Modeling of Cyber-Physical Systems and Digital Twin Based on Edge Computing, Fog Computing and Cloud Computing Towards Smart Manufacturing

Author(s):  
Qinglin Qi ◽  
Dongming Zhao ◽  
T. Warren Liao ◽  
Fei Tao

Nowadays, smart manufacturing has attracted more and more interesting and attentions of researchers. As an important prerequisite for smart manufacturing, the cyber-physical integration of manufacturing is becoming more and more important. Cyber-physical systems (CPS) and digital twin (DT) are the preferred means to achieve the interoperability and integration between the physical and cyber worlds. From the perspective of hierarchy, CPS and DT can be divided into unit level, system level, and SoS (system of system) level. To meet the different requirements of each level, the following three complementary technologies, i.e., edge computing, fog computing and cloud computing, are instrumental to accelerate the development of various CPS and DT. In this article, the perspectives of unit-level, system-level, and SoS-level of CPS and DT supported by edge computing, fog computing and cloud computing are discussed.

Author(s):  
Bert Van Acker ◽  
Joost Mertens ◽  
Paul De Meulenaere ◽  
Joachim Denil

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4762 ◽  
Author(s):  
Ahmed Saad ◽  
Samy Faddel ◽  
Osama Mohammed

With the emergence of distributed energy resources (DERs), with their associated communication and control complexities, there is a need for an efficient platform that can digest all the incoming data and ensure the reliable operation of the power system. The digital twin (DT) is a new concept that can unleash tremendous opportunities and can be used at the different control and security levels of power systems. This paper provides a methodology for the modelling of the implementation of energy cyber-physical systems (ECPSs) that can be used for multiple applications. Two DT types are introduced to cover the high-bandwidth and the low-bandwidth applications that need centric oversight decision making. The concept of the digital twin is validated and tested using Amazon Web Services (AWS) as a cloud host that can incorporate physical and data models as well as being able to receive live measurements from the different actual power and control entities. The experimental results demonstrate the feasibility of the real-time implementation of the DT for the ECPS based on internet of things (IoT) and cloud computing technologies. The normalized mean-square error for the low-bandwidth DT case was 3.7%. In the case of a high-bandwidth DT, the proposed method showed superior performance in reconstructing the voltage estimates, with 98.2% accuracy from only the controllers’ states.


Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3488 ◽  
Author(s):  
Wafa Bouaynaya ◽  
Hongbo Lyu ◽  
Zuopeng Zhang

With the growing popularity of Internet of Things (IoT) and Cyber-Physical Systems (CPS), cloud- based systems have assumed a greater important role. However, there lacks formal approaches to modeling the risks transferred through information systems implemented in a cloud-based environment. This paper explores formal methods to quantify the risks associated with an information system and evaluate its variation throughout its implementation. Specifically, we study the risk variation through a quantitative and longitudinal model spanning from the launch of a cloud-based information systems project to its completion. In addition, we propose to redefine the risk estimation method to differentiate a mitigated risk from an unmitigated risk. This research makes valuable contributions by helping practitioners understand whether cloud computing presents a competitive advantage or a threat to the sustainability of a company.


Twin-Control ◽  
2019 ◽  
pp. 3-21 ◽  
Author(s):  
Mikel Armendia ◽  
Aitor Alzaga ◽  
Flavien Peysson ◽  
Tobias Fuertjes ◽  
Frédéric Cugnon ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document