Digital twins in manufacturing – design, optimise and expand

By Johan Potgieter, Cluster Industrial Software Lead at Schneider Electric

14 May 2025

Digital twin technology can help create better products, fast.  It can transform the work of product development too.  A strong statement from McKinsey that reinforces how far digital twins have come in manufacturing.

In fact, global market for digital twin technologies is forecast to grow at about 60 percent annually over the next five years, reaching $73.5 billion by 2027, states McKinsey.

Today, digital twins serve as the bridge between the physical and digital worlds.  The benefits are tremendous; by creating a digital counterpart of a physical asset, manufacturers can simulate different scenarios, predict outcomes, and optimise processes without the need for physical trials.  A win-win scenario and particularly beneficial in areas such as:

• Predictive maintenance - digital twins can predict equipment failures before it occurs, allowing for timely maintenance and reducing downtime.
• Process optimisation- by simulating various production scenarios, manufacturers can identify the most efficient processes, leading to cost savings and improved productivity.
• Quality control- digital twins enable real-time monitoring and quality assurance, ensuring that products meet the required standards throughout the production cycle.
• Supply chain management- by integrating digital twins into supply chain operations, companies can enhance visibility, improve logistics, and respond swiftly to disruptions.

Digital twins in the design phase

Apart from the abovementioned operational benefits, digital twins are proving to be invaluable in the design phase. Granted, while live data won’t be available, information such as process requirements and constraints can help with tasks such as energy monitoring, mass balance calculations and projected throughput.

In turn, this data-centric approach can reduce the install costs of projects and improve the control, visibility, and trust in the EPC (engineering, procurement, and construction) process.

The adoption of a data-centric approach also improves visibility and control from capital project phase to plant start-up. EPCs can spend less time on design rework and delivery is more likely to be on schedule and on budget.

Digital twins in the optimisation phase

As digital twins’ model real-time operations, users can manage the gap between the status and objectives. With access to real-time, historical, and modelled data, users gain a deep understanding of operating conditions. Furthermore, future behaviour can be predicted, preventing unplanned downtime and production losses.

AI can also give insight into improvement opportunities such as minimising waste, reducing energy consumption, and improving production efficiency, enabling manufacturers to confidently meet their sustainability KPIs.

Digital twins in the expansion phase

Digital twins offer important insight into facility planning and design. For example, by simulating the layout and functionality of new facilities, it allows manufacturing companies to refine designs and workflows, mitigating the risk of costly errors, before construction begins.

Also, as manufacturers grow, integrating new processes and equipment into existing system can be quite challenging. Here, digital twins provide detailed insights into how expansions will fit within the current infrastructure. This ensures that growth happens seamlessly, avoiding disruptions to ongoing operations.

Efficient resource management is another advantage of digital twins. With access to real-time data on resource usage and availability, companies can make informed decisions about how to allocate resources effectively during expansions.

Finally, digital twins play a pivotal role in risk mitigation. By simulating various expansion scenarios, digital twins help identify potential risks and bottlenecks before it becomes an issue.

Manufacturers can use this information to address challenges proactively, reducing the likelihood of unexpected problems during the expansion process.

At Schneider Electric our EcoStruxure Machine Expert Twin is a scalable digital twin software solution designed to manage the entire machine lifecycle. This software allows original equipment manufacturers (OEMs) to create digital models of real machines, enabling virtual design and commissioning before physical construction.

Furthermore, AVEVA, owned by Schneider Electric, offers comprehensive digital twin solutions that integrate data from engineering and operations to create a unified digital representation of industrial assets. The AVEVA CONNECT platform combines AI applications and visualisation tools to provide a holistic view of the asset lifecycle.

ENDS

About Schneider Electric

Schneider’s purpose is to create Impact by empowering all to make the most of our energy and resources, bridging progress and sustainability for all. At Schneider, we call this Life Is On.

Our mission is to be the trusted partner in Sustainability and Efficiency.

We are a global industrial technology leader bringing world-leading expertise in electrification, automation and digitization to smart industries, resilient infrastructure, future-proof data centers, intelligent buildings, and intuitive homes. Anchored by our deep domain expertise, we provide integrated end-to-end lifecycle AI enabled Industrial IoT solutions with connected products, automation, software, and services, delivering digital twins to enable profitable growth for our customers.

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