Nov 16, 2022
European Production Giganet — EuProGigant
How the GEN-X network and Gaia-X help to create a resilient, sustainable, and data-sovereign Industry 4.0
Last week, we published our first use case blog post, which highlighted how the GEN-X network for Gaia-X, powered by Polygon, can be leveraged to enable technical data-sovereign mobility applications on the edge.
Today, we would like to introduce the EuProGigant Portal and our joint web3-based industry 4.0 ecosystem, which we created together with the Austrian-German Gaia-X lighthouse project EuProGigant. The portal was shown for the first time at the HANNOVER MESSE 2022, where data from connected manufacturing machines at different locations have been made available in a decentralized, secure and privacy-preserving way. This made the Austrian-German Gaia-X Lighthouse Project the first Gaia-X lighthouse project to use the Gaia-X Web 3 Ecosystem.
From Hannover to Vienna and the Gaia-X Summit 2022 in Paris
In this spirit, our successful cooperation continued and EuProGigant contributed one of the first GEN-X validators, to enable a federated, interoperable and autonomous ecosystem for the industry 4.0 on the road towards production and Gaia-X compliance.
This use case spotlight will take a closer look at various use cases enabled by the EuProGigant portal and the GEN-X network, and provide an overview of EuProGigant and the ambitious goals we want to achieve together in the context of Gaia-X.
This week, from November 16–17, EuProGigant and the use cases described below, running on the Pan-European GEN-X network, will be featured and displayed live at the Gaia-X Summit 2022 in Paris.
What is the European Production Giganet?
EuProGigant is a research project carried out by an Austrian-German project consortium which aims to build a multi-location, digitally connected manufacturing ecosystem.
This ecosystem shows how value for customers and manufacturing firms can be created through the added value based on the practical implementation of smart and sovereign use of data. This empowers European industry and supports its contribution to the sustainable development of Europe. The project “European Production Giganet for calamity-avoiding self-orchestration of value chain and learning ecosystems” (EuProGigant) is the first financially supported industrial project with practical implementation of Gaia-X principles and should illustrate the technological and economical use of the open, European multi-cloud infrastructure Gaia-X. Within the framework of the EuProGigant project will be demonstrated how a highly connected manufacturing set-up can be equipped with self-orchestrating and stabilizing characteristics. Thanks to sovereign data and information exchange within a shared data ecosystem, a sustainable and resilient manufacturing is realized.
The Goals
- …the identification, extraction, and organization of production-relevant data;
2. … increasing flexibility and efficiency in production through the processing of production data (e.g., energy demand and consumption);
3. … ensuring reliability and availability of production data;
4. … the mapping of cross-border value chains.
Who drives EuProGigant?
The development, execution, and scaling of such a complex project cannot be managed by one company alone. Therefore, 16 project partners are actively involved in EuProGigant: eight large companies, four SMEs, and four scientific partners.
The partners develop and test the domain-specific demonstrator for the Gaia-X “Industry 4.0 / SME“ domain and are involved in research and technology transfer.
The Vision
The vision of EuProGigant is to create a new type of interaction in both value creation and learning ecosystems. This will enable resilient, data-driven and sustainable production to regain and strengthen European leadership in the manufacturing industry.
“In our view, digitalization enables us to solve cross-generational challenges, such as resource conservation, sustainable development, and the energy transition. This is because digitalization in data exchange facilities the holistic consideration of product and plant life cycles throughout the process.“ — Markus Weber, Project Lead, PTW TU Darmstadt
The project seeks to contribute to a Europe in which companies work together collaboratively and consensually based on shared European values and legal views across national borders. The industrial ecosystem is characterized by the self-organization of participants, data, and services (= self-orchestration) to mitigate threats from crisis situations (= calamity avoiding).
To achieve this, companies will operate within increasingly decentralised production infrastructures. In the case of computing resources this will be reflected in the free choice of storage location, access rights and partnerships. Where production takes place and where data is processed and stored is completely transparent. The prerequisites for this are the above-mentioned values, primarily the Gaia-X principles of trust and transparency, interoperability, and data sovereignty. By constantly using data, albeit for a fee, companies can adapt much better to new situations, share knowledge and thus also access solutions themselves that have worked for others. The infrastructure also opens opportunities for new business models with high value creation along the entire data value chain in parallel to the production value chains: Offering own resources such as data, smart services and ideas as digital sales assets creates an additional pillar for one’s own company besides the usual product offering. Such a broad positioning makes it easier for companies to adapt to market changes — they become faster, more adaptable, and more resilient.
You can read more about this in the Conference on Production Systems and Logistics (CPSL) publication “Developing Gaia-X Business Models For Production” and the CIRP Conference on Manufacturing Systems publication “EuProGigant Resilience Approach: A Concept for Strengthening Resilience in the Manufacturing Industry on the Shop Floor”.
What is being developed and powered by the GEN-X network?
During EuProGigant’s research mission, several potential uses, and benefits of Distributed Ledger Technologies (DLT) were identified, which ultimately led to the development of the EuProGigant portal with deltaDAO and Ocean Protocol. The need for decentralization, interoperability, and resilience as well as the realization of the added value of blockchain and DLT convinced EuProGigant to be one of the initial supporters of the GEN-X network using Polygon’s Supernets technology.
In the following we will present three different use cases that can already be discovered and consumed today in the Gaia-X Web3 ecosystem:
- Use Case 1: “Component Matching”
- Use Case 2 “CO2 footprint in production engineering and manufacturing”
- Use Case 3 “EuProGigant Validation Platform”
We cluster these use cases around two focus topics.
Focus topics: Sustainability and responsible use of artificial intelligence
“In EuProGigant we work wisely with the data, so much so that we contribute to the UN’s Sustainable Development Goals.” Markus Weber, PTW TU Darmstadt
This is how EuProGigant promotes resource efficiency:
- Machines are used optimally at full capacity, increasing productivity. More parts can then be produced with existing resources. The greater output of pieces per unit of time reduces the energy required per piece, energy savings are therefore achieved per piece.
- Thanks to data exchange, the best possible material selection is made. The right parameters for machines or production can be found for the material selection. In the future, materials with the lowest carbon footprint will be selected in the product design process, in process planning and in the parameter settings of the machine.
- Necessary resources — material, energy, and personnel — will be saved as testbeds will be shared in the future.
Use case 1: Component Matching
Machine parts are usually produced at multiple companies, which means that there can be size deviations in the produced parts. All producers should adhere to certain tolerances for their produced parts, to make sure that these parts can be matched. In practice, however, parts often deviate from these tolerances leading to extra work to adapt these parts, more inventory or even waste.
We aim to make tolerances fluent. With a digital platform for component matching, search efforts for product assembly will be minimised and higher productivity can be achieved. It can also pave the way towards zero-waste and zero-defect manufacturing and paperless production. Furthermore, it allows for standardised and automated information transfer and reporting.
In this use case the produced parts will be precisely measured right after the manufacturing process and the data will be made available for use further down the value chain. This helps to orchestrate more efficient production processes, reduce waste and energy usage in the form of overproduction and to create better products.
You can find an example of the component matching data here on the EuProGigant Portal and a more detailed description on the EuProGigant website.
Use Case 2: CO2-Footprint
Companies that want to stay competitive in the future will have to consider sustainability measures. The manufacturing process offers
Holding clamps were manufactured in different materials, such as aluminium or plastic, and produced using different processes, such as 3d printing, metal cutting or injection moulding. Using compute-to-edge, we demonstrate CO2-equivalent (CO2e) emission reporting per manufactured part. Companies will be able to publish their data sets and algorithms securely on the Portal.
This is how EuProGigant promotes the responsible use of Artificial Intelligence to create value:
- Disturbance control, risk prevention: configuration of the hardware systems so that they can self-orchestrate in the future. The system recognizes which disturbance is having an effect, how the ecosystem is reacting to the disturbance, and what needs to be done so that the disturbance does not have this effect. Parameters must be set for this. AI helps to decide the appropriate parameters for computer units in the software. The software can be in edge hardware, in the surrounding environment of the machine or even in the cloud.
- Long-term data processing / Big Data processing: even in 50 years’ time, it should still be possible to extract information from the stored data (large volumes of data) according to search terms (AI searches for results in the right context).
- Intelligent functions for data flow control (= where does the data flow).
The use of artificial intelligence in machine tools continues to grow. The benefits of data-driven manufacturing are also growing with the availability of Big Data. This is supported by the European Commissions’ European data strategy, which indicates an estimated 530 % increase in data volume by 2025. Artificial intelligence is seen as a future key technology for correctly interpreting the growing volume of data and recognizing correlations. Great potential lies particularly in the applications of predictive analytics, intelligent assistance systems, robotics, intelligent automation, and intelligent sensor technology.
Compute-to-Edge completes the edge-to-cloud continuum.
However, there is a great deal of concern about the intellectual property of manufacturing companies, which is why there is still reluctance to share production data.
To relieve companies of this worry, deltaDAO has integrated Ocean Protocol’s data access mechanism Compute-to-Data (CtD) into the Gaia-X Web3 ecosystem and the EuProGigant Portal. As one of the cornerstones for data sovereignty, privacy, and compliance, CtD empowers data owners to grant compute-only access to their data without having to create copies in other environments they do not control.
Today, however, production data is often no longer processed in the cloud, but directly on the machine, i.e., the edge, to improve response times and save bandwidth. To take full advantage of edge computing, we have combined the paradigm with CtD, forming Compute-to-Edge (CtE). Using CtE, collected data can stay on the manufacturing machine controlled or selected by the data owner. Just like using CtD, whitelisted algorithms are brought to the data, so privacy-preserving compute jobs can take place in the data owners’ edge environment. As a result, the data footprint is reduced, as unnecessary replication, transport, and storage of data are being avoided. CtE opens new doors for data usage and monetization of data across companies and industries with vast benefits in terms of compliance, cost savings, and data control. In the following, another use case that leverages CtE is presented.
Use Case 3: Validation Platform
The data volumes required for condition monitoring present small and medium-sized enterprises (SMEs) with numerous challenges — they often do not have the needed number of identical machines to generate sufficient operating data, or the capabilities to analyse existing data.
The validation platform enables service creation based on data sets from different machine tools across company borders. The platform is part of the Gaia-X Web3 ecosystem and ensures secure and technical data sovereign data exchange between production companies. As such, the validation platform functions as a commonly accepted and verifiable source for information validation. The validation platform puts condition monitoring of manufacturing processes in focus and shows how SMEs can collaborate in creating the necessary database.
The first use case of the validation platform is the pragmatic implementation of predictive maintenance on a HELLER CNC ProfiTrainer machine. This use case was successfully debuted at HANNOVER MESSE 2022, after which it has been demonstrated at numerous other events and trade fairs.
The HELLER CNC ProfiTrainer mills components and subsequently publishes the real production parameters on the EuProGigant portal. However, the data itself remains with the machine, i.e., on the edge. Using Compute-to-Edge, an algorithm is executed on the production data, which analyses the condition of the components used for milling. The algorithm uses this data to assess whether the tool needs to be changed and to assess the quality of the produced workpiece. This result can be purchased in the EuProGigant portal.
The use case shows how tool suppliers can change their tool in a timely and efficient manner without the component manufacturers having to reveal the intellectual property of their manufacturing process. The GEN-X network, powered by Polygon, validates transactions, and ensures that portal participants, in this case component manufacturers and tool suppliers, can publish and consume data in a decentralized, secure, and resilient manner, while the network remains interoperable with other Web3 ecosystems and participants adhere to the rules of the network.
Examples for the validation platform can be found in the Federated Catalogue, accessible through the EuProGigant Portal.
If you want to see the process in detail, we recommend the Hannover Messe Explainer video.
The Activities
EuProGigant focuses on optimizing the speed and flexibility of value creation through the implementation of the technical architecture of a data ecosystem according to Gaia-X. A high-frequency data collection by means of, open-source-based, cost-effective solutions in combination with a process-oriented aggregation of the collected data should offer a high incentive for new users. In addition, easy, self-configurable connectivity between the infrastructure ecosystem and the data ecosystem should accelerate the speed of value creation.
EuProGigant demonstrates data continuity in the manufacturing ecosystem through standardized vertical integration from the machine to the plant management level as well as further horizontal linkages across different business units and even company and country boundaries. The project shows how different actors, stakeholders and companies can access data, achieving a common benefit by working together. It does this by creating interfaces, showing how the building blocks of the system (computing units, measuring devices, software, Gaia-X Federation Services) need to be used and implementing this in models for which different use cases have been devised. By analyzing the contributing factors and their effects on our value creation and learning ecosystem, disruptive factors are identified and software and hardware-based solutions for stable systems are developed.
EuProGigant and Gaia-X — the new data infrastructure for Europe and beyond Europe
Gaia-X is a European initiative to build a common, secure and sovereign data infrastructure for Europe based on the principles of trust and transparency. Gaia-X is the first opportunity to apply European standards for the secure and sovereign use of data in manufacturing. Gaia-X is paving the way for resilient value creation and learning ecosystems because it provides tools on how to design a virtual marketplace that is independent, overarching and secure.
For EuProGigant, Gaia-X is a multiplier initiative for the dissemination of proven, industry-ready services for energy monitoring, energy data-based analysis of industrial processes and the estimation of CO2 emissions. Thanks to the Gaia-X principles, a virtual economic space is being created that is neutral in terms of platform. It will promote the dissemination of smart services and thus contribute to the European Commission’s climate policy goals and the Green Deal.
We thank EuProGigant for the fantastic cooperation and for the preparation of the extensive content and use case descriptions. If you want to learn more about the European Production Giganet — EuProGigant, please visit https://euprogigant.com/en/.
