September 17, 2019

Digital Twins: Coming of Age for the Supply Chain

Written by Garret Weigel | Supply Chain

The next big movement in telematics for the logistics industry could be a combination of hardwired sensors and supply chain monitoring platforms all together in what is now becoming a new phenomenon: a digital twin.


What Is a Digital Twin?

A digital twin is a software model of a physical asset, equipment, system, or any combination of these things. It could be a model of a transportation supply map. It could be a very delicately modeled long-haul truck with cargo inside of it. Or it could be a jet engine. A digital twin is a virtual model of an asset and acts as a snapshot of that physical asset in real time, only with digital attributes.


manufacturing process digital twin model

Manufacturing process digital twin model. Source:


As the consulting firm PwC describes it, a digital twin "captures a virtual model of an organization and helps accelerate strategy. The model can identify elements that are hindering or enabling strategy execution and suggests specific recommendations based on embedded pattern recognition."


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Creating a Digital Twin of a Transportation Fleet

How could this be used in the transportation industry? Consider an over-the-road long haul truck carrying a shipment of temperature-sensitive cargo. The cargo might be refrigerated or frozen. Many variables are operating within that truck and need to be monitored. For example, the temperature inside the container could be key for certain cargo, like perishable foods or vaccines. The humidity within that container may also be monitored for similar reasons. Additionally, the operating parameters of the truck itself can be monitored. The air in the tires, the speed of the truck, the number of slowdowns and startups or speedups of the driver can all be monitored. The driver's time on the road can be monitored. All of this data can be transmitted back to a platform where the truck can be viewed in a three-dimensional image overlaid with these parameters.


simple digital twin example

A simplified representation of using a digital twin to monitor routes of a transportation fleet.


NFI is a fully integrated third-party supply chain solutions provider who utilizes digital twins for its fleet management. They created a digital twin of their fleet using mapping of every incident, trip that they took, breakdowns or other unplanned incidents and stops, and they fed all this information into a software model that extrapolated the necessary data so that it could be viewed remotely by somebody in a far-off location. This enabled them to not only predict any failures of different components of that entire system, but it also allowed them to anticipate any impending problems that they might encounter along the way. Thus, it gave them more control - but it did this in real time. That's the true merit of a digital twin. They can also utilize this data by logging it and doing trend analysis for maintenance purposes, and to determine the root cause of other problems, such as breakdowns or potential spoilage of the cargo.


Creating a Digital Twin of an End-To-End Supply Chain Map

In another example, SKF, a company that makes bearings and mechanical equipment, utilized the digital twin concept to replicate its supply chain network in a map. This digital twin map gave them a view of how their items were being manufactured and moved from their point of origin to their point of distribution. The digital twin concept was applied to it not from one specific point in that map but from the entire map itself. This enabled them to have everything in a single pane. This included service level targets as well as lead times and an understanding of where their multiple SKUs of cargo were located at any particular time in its journey from the manufacturing floor to the customer's hands.


Digital twins are an emerging technology that are certainly in the early adoption phase. They are permeating many different industries, including aerospace and defense, transportation and logistics, and manufacturing. They are a refinement of the use of sensors and hardware in the age of IoT – monitoring not just one variable, but painting a complete picture with multiple variables. In the future, we can expect this technology to serve as a feed for such variables into a graphical and visual display that's easy to comprehend, see, and monitor at any given time.


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