There is plenty of data from development, production, and service, but rarely a clear answer to how sustainably a system actually operates. This is precisely where the it's OWL EcoTwin project comes in. It demonstrates how a "Digital Green Twin" is created, linking technical conditions with environmental and resource data, thus revealing where energy, materials, and CO₂ can be specifically saved during operation. All the key findings and tips are now summarized in a report.

When we talk about the Twin Transition, we're referring to a dual challenge: companies are expected to digitize their processes while simultaneously operating more sustainably. EcoTwin addresses precisely this challenge, translating it into a concrete approach. The project links data from development, production, and operations to create a coherent picture.

The final report summarizes the findings in an application-oriented guide. It outlines, in three steps, how companies can build a digital green twin. The scope ranges from sustainability goals and drivers, through stakeholder benefits and relevant key performance indicators, to technical implementation. This ensures that organizational and technical issues are seamlessly integrated, rather than running parallel.

Download the final report for free

You can download the complete final report for the it's OWL project EcoTwin free of charge from the project page on the it's OWL innovation platform. The download is only visible to registered and logged-in users.

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Three steps: From sustainability goal to data architecture

The first step clarifies the purpose of the Digital Green Twin. Is it about documenting CO₂ emissions, saving energy, closing material cycles, or fulfilling new reporting obligations? Once these drivers are identified, it becomes much easier to determine which data is truly important.

In the second step, the focus shifts to the people who will later work with the virtual twin. Who should benefit from the new insights: production, development, service, sales, or the sustainability department? Each group asks different questions and needs different key performance indicators (KPIs). EcoTwin helps to organize these perspectives and derive concrete use cases. This transforms the abstract "We need more data" into a clear picture: Who needs which information for which decision?

Only in the third step does the focus shift to the technical aspects. This involves defining which sources will be connected, how data will flow together, and which architecture is suitable. The guide provides a structure that leads companies step by step from their target vision to a feasible solution, without getting bogged down in technical details.

How the Digital Green Twin works technically

Technically, EcoTwin demonstrates that scalable architectures for digital green twins can now be implemented in industrial environments. Sensors and programmable logic controllers (PLCs) at the plant itself record the relevant operating parameters. Middleware based on Node-RED, an open graphical environment for processing data streams, standardizes this data and distributes it to the connected systems.

To securely transfer data to the cloud, EcoTwin uses the Azure IoT Hub, an online interface specifically designed for machine connectivity. This creates a digital twin of the machine within Azure Digital Twins. The structures within the twin are described using the Digital Twins Definition Language (DTDL). DTDL functions as a formal description language that allows components, sensors, and relationships within the system to be recorded in a machine-readable format. This results in a networked twin graph—a digital model containing the elements of the system and their relationships.

This model incorporates not only data points but also real-time events. A 3D scene and interactive diagrams further visualize the plant's condition. A dashboard based on Grafana, a data visualization platform, supports data-driven evaluation of consumption and plant status. Managers can see at a glance how the plant is performing and where potential improvements in efficiency and sustainability lie.

Digital product passport: 148 data points for reference

A second focus of EcoTwin is the Digital Product Passport (DPP). A Digital Product Passport can be understood as a digital profile of a product. It accompanies a product throughout its entire life cycle and contains information on materials, components, repair options, and disposal. Future EU regulations, such as those related to the EU Battery Directive, will make such passports mandatory for many products.

Companies are thus faced with two key questions: What data belongs in such a product passport? And how do I implement it technically? EcoTwin addresses precisely these questions. The project provides an information list with 148 potential data points as a reference. This list shows what information companies can collect regarding resource use, components, and usage in order to later populate the product passport.

The Digital Product Passport (DPP) is not just a concept in the project, but is already technically integrated. EcoTwin demonstrates the prototypical integration as a separate twin in the Twin Graph. This DPP twin is linked to the actual plant. It draws on static product data, for example, from development and ERP systems. Live operational data from the plant also flows in. Based on this, companies can create transparency, meet regulatory requirements, and develop new data-driven services throughout a product's lifecycle.

Practical pilot project at Herbert Kannegiesser: Laundry plant as a digital twin

The pilot project at Herbert Kannegiesser GmbH demonstrates how this works in practice. The company operates industrial-scale laundry facilities. In the project, a real plant was implemented as a digital twin. It has a real-time representation of operations, analytics, and decision-making logic that goes beyond mere monitoring.

Instead of simply displaying measured values, the Digital Twin supports the evaluation of conditions and consumption. Those responsible can see how changes in operations affect the process and where potential efficiency gains lie. This makes the Digital Green Twin a tool that supports day-to-day decisions in a production plant.

Transferability to other machines and ecosystems

EcoTwin is not limited to a single example. The chosen architecture can, in principle, be applied to other machines and processes. Digital twins based on standardized descriptions create a common language between manufacturers, suppliers, and customers. This opens up perspectives for an interoperable ecosystem in which data becomes the connecting element.

For companies, this means they can no longer consider sustainability, digitalization, and regulatory requirements separately. A digital green twin, like EcoTwin, connects these topics. It clarifies which data is relevant, how it can be technically linked, and how this leads to concrete decisions in day-to-day operations.



The article " Mastering Twin Transition: Three Steps to a Digital Green Twin" first appeared on it's OWL .