Digital Twins For Logistics
Indian Transport & Logistics News
|July - August 2019
How do you operate, maintain, or repair systems when you aren’t in their physical proximity? That was the challenge for NASA when it had to monitor its rockets and vehicles on space missions. So it created mirrored systems or digital twins, still on earth that allowed engineers and astronauts to determine how they could control space mission vehicles. The concept of digital twin helps to control Chandrayaan-2, India’s lunar mission. A digital twin can create huge value in logistics and provide greater insight into and visibility of the current and future state of logistics.
It was in the late 1990s that Michael Grieves began thinking about the idea of the digital twin. Grieves was then pursuing his executive management doctorate program at Case Western Reserve University in Cleveland, Ohio. However, the term he used then for the concept was “Doubleganger”. In 2002 Grieves introduced the concept as part of his product lifecycle management (PLM) research at the University of Michigan. The slide that contained the revolutionary idea showed a simple graphic with the sober title “Conceptual Ideal for PLM”.
While the term changed over and over again in the years to follow, this graphic already contained everything that still makes up the digital twin: a virtual image that contains all the information of a physical product and reflects it throughout the entire product lifecycle – an idea so visionary that it could not be achieved for many years.
While Grieves was toying with the idea years ago and was not in a position to implement a comprehensive digital twin, he was firmly convinced that the computer would be powerful enough someday to bring his ideas to life. Today, machine intelligence and connectivity to the cloud allows us an unprecedented potential for large-scale implementation of digital twin technology for companies in a variety of industries.
Digital twins are today coming of age. Fuelled by the confluence of progress in the internet of things, big data, cloud computing, open APIs, artificial intelligence, and virtual reality, once static digital models and simulations can now truly come alive in real-time to help predict future situations, the state of physical things, and even the world around us.
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