Digital Twins in Logistics & Construction

A few weeks ago, we wrote an article about digital twins. We mentioned some of the challenges in building digital twins. Some were quite obvious (like cost and precise representation), others really touched upon what we at Nemeon do on a day to day: "managing data." We understand now that data quality and (data) interoperability do have a profound impact on the value and accurateness of a digital twin (regardless of which industry in which they are used).

In the industries we focus on at Nemeon (Logistics, Construction, Travel & Entertainment), construction seems to "lead the pack" when it comes to building digital twins. "BIM" (Building Information Modelling) has led to full-blown 3D models of physical structures. It is only a matter of time before they will include more "living" items such as sensor data to track things like energy consumption or wear and tear on technical appliances (like HVAC systems).

In capital-intensive sectors that build expensive structures, digital twins are bound to arrive first. Think about digital twins of energy plants (incl. windmill farms) or transport networks (like train or subway networks). In these sectors, the investment in building a digital twin is comparatively low to the overall cost of the real-live item. As the technology becomes more mature, we will see a trickle down effect to more "everyday" structures (like office buildings or living units).

In logistics, a tough (low-margin) business, digital twins have taken more time to arrive. DHL trend research wrote:

While digital twins have not yet achieved widespread application in logistics, many of the key enabling technologies are already in place.

We are seeing digital twins these days in four distinct areas:

1. Packaging and container digital twins
2. Digital twins of shipments
3. Digital twins of warehouses and distribution centers
4. Digital twins of logistics infrastructure
5. Digital twins of global logistics networks

We are confident that cloud technology, AI, VR and sensor data will converge and create new opportunities. Only a matter of time before we see more breakthroughs in this exciting area. What all of these breakthroughs will have in common though is that they can only be leveraged to their full extent in organizations that already reached a higher data maturity level and dispose of a scalable data infrastructure.