Optimizing Production and Logistic Resources in the Time-critical Bio Production Industries in Europe

Projektinformationen

CLARUS

ID Finanzhilfevereinbarung: 101070076

DOI

10.3030/101070076

Projekt abgeschlossen

EK-Unterschriftsdatum 13 Juni 2022

Startdatum 1 September 2022

Enddatum 30 November 2025

Finanziert unter

• Digital, Industry and Space

Gesamtkosten

€ 3 423 230,75

EU-Beitrag

€ 2 999 105,75

Koordiniert durch

POLITECNICO DI MILANO
Italy

Periodic Reporting for period 2 - CLARUS (Optimizing Production and Logistic Resources in the Time-critical Bio Production Industries in Europe)

Berichtszeitraum: 2024-03-01 bis 2025-11-30

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

The CLARUS project aims to connect the sustainable paradigm in the food industry and AI-based applications, with the goal of developing a platform with high communication and processing capabilities, as well as the use of standardized open protocols and data models that allow resource consumption assessment and traceability for food industry processes. To achieve these objectives, CLARUS develops and integrates three main Tangible Expected Outcomes (TEOs):

1. CLARUS Green Deal Index. The Green Deal Index (GDI) translates complex environmental, operational, and digitalization data into a single, interpretable indicator aligned with EU sustainability priorities. Together with the GDI, a Green Deal Ontology (GDO), as novel sustainability ontology for food domain, has been developed in the project.

2. CLARUS Data Space. A key result has been the design and deployment of a secure and interoperable CLARUS Data Space, compliant with International Data Spaces Association (IDSA) principles. The Data Space has evolved from a minimum viable configuration into a reinforced ecosystem including metadata discovery and transaction logging services, ensuring data sovereignty, transparency, and auditability.

3. CLARUS AI Toolkit. In parallel, the CLARUS AI Toolkit has been developed and refined within an MLOps framework to address concrete industrial challenges across the food value chain. AI models have been designed, trained, and validated for predictive maintenance, energy and water consumption forecasting, anomaly detection, logistics optimization, and process optimization.

The CLARUS solution has been validated through two large-scale industrial pilots representing different stages of the food production ecosystem. Together, these pilots demonstrate the applicability and robustness of CLARUS solutions across diverse industrial contexts within the food sector.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

The work performed and the main achievements within the project are the following:

- CLARUS Green Deal Index:
The performed activities included the identification and definition of a quantitative environmental sustainability methodology (and related KPIs) for the environmental sustainability assessment of food manufacturing systems, to be integrated into a unique Green Deal Performance Assessment (GDPA) methodology and a final Green Deal Index (GDI). The GDPA methodology has been defined as quantitative metrics that deliver the final GDI. The main goal has been to finalize and test data-driven metrics for environmental sustainability assessment, efficiency, and manufacturing digital adoption, optimization/minimization of production resources, waste stream, energy consumption within the CLARUS pilots. Moreover, the Green Deal Ontology (GDO), as novel sustainability ontology for food domains and strictly related to the GDI indicator, has been developed.

- CLARUS Ecosystem:
The carried-out activities provided the context for the exploitation and sustainability business modelling through a detailed analysis of the existing market and the business opportunities of CLARUS developments. The conducted market analysis helped to identify and understand competitors’ strengths and weaknesses concerning CLARUS offerings. The performed Opportunity Analysis included an analysis of external factors, identifying legal, political, economic, technological, and societal trends relevant to the developed CLARUS services.

- CLARUS Data Space:
A data-driven industrial platform has been the final goal of the technical effort in CLARUS project building a Data Space for manufacturing, able to improve business opportunities for value-added services relating to the industrial data of the participants involved in the project. The CLARUS Data Space is based on IDSA reference models and architecture (IDS RAM), constituting the standard de facto in European data-sharing landscape. The architecture and operational flow of a secure data-sharing process within an IDSA-compliant Data Space, emphasizing trust, interoperability, and governance.

- CLARUS AI Toolkit:
This toolkit encompasses AI algorithms, trained models, and an MLOps workflow definition. It aligns with the approach proposed in CLARUS Data Space and CLARUS Green Deal Index. For the CLARUS MLOps workflow first the building blocks associated with the MLOps strategy have been identified and state-of-the-art MLOps tools have been analysed. Based on collected requirements a set of edge services have been implemented to cover the entire lifecycle of AI models in the edge to cloud continuum.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

The project has demonstrated significant potential across scientific, economic, and societal dimensions:
• Environmental & Economic Impact: Preliminary results from pilot sites indicate potential annual savings in terms of natural resources consumed in food processes analysed.
• Industrial Competitiveness: By utilizing AI-driven decision support, pilot companies have optimized logistics and production, leading to reduced operational costs and increased competitiveness.
• Scientific Advancement: The project has contributed to the state-of-the-art through peer-reviewed publications and the development of the three TEOs in the food domain and their integration as overall CLARUS solution.

To ensure the long-term success and wider adoption of the CLARUS solutions in other industrial contexts beyond the project, the following needs have been identified:

• Commercialization & Finance: Operationalizing joint exploitation agreements and launching early commercial activities targeting the agri-food sector are critical next steps.
• Market Access: Further tailoring of the business models to meet emerging market demands for secure data spaces and AI-driven decision support.
• Business Model & Economic Sustainability: Design of business model and revenue strategies applicable to AI & data services in the food industry.
• Regulatory & Standardization Framework: Alignment with evolving European regulations on sustainability reporting will be essential for market-ready product rollout.
• IPR & Governance: Finalizing ownership structures and access rights for the integrated CLARUS Solution to facilitate licensing and potential spin-offs.