limited to activities within its own devices.

在Moxa看來，之所以要OT數據離開舒適區，與今天的運營需求密切相關，也與我們如何使用OT數據有關。讓我們從工業2.0時代開始，看一看OT數據的演變。工業2.0時代，人們引入了電力和流水線生產，推動了控制器的發明，可以更好地控制工廠車間的設備，大規模生產也隨之發展起來。控制器通過簡單的開關操作，幫助人們完成簡單的常規任務。那時，數據量很小，并停留在產生數據的設備范圍內。在其初期，工業2.0時代的OT數據的活動范圍也僅限于其自身設備之內。
 
The third Industrial Revolution introduced system automation as the new standard. Advancements in computing and communication technologies enabled automated processes to connect and "talk to each other." This was achieved by adding sensors to the original controllers, a step that created a closed loop involving sensors gathering data and sending it back to the controller for some preliminary calculations. Based on these calculations, feedbacks helped complete the command. This signified the first step taken by OT data from existing solely within devices to it circulating between a few devices in a closed loop.

第三次工業革命引入了系統自動化的新標準。計算和通信技術的進步促使自動化生產過程具備了聯通能力。人們通過為原始控制器增加傳感器、創建閉環來實現這種連接和通信。該閉環包含傳感器收集數據，再將數據發送回控制器，以進行初步計算。基于這些計算，控制器會生成相應反饋，幫助完成命令。這標志著OT數據從僅存在于設備內部到在幾個設備之間閉環循環所邁出的第一步。

Along with further technological advancements, the evolution of OT data was inevitable. With the advent of Industry 4.0, or Industrial Digital Transformation, managers are no longer satisfied with only preprogrammed automation. They now demand a smart, self-thinking system, pushing mandates for OT data to the next level. So, the big question now is how to maximize OT data’s true value.

隨著技術的進步，OT數據的演變也隨之而來。進入工業4.0（工業數位轉型）時代，人們不再僅僅滿足于預編程的自動化，而需要一種能夠自我思考的智能系統。這使對OT數據的要求提升到了全新水平。現在最大的問題是如何最大化 OT 數據的真正價值。

To achieve this feat, OT data has had to extend beyond its original dwellings and step into data centers or the cloud for further analysis, a move that can improve production efficiency, enhance quality, reduce costs, and even provide new business services. This kick-started a phenomenon that turned protected and localized OT data into usable data when transmitting it to remote IT systems and feeding it back to the OT side for real-time optimization. This phenomenon is what Moxa refers to as the Everlasting Data Stream, in which data continuously circulates between OT and IT, forming a lasting loop.

為了實現這個壯舉，需要讓OT數據走出原有活動范圍，進入數據中心或云端完成進一步分析，以盡可能提高生產效率、提升生產質量、降低成本，甚至提供新的商業服務。這賦予OT數據新的價值：受保護的本地OT數據傳輸到遠程IT系統，再反饋給OT端，實時優化生產過程，這些數據因此成為可以指導生產的有用數據。這種現象就是Moxa所說的永恒數據流：數據在OT和IT之間不斷循環，形成持續的閉環。

As an example, let's look at an auto parts manufacturer Moxa has worked with. This factory had “bottleneck equipment,” which meant all items had to go through that specific equipment during the manufacturing process. Therefore, if the equipment stopped, so did the entire production line, making maintenance of this equipment imperative. Considering the high stakes, the manufacturer wanted to perform predictive maintenance on it to anticipate the parts that might wear out and stock up in advance to avoid stalling the production because of shortages. In the end, the manufacturer installed additional sensors to the bottleneck equipment. The necessary OT data could then be gathered in real-time and sent to cloud computing for analysis. This Industry 4.0 solution gave management insights into the status of every part, complete with the in-depth prediction analysis needed to take further actions.

以Moxa合作的一家汽車零部件制造商為例進行說明。這家工廠中存在“瓶頸設備”，這意味著所有物品在制造過程中都必須通過某一特定設備。因此，如果該設備停止工作，整個生產線也會停止，對這一特定設備的維護便顯得極為重要。考慮到這種高風險，制造商希望對該設備進行預測性維護，預測哪些部件可能會磨損，并提前補充庫存，避免因部件短缺而導致生產停滯。他們還為該瓶頸設備安裝了額外的傳感器。傳感器收集必要的OT數據，并將其發送到云計算平臺進行分析。最后，云平臺計算零件的狀態并將預測反饋給管理人員，以采取進一步的行動。

Is OT data ready to swim in the IT ocean?
OT數據準備好在IT領域暢游了嗎？

While moving data from an OT domain to an IT domain seems to paint a rose-colored world, a few considerations are required before diving headfirst into the deep end. Moxa proposes these three things to consider before taking this leap:

雖然將數據從OT領域移動到IT領域的設想很美妙，但需三思而后行。Moxa提出，在邁出這一飛躍性的一步前，有三個需要考慮的要素：

Data Interoperability: The first and most common challenge encountered when OT data is moving beyond its original confines is the interoperability of OT/IT data. Since the communication protocols used in the OT field are often vastly different from the ones IT use, systems often run into communication errors. For example, when the OT data output shows a single “5" with no context, IT will never know that the number 5 represents "machine speed" thus stalling the lines of communication. For the OT/IT data cycle to materialize, and for the data to move among the two domains freely, preprocessing OT data is required.

數據互操作性: 當OT數據越過其原始范圍時，遇到的第一個也是最常見的挑戰是OT/IT數據的互操作性。由于OT領域使用的通信協議通常與 IT 領域大不相同，系統在兩者之間嘗試發送數據時經常會出現通信錯誤。例如，當 OT 數據輸出顯示一個沒有上下文的“5”時，IT無法得知數字5代表“機器速度”，通信線路也會因此阻塞。為了實現OT/IT數據循環和兩域間數據的順暢移動，需要對OT數據進行預處理。

Data Integrity: The second challenge is whether OT data can be transmitted in its entirety via connectivity technologies. This is especially challenging because of many disturbances found in OT environments, such as electromagnetic waves generated when devices start, extreme temperatures, harsh environments, and even the mutual interference between the control network and the OT data network, all of which may cause communication disconnection or instability. Disconnection may cause incomplete or dropped transmissions, resulting in erroneous analysis and, by extension, erroneous decision-making. In cases like this, it is important to strengthen the "resilience of data transmission” to ensure that data is promptly transmitted in its entirety.

數據完整性: 第二個挑戰是互聯技術能否保障OT數據的完整傳輸。這尤其具有挑戰性，因為在OT環境中存在許多干擾，例如設備啟動時產生的電磁波、極端溫度、惡劣環境，甚至控制網絡和OT數據網絡之間會相互干擾。這些干擾可能導致通信中斷或通信不穩定。通信中斷會導致傳輸不完整或丟包，導致分析出錯，進而產生錯誤決策。在這種情況下，必須加強“數據傳輸的恢復力”，以確保及時完整地傳輸數據。

Data Security: Finally, the more valuable OT data becomes, the more important it is to secure its transmission. Cybersecurity was not much of an issue in the past since the physical barriers of a factory were most likely enough to protect the data that was contained within its walls. However, now that we connect OT data to IT systems or to the cloud, its old protective shells no longer work. Therefore, how to strengthen "OT network’s security" will become a required focal point for enterprises.

數據安全: 最后，OT數據越有價值，傳輸的安全性就越重要。網絡安全問題在過去并不嚴重，因為工廠的物理屏障幾乎足以保護內部數據。但是，現在我們將OT數據連接到IT系統或云平臺，原來的保護措施便不再起作用。因此，如何加強“OT網絡的安全”將成為企業需要關注的重點。