Industrial Digital Twins in Action: Transforming Operations

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As enterprises strive for efficiency, accuracy, and innovation, the concept of digital twins has emerged as a transformative force. By creating a virtual representation of physical assets, digital twins enable organizations to optimize processes, reduce costs, and enhance decision-making throughout the project lifecycle.

The Role of Digital Twins in Enterprises

At its simplest, a digital twin is a virtual model of a physical object or system, continuously updated with real-time data from sensors, artificial intelligence (AI), and other sources. These dynamic models allow businesses to simulate, analyze, and predict how assets will perform in various conditions—without having to manipulate the physical asset itself.

Siemens USA CEO Barbara Humpton emphasized this potential in a recent interview, stating, “Digital twins can help you play around with a whole lot of permutations before you start to bend metal.” Siemens' work on the Mars rover, where their digital twin technology helped simulate landing conditions that couldn't be replicated on Earth, is a powerful example of the technology’s capabilities.

Digital twins have moved beyond individual components; they now encompass entire systems, including buildings, bridges, production lines, and even cities. In construction, federal agencies are beginning to require digital twins on projects to ensure better oversight and management of assets. The ability to create accurate, real-time digital versions of infrastructure is set to become a standard practice as industries continue to modernize.

The benefits are tangible. “Companies leveraging Industry 4.0 technologies can report up to 30% increase in productivity and 20% reductions in operational costs,” said Ibrahim Imam of PlanRadar. He continued, “In 2024, nearly 50% of large industrial companies are expected to use digital twins, enhancing their product development cycles and operational efficiency.”

The Role of Reality-Capture Technology

To ensure that digital twins are accurate and useful, reliable data collection is critical. Reality-capture technology—including drones, 3D laser scanning, mobile mapping, and unmanned aerial vehicle (UAV) systems—plays a pivotal role in creating these precise digital representations. These technologies allow surveyors and engineers to collect vast amounts of data from complex environments quickly, safely, and accurately.

One of the most significant advantages of using reality-capture technology in tandem with digital twins is that it provides a detailed and up-to-date picture of a construction site or production facility. For example, drones can capture aerial views of a site, transforming that information into actionable 3D data models. This ensures that companies can make informed decisions, monitor construction progress, and troubleshoot potential issues before they cause delays or add to costs.

By using reality-capture solutions, project teams can scan and map locations in a way that wasn’t possible just a few years ago. Modern 3D scanners are so advanced that they can capture the intricate details of a bolt’s thread. This precision enhances the effectiveness of digital twins, enabling teams to pivot quickly when unforeseen challenges arise.

Enhancing Project Lifecycle Management

Digital twins offer value across every phase of a project, from the design and construction stages to long-term maintenance and operation. When continuously updated with real-time information, they allow stakeholders to monitor progress, improve quality assurance, and make better decisions based on current and historical data.

In the construction sector, this ability to simulate different scenarios before actual production starts mitigates risk. Historically, relying on 2D datasets for planning could result in costly errors. As Troy Dahlin noted in an article in Informed Infrastructure, relying on outdated or incomplete 2D information can lead to "decisions based on inaccurate information," which can have disastrous consequences. Digital twins eliminate this risk by providing a constantly updated, data-rich model of the asset that allows teams to simulate potential changes in real-time and adjust accordingly.

Moreover, digital twins create a historical record of projects. If a building or system develops issues, engineers can refer back to the digital twin to determine the exact cause of the problem—whether it's an issue with the materials used, sub-compaction, or improper placement of structural elements. Without this technology, companies often have to rely on guesswork and spend valuable resources identifying problems.

ENEOS announced last month that it’s using Cognite Data Fusion to build a digital twin infrastructure in its refineries. The goals of this initiative—increased engineer productivity, improved maintenance planning accuracy, and improved construction quality—span the product lifecycle.

Bridging the Skills Gap

One of the major challenges in industrial sectors is the ongoing labor shortage. Digital twins, along with reality-capture technologies, are helping address this issue by automating many labor-intensive tasks. This not only makes operations more efficient but also attracts younger workers who are drawn to tech-focused roles.

By using tools like 3D laser scanning and drones, fewer workers are required to collect critical data, meaning companies can do more with less. Additionally, these technologies create new training opportunities for the existing workforce, helping them build the skills necessary to work in increasingly technology-driven environments.

As Dahlin pointed out, these digital solutions can even appeal to potential recruits, aligning with the trend toward more digitized job sites and providing an opportunity to close the labor gap through innovation.

Overcoming Challenges in Deploying Digital Twins

While digital twins offer immense promise, they are not without challenges. From complexity and incomplete networks to skills shortages, businesses deploying digital twins need to be aware of potential roadblocks and have strategies in place to navigate them effectively.

An article in ZDNET detailed seven challenges of industrial digital twins and how to navigate them:

  1. Complexity

  2. Incomplete networks

  3. Data velocity

  4. Real-time user interfaces that aren’t real-time enough

  5. Inconsistent standards

  6. Managing diverse data inputs

  7. Lack of skills

By addressing these challenges head-on, companies can unlock the full potential of digital twins. Emphasizing business-first strategies, as Jason Noel from EY Consulting suggests, can help ensure digital twins not only provide technical benefits but also drive meaningful outcomes for the entire organization.

The Road Ahead

As digital twin technology continues to evolve, its applications are expanding beyond individual assets and projects. Entire cities are being scanned and modeled to provide predictive analytics that enhance urban planning, improve infrastructure maintenance, and drive sustainability. Whether it’s helping optimize construction projects or informing future smart infrastructure initiatives, the potential of digital twins is boundless.

Looking ahead, as technology becomes more affordable and accessible, digital twins will likely become a standard tool across multiple industries. Companies that resist adopting this technology risk falling behind their competitors, as digital twins will increasingly be expected by clients seeking detailed, accurate, and data-driven project management.

The message is clear: those who embrace digital twin technology will find themselves at the forefront of the next industrial revolution, equipped with the tools necessary to compete on the global stage.

Want more digital twin news? Mark your calendar for March 3-4, 2025, for the 4th Annual Industrial Digital Twin Forum. (New website, who dis?)