In this interview, Jordan Kock, co-founder and COO of Solid Cloud, and Supertrends Expert, provides a deep dive into how his company is leveraging digital twin technology to enhance project accuracy and efficiency. Jordan discusses the practical applications, benefits, and current challenges of digital twins. He also sheds light on their role in improving workflows, efficiency, and management in construction, processing, and solar energy management.

Supertrends: Welcome to Supertrends Interviews. Today, my guest is Jordan Kock. He has extensive experience in the construction industry, with a special focus on the solar industry. He’s a co-founder of Solid Cloud, a company that aims to transform the construction sector. Hello, Jordan.

Jordan Kock: Hi, good afternoon. Thank you for having me.

Supertrends: Thank you for agreeing to this interview. So maybe we could start with you first explaining what Solid Cloud actually does.

J.K.: Sure. We serve three types of clients: solar, construction, and the processing industry. We help them by collecting data and structuring it in a way that can be integrated into their existing systems. This is the biggest struggle currently in the digital twin sector, in my opinion.

Supertrends: And what exactly is a digital twin? Could you explain it for people who have never heard about this concept?

J.K.: A digital twin is commonly understood as a digital replica of a physical object, but it can also be purely informational. For example, a digital twin of the brain isn’t something you can visualize, but it represents data about the brain. Essentially, a digital twin is an exact digital representation of a physical object or system, enriched with data and attributes, and continuously updated to mirror its real-world counterpart throughout its lifecycle. While some might compare it to a detailed model or a simulation, what sets digital twins apart is their ability to stay synchronized with the physical object in real-time, enabling ongoing monitoring and optimization.

Supertrends: There are probably many other simulation models. How are digital twins different from these older models?

J.K.: A digital twin aims to be consistently up to date with its physical counterpart, unlike static models, which represent only a moment in time. This real-time synchronization allows for more accurate and actionable insights, making it possible to monitor and optimize the object or system as it evolves.

Supertrends: I imagine you need a lot of different data to build a digital twin. What types of data and technologies do you use?

J.K.: Definitely. Digital twins involve several types of data. We use 3D scanning, such as LIDAR (Light Detection and Ranging), thermographic scanning, and photogrammetry for spatial data. IoT sensors collect real-time data from embedded physical assets. Processing and analyzing this data creates an accurate digital representation. We also need computing/cloud computing and visualization tools like Nira.app, which helps us visualize large spatial datasets in real-time and make actionable decisions from them.

Supertrends: Building the digital twin is one thing, but how do you explore it?

J.K.: There are many platforms out there. As I mentioned, we use Nira.app for spatial data exploration. In different industries, tools vary. For instance, in solar, thermographic scans help detect inefficiencies in panels. AI analyzes the scans to flag temperature anomalies in real time, ensuring proactive maintenance. In contrast, sectors like monument restoration focus more on spatial data, using 3D scans to create as-built models for accurate restoration work. The tools and methods depend on the specific needs of each sector.

Supertrends: Now, let's talk about your sector, the construction industry. How can digital twins make operations more efficient or smoother? How do you apply digital twins in construction, and what are the benefits?

J.K.: In construction, digital twins improve accuracy by using real spatial data to create a 3D model from a scan, which reduces the likelihood of mistakes during the design and planning stages. This is important because real buildings often differ from the drawings—walls may not be perfectly straight, for example. Using digital twins as a base for design minimizes expensive redesigns and remeasurements. This approach saves time and reduces costs.

For example, we worked on a project for O-I Glass, a glass production giant. We scanned their sites and used VR to help identify which pipes needed removal. By converting 2D plans into 3D models, we could immediately see potential collisions between new high-pressure piping and existing structures. This streamlined collaboration and minimized risks.

Supertrends: OK, so did I understand correctly that this technology can be used not only in the design phase but also later for maintenance and keeping things operational? It’s not just for designing or maintaining but can be used at various stages of a construction project.

J.K.: Yes, exactly. Digital twins can be used throughout a building's lifecycle, but the key challenge is keeping the twin up to date. If the model isn’t updated as changes happen in the physical environment, you lose the benefits of having a twin in the first place. This is where tools like IoT sensors and AI come in. They can automatically update the digital twin in real time, ensuring that the data remains accurate.

The issue right now is that maintaining these models is resource-intensive, requiring specialized software and personnel. That's why structured data management systems, cloud solutions, and edge computing are becoming essential for handling this complexity.

Supertrends: And if you had to name the biggest challenge when adopting digital twins in the construction industry, what would it be?

J.K.: One of the major challenges is ensuring interoperability between contractors and subcontractors. While a main contractor might be using advanced 3D modeling software like Revit, the subcontractors might still be working with 2D drawings. This lack of alignment can create inefficiencies and reduce the benefits of the digital twin.

Moreover, integrating different types of data, like LIDAR scans, thermographic images, and IoT sensor data, into a unified model is difficult. Tools like Bonsai.org (formerly BlenderBIM) and Speckle help bridge these gaps by facilitating data exchange across different platforms, but there’s still work to be done in terms of standardization.

Supertrends: Do you think digital twins will eventually become mainstream, and if so, when do you think that might happen?

J.K.: I think we’re heading toward broader adoption, especially as AI becomes more integrated into digital twins. Keeping twins updated in real-time is one of the biggest barriers to full adoption, but AI is helping automate a lot of that process. We’re already seeing AI applications that can predict maintenance issues or automate data updates from IoT sensors.

My prediction is that we'll see significant changes in the next five years, and full adoption could happen within ten years, as data management becomes more streamlined and affordable solutions like cloud and edge computing improve.

Supertrends: Which sectors do you think will be impacted the most by widespread adoption?

J.K.: I believe every sector has the potential to benefit, but industries that rely heavily on spatial accuracy, like construction and manufacturing, will see the most immediate gains. In solar, for instance, digital twins already help optimize performance by integrating thermographic and spatial data in real time.

In the processing industry, digital twins can optimize operations by connecting 3D models with real-time data from machines, which helps predict issues before they occur. The potential is huge, especially as tools become more affordable and easier to implement.

Supertrends: One concern that comes to mind is data protection. Could you elaborate on this topic?

J.K.: Absolutely, data security is a big concern. Most of the platforms we use come with built-in encryption and access control measures. Regular audits are also essential to ensure compliance with security standards. For smaller companies, building your own platform isn’t usually feasible, so it’s better to rely on established platforms with strong data protection protocols.

Supertrends: Do you have any favorite projects you've worked on with Solid Cloud, something you're especially proud of?

J.K.: One project that stands out is the work we did for O-I Glass. By using digital twins, we reduced the project timeline from 10 months to just under 3 months. This was a huge success, and it showed just how impactful digital twin technology can be when applied correctly.

Supertrends: Is there anything else you’d like to share or any additional points you’d like to make before we conclude?

J.K.: I think digital twins are a fantastic tool, but we still have challenges to overcome, especially with data integration and keeping models updated. Structured data management, cloud storage, and edge computing will play a big role in the future of this technology. The key is finding ways to manage the flow of information effectively, and AI will likely be a driving force in helping us solve these issues. But the potential benefits—especially in terms of efficiency, cost savings, and decision-making—are huge across industries.

The text is a transcript of an interview conducted on 22 July 2024. The interview was conducted as part of Supertrends' 'Interviews with Experts' series. Please note that the transcript may have been lightly edited for editorial reasons.