Insights

IoT and digital twins: Keys to industrial resilience in 2026

How to prevent operational disruptions during power outages, supply shocks, or unpredictable demand shifts.

Daniel Field, Head of Emerging Technologies at UST

In a world where disruption has become the new normal, from supply chain interruptions to natural disasters or unpredictable fluctuations in demand, organizations can no longer afford to react too late. Operational resilience must be built into the very core of industrial processes.

Today, that resilience is powered by real-time data, predictive maintenance, and a digital transformation driven by technologies such as the Internet of Things (IoT) and digital twins. Rather than isolated tools, these capabilities represent a new way of operating: an industrial environment that anticipates problems, simulates scenarios, and responds quickly to unexpected situations. Predictive maintenance: intervening at the right moment

The digital transformation of industry has opened the door to a far more intelligent approach to maintenance.

Predictive maintenance enables organizations, particularly in manufacturing environments, to optimize their strategies and perform interventions precisely when needed. Not too early, which can generate unnecessary costs, and not too late, when a failure has already caused an operational interruption.

This approach improves productivity, reduces downtime, and helps minimize operational costs. However, its real value lies in its ability to anticipate problems.

By integrating IoT sensors that continuously collect data with artificial intelligence systems that identify anomalous behavioral patterns , organizations can detect early warning signs of potential failures. In this context, machines stop being passive components within a production line and become active participants in the organization’s information ecosystem. Maintenance, therefore, shifts from reacting to breakdowns to becoming a strategic, data-driven decision.

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Digital twins: simulating before deciding

Beyond maintenance, the Industry 4.0 revolution has introduced a powerful tool for improving operational management and decision-making: digital twins.

These virtual models of physical systems enable real-time simulation, monitoring, and optimization of operations. Powered by data collected through IoT sensors, digital twins replicate the behavior of assets, processes, or infrastructures with high accuracy. This allows teams to test different scenarios and evaluate outcomes before implementing decisions in the physical world.

Simulation, therefore, becomes a strategic advantage. Organizations can anticipate the impact of operational changes, assess risks, or experiment with new configurations without physically intervening in production systems.

At UST, we are applying this technology across a wide range of environments. Our work spans projects from monitoring natural reserves to optimizing factory assembly lines and analyzing electrical systems in vehicles.

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Industrial applications: from pharmaceuticals to automotive

Digital twins are increasingly being applied across a wide variety of industries.

In the pharmaceutical sector, for example, digital twins can simulate critical environmental conditions that directly affect the production of active pharmaceutical ingredients (API). These simulations help ensure regulatory compliance, improve process safety, and anticipate the impact of disruptive events such as natural disasters or supply interruptions.

In the automotive industry, manufacturers can use digital twins to monitor production lines and adjust parameters in real time as demand shifts . This capability also supports the management of model transitions within manufacturing plants, enabling smoother changeovers without compromising quality or performance.

The scope of digital twins, however, goes beyond representing physical objects or environments. At UST, we have also worked on digital twins that model the lifecycle of materials. In these scenarios, data collected from IoT sensors in production facilities is connected with sensors in recycling centers to create a dynamic digital product passport. This approach supports circular economy initiatives by maximizing the secondary value of materials and helping justify greater investment in sustainability throughout a product’s lifecycle.

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Building operational resilience through data

When predictive maintenance and digital twins are integrated into an organization’s technology strategy, their impact extends well beyond operational efficiency. These technologies enable organizations to gain deeper insight into what is happening in complex industrial systems in real time, anticipate potential disruptions, and make faster,more accurate decisions.

Visibility across processes increases significantly, allowing teams to operate using a single shared source of truth. At the same time, the ability to simulate scenarios reduces the need for costly physical testing and helps minimize human error. Together, these capabilities improve the balance between supply and demand, enhance capacity planning, and enable organizations to detect anomalies before they escalate into critical failures.

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Preparing today to withstand tomorrow

Industrial resilience can no longer rely solely on experience or the ability to react quickly during a crisis. In an increasingly uncertain environment, resilience must be built on data, simulation, and automation.

Organizations that are adopting technologies such as industrial IoT, predictive maintenance, digital twins, and advanced analytics are laying the foundations for a new generation of smart factories. These facilities are capable of anticipating problems, adapting to unexpected changes, and minimizing the impact of disruptions.

Adopting these technologies is not simply about digitizing existing processes. It requires redesigning the way organizations observe their operations, interpret data, and make decisions.

Because in today’s industrial landscape, success does not necessarily belong to the biggest organizations, but to the most adaptable.

Understanding how to apply these technologies in real industrial environments has therefore become a strategic priority. At UST, we work with organizations across multiple industries to design more resilient operating models based on IoT, advanced analytics, and digital twins.

Build industrial resilience before disruption strikes.
Discover how IoT and digital twins can help your organization anticipate failure, adapt in real time, and keep operations running—no matter what 2026 brings. Talk to UST about building resilient, data‑driven industrial systems.