User:Vishnu Natarajan

Off-Board Diagnostics is a term used for diagnostic of planes, vehicles and other machines. It was created by Nassim Khaled in 2018 and first published in his book in 2020[1]. Motivated by Max 737 issues and the subsequent crashes of airplanes [2], Nassim and his co-authors wanted to make the process of predicting and detecting failures of vehicles, machines and processes more robust. Unlike on-board diagnostic [3] where the diagnostic decision takes place in the controller of the machine, Nassim proposed to have the decision made in the cloud [1]. The main advantages of off-BD compared to OBD is the computational power in the cloud. Nassim proposed using physics-based models that can be used as virtual copies of the physical machine. These virtual copies, or digital twins, can then be used as a reference to check if the machine is operating properly. and thus the term Off-BD. Figure 1 demonstrates the concept of a turbine asset and it’s virtual replica (i.e. the model) and how their outputs can be compared to detect a deterioration in the performance of the physical asset.

Cloud simulations constitue a very small part of the cloud revenue which is mostly geared towards entertainment. For the purpose of simulations and diagnostics, cloud technology is hugely underutilized. Figure 2 shows the general steps involved in designing Off-BD [1].

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