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E-raamat: Digital Twin Development and Deployment on the Cloud: Developing Cloud-Friendly Dynamic Models Using Simulink(R)/SimscapeTM and Amazon AWS

(Assistant Professor, Mechanical Engineering, Prince Mohammad Bin Fahd University, KSA.), (Senior Controls Engineer, Cummins Emissions Solutions, Columbus, IN, USA), (Technical Advisor with KPIT Infosystems Inc, Columbus, IN, USA)
  • Formaat: 592 pages, Approx. 300 illustrations; Illustrations, unspecified
  • Ilmumisaeg: 24-May-2020
  • Kirjastus: Academic Press Inc
  • Keel: eng
  • ISBN-13: 9780128216460
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  • Hind: 136,43 €*
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  • Formaat: 592 pages, Approx. 300 illustrations; Illustrations, unspecified
  • Ilmumisaeg: 24-May-2020
  • Kirjastus: Academic Press Inc
  • Keel: eng
  • ISBN-13: 9780128216460
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Digital Twin Development and Deployment in the Cloud: Developing Cloud-Friendly Dynamic Models Using Simulink®/SimscapeTM and Amazon AWS promotes a physics-based approach to the field of digital twins. Through the use of multiphysics models running in the cloud, significant improvement to the diagnostics and prognostic of systems can be attained. The book draws a clear definition of digital twins, helping business leaders clearly identify the value it brings. In addition, it outlines the key elements needed for deployment, including the hardware and software tools needed. Special attention is paid to the process of developing and deploying the multi-physics models of the digital twins.

  • Provides a high-level overview of digital twins and their underutilization in the field of asset management and maintenance
  • Proposes a streamline process to create digital twins for a wide variety of applications using MATLAB® Simscape™
  • Deploys developed digital twins on Amazon Web Services
  • Includes MATLAB and Simulink codes available for free download on MATLAB central
  • Covers popular prototyping hardwares, such as Arduino and Raspberry Pi
1. Added value of digital twins and IoT
2. Cloud and IoT technologies
3. Digital twin model creation of a robotic arm
4. Ball on plate modeling
5. Digital twin model creation of double mass spring damper system
6. Digital twin model creation of solar panels
7. Digital twin development for an inverter circuit for motor drive systems
8. Digital twin development and cloud deployment for a Hybrid Electric Vehicle
9. Digital twin development and cloud deployment for a DC Motor Control embedded system
10. Digital twin development and deployment for a wind turbine Index
Dr. Khaled has extensive industrial and academic experience in the field of dynamics, controls and IoT solutions. He is currently an Assistant professor in Prince Mohammad Bin Fahd University. He is an innovator with more than 30 patents and patent applications in the fields of smart systems and energy. He is the author of "Practical Design and Application of Model Predictive Control". He also has numerous publications in the field of controls and autonomous navigation. Dr. Khaled is a green-belt six sigma certified. He received the status of "Outstanding Researcher" granted by the U.S Government in 2012. Bibin has a Master of Science in Mechanical engineering and 12 years of industrial experience in the field of Controls Design, Software Development and Rapid Prototyping. He is currently working as a Technical Advisor with KPIT Technologies Inc, USA. Bibin has worked on vehicle, aftertreatment, air-handling and engine modelling and controls and on board diagnostic development. He is an expert in Matlab and Simulink as well as Hardware and Software solutions for the control of vehicle and powertrain systems. He has 7 patents and several patent applications and published 5 journal and conference papers. Bibin is the co-author of "Practical Design and Application of Model Predictive Control". Affan Siddiqui is currently working in Cummins Emissions Solutions as a Senior Controls Engineer. He has 4 years of experience in software development of control algorithms and diagnostics of diesel engine aftertreatment systems. Affan specializes in embedded control systems using Matlab Simulink and is an expert in the urea doser control portion of the aftertreatment system with 1 patent application. Before his work in Cummins, Affan acquired a Master of Science degree in Mechanical Engineering from Virginia Tech. His master's thesis "A New Inspection Method Based on RGB-D Profiling" is based on an inexpensive autonomous railway and road mapping system using Robot Operating System (ROS) and Microsoft Kinect cameras.