Past Event

COVID-19 and Manufacturing: Digital Twins

June 16, 2020
COVID-19 and Manufacturing: Digital Twins
Webinar

Location

Zoom Webinar

Education Partner:


Overview

Digital Twins: The Vision. And Demystified.

The Vision:  With the proliferation of digital technologies and a rapidly changing global market, manufacturing paradigms will shift from automated to autonomous operations with more flexible flow chains. This in turn enables a more rapid realization of products from concepts in commercially viable ways, shorter time to market and faster throughput.

The digital thread of sensors, data, computation, and information is required to fully realize the potential of digitally-native production systems, with high-value, customized, products.   The digitally native production system includes digital twins of the product, materials, manufacturing process, supply chain and production line. 

A full framework of digital twins assist in simulating and integrating sensor data for data analytics. Digital twins enable greater throughput, early identification of bottleneck processes, supply chain issues and identification of novel process and production level opportunities.

And Demystified:  Digital twins are, simply, physics-based and data driven models. They are design and decision tools. Let's explore some examples.

 


Instructions to join event:
Please register for the Zoom Webinar here. You can then join the webinar through the Zoom application on your computer or phone, within your Internet browser*, or by dialing in*. When accessing the webinar, you will be prompted to enter your name, email address, and other optional information. After registering, you will receive a confirmation email containing information about how to join the webinar.

If you need further assistance, please consult the Zoom support instructions to join a webinar.
*These options to connect offer fewer features with less forms of engagement. We recommend installing the Zoom application on your device for the best webinar experience.

  • Overview

    Digital Twins: The Vision. And Demystified.

    The Vision:  With the proliferation of digital technologies and a rapidly changing global market, manufacturing paradigms will shift from automated to autonomous operations with more flexible flow chains. This in turn enables a more rapid realization of products from concepts in commercially viable ways, shorter time to market and faster throughput.

    The digital thread of sensors, data, computation, and information is required to fully realize the potential of digitally-native production systems, with high-value, customized, products.   The digitally native production system includes digital twins of the product, materials, manufacturing process, supply chain and production line. 

    A full framework of digital twins assist in simulating and integrating sensor data for data analytics. Digital twins enable greater throughput, early identification of bottleneck processes, supply chain issues and identification of novel process and production level opportunities.

    And Demystified:  Digital twins are, simply, physics-based and data driven models. They are design and decision tools. Let's explore some examples.

     


    Instructions to join event:
    Please register for the Zoom Webinar here. You can then join the webinar through the Zoom application on your computer or phone, within your Internet browser*, or by dialing in*. When accessing the webinar, you will be prompted to enter your name, email address, and other optional information. After registering, you will receive a confirmation email containing information about how to join the webinar.

    If you need further assistance, please consult the Zoom support instructions to join a webinar.
    *These options to connect offer fewer features with less forms of engagement. We recommend installing the Zoom application on your device for the best webinar experience.


Agenda

11:00am - 12:00pm
Associate Director, MIT.nano
Faculty Lead, Industry Immersion Program in Mechanical Engineering
Brian Anthony
Associate Director, MIT.nano
Faculty Lead, Industry Immersion Program in Mechanical Engineering

Dr. Anthony has over 25 years of commercial, research, and teaching experience in product realization and information enabled manufacturing. He has extensive experience in market driven technology innovation, product realization, and business entrepreneurship and commercialization at the intersection between information technology and advanced manufacturing. His research and product development interests cross the boundaries of manufacturing and design, medical imaging, computer vision, acoustic and ultrasonic imaging, large‐scale computation and simulation, optimization, metrology, autonomous systems, and robotics. His teaching interests include the modeling of large-scale systems in a wide variety of decision-making domains and the development of optimization algorithms and software for analyzing and designing such systems.  He teaches on-line and on-campus professional programs in Smart Manufacturing and sensory systems Beyond IoT.

Dr. Anthony spent the first part of his career as an entrepreneur. He developed and directed the development of products and solutions for the industrial and scientific video markets. His products fueled corporate growth from startup to dominant market leader. He has been awarded 20 patents, published over 100 peer reviewed articles, and won an Emmy from the Academy of Television Arts and Sciences for innovations in sports broadcast technical innovation.

The Vision:  With the proliferation of digital technologies and a rapidly changing global market, manufacturing paradigms will shift from automated to autonomous operations with more flexible flow chains. This in turn enables a more rapid realization of products from concepts in commercially viable ways, shorter time to market and faster throughput.

The digital thread of sensors, data, computation, and information is required to fully realize the potential of digitally-native production systems, with high-value, customized, products.   The digitally native production system includes digital twins of the product, materials, manufacturing process, supply chain and production line. 

A full framework of digital twins assist in simulating and integrating sensor data for data analytics. Digital twins enable greater throughput, early identification of bottleneck processes, supply chain issues and identification of novel process and production level opportunities.

And Demystified:  Digital twins are, simply, physics-based and data driven models. They are design and decision tools. Let's explore some examples.

  • Agenda
    11:00am - 12:00pm
    Associate Director, MIT.nano
    Faculty Lead, Industry Immersion Program in Mechanical Engineering
    Brian Anthony
    Associate Director, MIT.nano
    Faculty Lead, Industry Immersion Program in Mechanical Engineering

    Dr. Anthony has over 25 years of commercial, research, and teaching experience in product realization and information enabled manufacturing. He has extensive experience in market driven technology innovation, product realization, and business entrepreneurship and commercialization at the intersection between information technology and advanced manufacturing. His research and product development interests cross the boundaries of manufacturing and design, medical imaging, computer vision, acoustic and ultrasonic imaging, large‐scale computation and simulation, optimization, metrology, autonomous systems, and robotics. His teaching interests include the modeling of large-scale systems in a wide variety of decision-making domains and the development of optimization algorithms and software for analyzing and designing such systems.  He teaches on-line and on-campus professional programs in Smart Manufacturing and sensory systems Beyond IoT.

    Dr. Anthony spent the first part of his career as an entrepreneur. He developed and directed the development of products and solutions for the industrial and scientific video markets. His products fueled corporate growth from startup to dominant market leader. He has been awarded 20 patents, published over 100 peer reviewed articles, and won an Emmy from the Academy of Television Arts and Sciences for innovations in sports broadcast technical innovation.

    The Vision:  With the proliferation of digital technologies and a rapidly changing global market, manufacturing paradigms will shift from automated to autonomous operations with more flexible flow chains. This in turn enables a more rapid realization of products from concepts in commercially viable ways, shorter time to market and faster throughput.

    The digital thread of sensors, data, computation, and information is required to fully realize the potential of digitally-native production systems, with high-value, customized, products.   The digitally native production system includes digital twins of the product, materials, manufacturing process, supply chain and production line. 

    A full framework of digital twins assist in simulating and integrating sensor data for data analytics. Digital twins enable greater throughput, early identification of bottleneck processes, supply chain issues and identification of novel process and production level opportunities.

    And Demystified:  Digital twins are, simply, physics-based and data driven models. They are design and decision tools. Let's explore some examples.