Sameer Prabhu / MathWorks Inc.

工業4.0是以模擬和以感測器資料為基礎之解析模型的資料群聚應用，借助現今比以往更強大運算能力的軟硬體，從資料中獲得新見解而開啟新的商業機會。同樣地，數位分身(Digital Twin)亦同時包含了資料導向與以物理模型為基礎的模型，它主要是從營業資產的資料去建立一個資產的數位複製品。在這樣的情況下，人工智慧、機器學習、解析模型再加上從資產端來的資料流之聚集，如此一來，會營業資產變化而更新與改變的數位模擬模型變得極為關鍵，這個模型可以被用來預測、what-if模擬、異常偵測、錯誤隔離等等。預測性維護(Predictive Maintenance)包含了開發和把狀態監控與預測性維護軟體佈署至企業IT及OT系統。

本段演講將介紹MATLAB與Simulink如何提供工程師足夠處理能力，以因應涉及到開發工業4.0、數位分身、預測性維護等實際應用所面臨的挑戰。

Industry 4.0 is the confluence of simulation and sensor based analytic models with greater computational capabilities than we ever had access to in the past, which then opens up new opportunities for businesses for getting insight out of their data. Similarly, Digital Twin involves using both data-driven and physics-based models, along with data from the operating asset to create a digital replica of the asset. In this case, the confluence of artificial intelligence, machine learning, and analytic models along with streaming data from the asset, leads to a digital simulation model that updates and changes as the operating asset changes, which can then be used for prediction, what-if simulations, anomaly detection, fault isolation, and more. Predictive Maintenance involves developing and deploying condition monitoring and predictive maintenance software to enterprise IT and OT systems. In this talk you will learn how MATLAB® and Simulink® are giving engineers the ability to tackle the challenges involved in developing practical applications related to Industry 4.0, Digital Twin, and Predictive Maintenance.