TeleVision is an open-sourced immersive teleoperation system with stereo visual feedback. It can be potentially used to teleoperate

from anywhere

Investigating the use of digital twins in networked commercial UAVs

Author(s)

Vemulapalli, Kautilya.

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The Commercial UAS industry is relatively new and has significant growth potential as new technology are incorporated into it, new applications are found, and new regulations are coming in place. Digital Framework, also a relatively new concept, has found acceptance in various industry but has not yet been applied to Commercial UAS while having great potential. This thesis uses the ARIES framework to investigates how this concept can be applied to Commercial UAS, the possible applications and architecture. Towards this end, a study of the enterprise landscape and a stakeholder analysis are conducted. Next the current architecture of the Commercial UAS is identified. From this understanding, a possible future is identified and possible applications from integrating Digital Framework into Commercial UAS are identified. Finally, an architecture for the future UAS was proposed and four possible architectures that incorporated a Digital Framework into Commercial UAS were identified.

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Digital twin technology for enhanced upstream capability in oil and gas

Author(s)

LeBlanc, Mollie B. (Mollie Burke)

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Digital twins are receiving considerable attention as a cutting-edge technology that will transform the oil and gas industry. Powered by a digital thread that connects data across the product lifecycle, a digital twin virtually mirrors or emulates processes, assets, and projects in real-time to generate highly valuable insights. Promises of value creation, delivering optimized production, increased reliability, improved safety, and enhanced foresight, are now driving oil and gas operators to realize their potential. Despite these claimed and expected benefits, realized value is often hard to quantify and explicitly link to digital twin technology. And in addition, consistency in definition and availability of a reference architecture is lacking, resulting in a gap of a standard approach in implementing this technology. This thesis attempts to investigate and summarize the digital twin's enabling technologies (e.g., model-based systems engineering, network infrastructure, the Internet of Things (IoT), and automation) and provide insight into industry digital twin applications in use today. Modeling a simple production facility demonstrates that digital twins have the potential to improve the prediction and mitigation of facility failures leading to overall higher availability and improved financial outlooks for projects. The simulation results of a highly robust and integrated digital twin used on an offshore, deepwater facility showed an improved NPV of $211 million over 27 years. With enhanced upstream capabilities enabled by a digital twin, considerations to reducing daily physical inspection requirements are made more feasible. However, as costs for offshore personnel decrease, the cost of software development and maintenance will increase sharply. Oil and gas assets are more enabled to be monitored and controlled remotely through this increased rigor and oversight provided by the digital twin platform. From the perspective of a three-component digital twin framework consisting of modeling and analytics, enablement technology, and data, a digital twin can provide value from a virtual proxy to a fully autonomous system.

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Adaptability of Manufacturing Operations through Digital Twins

Author(s)

Reyes, Maria Fernanda; Garg, Sachin

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Manufacturing companies are under pressure to build faster and more efficient decision-making capabilities due to the rapidly changing customer demand and expectations. The conventional analytical models are no longer sufficient to capture the complexities of the supply chain. Companies are looking to embark in a digital transformation to address these challenges. One of the digital technologies that offer manufacturers a way to navigate this journey is digital twins, a virtual replica of an object, process or system. Our project focused on studying how digital twins can react to a complex and dynamic environment to create an adaptive mechanism and how can digital twins add value to increase operational efficiency. To answer these questions, we created a conceptual framework of digital twin, AI model and developed a learning feedback loop between simulation and artificial intelligence algorithm. We modeled the supply chain network by using data from a beverage industry and created what-if scenarios that involved varying customer demand and lead time through discrete-event simulation. The output of the simulation was fed into the AI algorithm. The AI prediction was simulated again and results were analyzed. Our research provides insights and discover value associated with adopting these technologies for better decision making. Our recommendation from this study will help supply chain managers understand that a digital twin and AI model framework can be developed, and can be utilized to foresee patterns in supply chain, and proactively take actions to resolve any bottlenecks and constraints.

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Redesigning Undergraduate Engineering Education at MIT – the New Engineering

Education Transformation (NEET) initiative

Prof. Edward F. Crawley, Massachusetts Institute of Technology

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Professor Ed Crawley is the Ford Professor of Engineering at MIT, a member of the National Academy

of Engineering, and a recipient of the Bernard M. Gordon Prize for engineering education of the NAE.

He is the Founding President of the Skolkovo Institute of Science and Technology (Skoltech) and. the

Co-Director of NEET at MIT.

Prof. Anette ”Peko” Hosoi, Massachusetts Institute of Technology

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New Engineering Education Transformation (NEET)

Babi Mitra

Executive Director, NEET

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MIT

Technische Universiteit Eindhoven

May 17th, 2018

neet.mit.edu

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New Engineering Education Transformation (NEET)

BabiMitra

ExecutiveDirector,NEET

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MIT

(wasFoundingDeanofEngineering

BMLMunjalUniversity,India)

May 25, 2019

Engineering Education for the Future (EEF)

ITA

São José dos Campos, Brazil

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CDIO and Universities as Engines of Economic Development

Ed Crawley

MIT

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Skoltech

January 2018

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