EDNA

Edge data economy in the sustainable automated manufacturing industry

The EDNA project is developing solutions aimed at the ecological and economic optimisation of industrial production and logistics. To achieve this goal, edge and cloud computing are specifically deployed and combined with AI methods and digital twins. Based on the production of truck trailers as an example, EDNA is designing and testing models and software that reduce the CO2 emissions associated with production, including from those from direct suppliers in the value creation network. The solutions are intended to increase the operational reliability and flexibility of production processes, along with their efficiency. One component specifically designed for this purpose is the Sustainability Dashboard, which has also been developed as part of the project. This dashboard visualises key indicators on the sustainability of production.

Market perspectives and product claims
EDNA is testing the solutions developed in the project under realistic conditions at sites of the KRONE Group. The immediate objectives are to address cost pressures in the commercial vehicle industry and secure the viability of the locations in Emsland together with the associated workforce in the long term. With these objectives in mind, the processes are optimised in terms of their CO2 emissions with the help of AI analyses and energy-efficient edge computing. At the same time, EDNA also enables seamless documentation of CO2 footprints along the entire value chain.
This approach fulfils a key requirement for the implementation of sustainability strategies in companies. To operate sustainably, companies require transparency not only about the environmental impact of their processes and products, but also transparency about the effectiveness of their sustainability measures. All development within the project is based on open standards and norms, thus allowing easy transferability to comparable cases.

Challenge and innovation
Sustainability strategies in companies often stall at the planning level, due to a lack of opportunities to put the strategy into practice. This is where EDNA's Sustainability Dashboard comes into play. Based on a digital twin, i.e. a digital representation of the value creation network, it enables the production status to be displayed transparently at any point during production. Edge computing provides data via interfaces and allows flexible networking within production using modular production plug-ins. The dashboard visualises key indicators on the efficiency and sustainability of production and supplier logistics. EDNA has thus created a data-based tool that companies can use to operationalise their sustainability strategy.
Companies on the path to sustainability can use the Sustainability Dashboard to raise awareness and understanding of sustainability measures. It can also be deployed to introduce environmentally friendly practices, optimise processes sustainably, and secure competitive advantages through sustainable innovations. In this way, EDNA’s solutions help optimise business models sustainably. The solutions take account not only of in-house production, but also the value creation network with direct suppliers.

Use cases
EDNA employs digital methods such as digital twins and artificial intelligence in conjunction with edge and cloud data spaces in order to optimise the economic and ecological sustainability of business models. The project demonstrates this approach with three use cases.
In the first use case, internal production and coating processes are optimised. This use case focuses on automated welding processes for large components, which consume high levels of resources not only in production but also in storage processes and handling. Based on decentrally recorded and processed operating data, the sustainability and efficiency of the production process are optimised using AI technologies.
In the second use case, sustainability optimisation is extended within the supply chain to include the suppliers' inter-company logistics. This optimisation, in the context of logistics processes, includes route optimisation, asset optimisation (type, payload, load volume, consumption, etc.) and intelligent equipment selection depending on the intended use, handling, weight and load volume. As part of a transnational cooperative effort, the Austrian Virtual Vehicle research centre is conducting a study on the driving style in inter-company logistics in this context.
The third use case maps the CO2 footprint of the production of a dry freight semi-trailer. Economic viability is ensured by a model of the business area that is optimised in terms of both cost and energy efficiency (CO2 footprint).
For each use case, solutions are developed that can be applied to comparable use cases.

Consortium
KRONE Business Center GmbH (consortium leader), Jade Hochschule Wilhelmshaven Oldenburg Elsfleth, Osnabrück University of Applied Sciences, OFFIS e.V., Virtual Vehicle GmbH (Austria)

Benefits