08.07.2026

Preparing Factory Data for the IMX Ecosystem

The International Manufacturing-X initiative has created a new way of approaching industrial data spaces by making them a model for collaboration across manufacturing value chains. This idea can be a game changer. However, it depends on whether each participant can provide reliable, well-described, and governed data.

IMX Enables Global Industrial Collaboration

The International Manufacturing-X Council (IMXC) promotes a federated approach to industrial data sharing, where instead of exchanging information within the constraints of a centralized platform, manufacturers, suppliers, technology providers, and customers keep control over their data. It is their decision what can be shared, with whom, and for what purpose [1][2].

This approach aligns with how manufacturing already works. Products move through suppliers, plants, logistics partners, and service organizations before they reach the customer. In the course of that journey, information regarding quality, materials, production history, maintenance, energy use, or carbon footprint may be required to accompany the product. For this reason, IMX provides a framework for trusted and interoperable exchange across that network [1][2].

Factory-Level Data Readiness Is Important for a Reason

A company’s data space can define the way it collaborates. However, it does not improve the quality of the information contributed by its participants. In most cases, the gaps for manufacturers still lie within the plant. Different systems and departments collect data separately, creating disconnected sources, where preparing a report, review, or compliance file might require a manual information check [3].

This problem can become especially prominent when data needs to leave the constraints of the company to be shared outside. Missing traceability, inconsistent identifiers, manual corrections without a clear history, or machine signals with no process context reduce confidence in the dataset before it even reaches the partner. Therefore, a trusted ecosystem first needs trusted factory data.

The Factory as a Node in a Global Data Ecosystem

Manufacturers should change their approach to data exchange and move from treating it like a technical interface added at the edge of the company to treating it like an operating capability. Before production data can become part of a wider ecosystem, a factory needs to understand what it owns, where the information comes from, how reliable it is, and under which conditions it may be shared.

At this point, data sovereignty shows its significance, as it depends on clear ownership, governance rules, quality standards, and controlled access to production information [2].

Experience from MES (Manufacturing Execution System) environments, machine connectivity, traceability, and industrial data integration shows that external collaboration depends on the quality of information collected inside the plant. A connector alone cannot compensate for missing context, inconsistent identifiers, or poorly governed datasets.

From Raw Machine Data to Industrial Data Products

Raw machine signals usually hold little value outside the equipment or line that generated them. A cycle time, alarm code, or temperature reading can only be useful when linked to a machine, product, batch, timestamp, and process state.

Turning these records into reusable industrial data products requires metadata, traceability, governance, and business context. FAIR principles describe this direction by stating that data should be findable, accessible, interoperable, and usable [4].

An MES can provide the missing context by connecting production events with orders, materials, and operations. Quality systems add verification, while maintenance systems contribute equipment history. Combined, they create information that can travel beyond the production site and still be understood.

Use Cases Enabled by IMX Collaboration

Reliable production data creates use cases within the value chain.

Supplier quality transparency becomes easier when manufacturers exchange structured quality indicators instead of static reports.
Customers can receive verified product and production information faster.
Technology providers can support diagnostics, maintenance, and process optimization on the basis of agreed datasets.
Predictive maintenance benefits from data collected across equipment fleets.
Manufacturers keep control over sensitive operational information.
Product carbon footprint calculations become more consistent because every participant contributes verified production data [5].

Another example is the Digital Product Passport (DPP). They require structured information gathered throughout the product lifecycle [5]. A practical example of how to exchange data within the DPP was displayed in a demonstrator.

During Hannover Messe 2026, explitia participated in a Manufacturing-X Digital Battery Passport demonstrator as the assembly node representing the Polish ecosystem, collaborating with partners across the globe. The project showed how standardized production data can move between independent organizations while remaining secure, traceable, and aligned with future European Digital Product Passport requirements.

The same foundation can support cross-site benchmarking and AI models trained on broader industrial datasets without giving up data sovereignty.

Recommendations for Manufacturers

Trying to cover every dataset from the start might not be optimal. A more sensible first step would be a business case where reliable production data is already essential, such as supplier quality, traceability, downtime analysis, energy reporting, or product carbon footprint data.

From there, manufacturers can strengthen the shopfloor data foundation:

An MES should connect production events with orders, materials, and operations.
Product and batch identifiers should stay consistent across systems.
Important datasets need owners, quality rules, and access conditions.

It is vital for IT and OT teams to build this foundation together. Production teams understand machines and process limits, while IT can provide integration, cybersecurity, and governance.

Interoperability should be a long-term capability, not just a one-time integration project. Manufacturers investing in structured, trustworthy production data will be ready to join an IMX-type collaboration without having to rebuild data exchange for every new customer, supplier, or regulatory requirement.