Summary
- Closed for EoI
- Profile Type
- Technology request
- POD Reference
- TRNL20241125023
- Term of Validity
- 4 December 2024 - 4 December 2025
- Company's Country
- Netherlands
- Type of partnership
- Research and development cooperation agreement
- Targeted Countries
- All countries
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General information
- Short Summary
- A Dutch SME aims to develop a digital twin software solution for the manufacturing industry to calculate, monitor, and predict carbon emissions. Seeking collaboration with R&D institutions or universities specializing in carbon emission calculation methodologies and sustainability. The SME seeks domain experts to implement their digital twin and AI solution. They are interested in research cooperation agreements and exploring grants or local funding opportunities to support this initiative.
- Full Description
-
A Dutch SME is embarking on the development of an innovative digital twin software solution aimed at the manufacturing industry. The goal is to create a tool that can calculate, monitor, and predict carbon emissions throughout manufacturing processes. This software will leverage artificial intelligence and advanced modeling techniques to provide real-time analysis and forecasting of carbon footprints.
The SME recognizes the complexity of accurately modeling carbon emissions within manufacturing environments, which involve numerous variables and dynamic processes. Therefore, they are seeking collaboration with R&D institutions or universities that possess expertise in carbon emission calculation methodologies, environmental modeling, and sustainability practices.
The collaboration aims to achieve the following objectives:
- Develop Robust Carbon Emission Models: Create accurate calculation methodologies suitable for integration into the digital twin software, considering all aspects of manufacturing processes, including energy consumption, material usage, and waste generation.
- Integrate Domain Expertise into AI Algorithms: Enhance the predictive capabilities of the solution by incorporating domain-specific knowledge and physics-informed neural networks into the AI models.
- Validate and Calibrate Models: Use real-world data to ensure the reliability and accuracy of the digital twin models, enabling precise monitoring and forecasting of carbon emissions.
- Promote Sustainability Practices: Provide manufacturers with actionable insights to reduce their carbon footprints, optimize processes, and comply with environmental regulations.
- Secure Funding Opportunities: Explore and apply for grants or local funding to support the research and development efforts, leveraging the partner's experience in funding applications.
The SME is particularly interested in domain experts who can contribute specialized knowledge in carbon accounting, life cycle assessment (LCA), and environmental impact analysis within manufacturing settings. The envisioned software will not only measure current emissions but also predict future emissions under various scenarios, supporting manufacturers in their sustainability initiatives and decision-making processes. - Advantages and Innovations
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The proposed digital twin solution represents an innovative approach to sustainability in the manufacturing industry. By integrating advanced AI models with real-time data from manufacturing processes, the software can accurately calculate, monitor, and predict carbon emissions. The use of physics-informed neural networks allows the incorporation of physical laws and domain-specific knowledge into the AI algorithms, enhancing the accuracy and reliability of predictions.
This solution provides several advantages:
- Real-Time Monitoring and Prediction: Enables manufacturers to track their carbon emissions in real-time and predict future emissions under various operational scenarios.
- Process Optimization: Identifies areas where carbon emissions can be reduced, leading to more efficient and sustainable manufacturing processes.
- Regulatory Compliance: Assists companies in meeting environmental regulations by providing accurate reporting and compliance tools.
- Cost Savings: By optimizing processes and reducing emissions, companies can achieve cost savings through improved efficiency and potential incentives for lower carbon footprints.
- Competitive Advantage: Demonstrates a commitment to sustainability, enhancing the company's reputation and appeal to environmentally conscious customers and stakeholders.
The innovation lies in the combination of digital twin technology with advanced AI models enhanced by domain expertise in carbon emissions. This integrated approach allows for a more precise and actionable understanding of environmental impacts in manufacturing. - Stage of Development
- Under development
- Sustainable Development Goals
- Goal 12: Responsible Consumption and Production
- Goal 11: Sustainable Cities and Communities
- Goal 9: Industry, Innovation and Infrastructure
- IPR description
-
The SME seeks R&D institutions, universities, or research organizations with expertise in carbon emission calculation methodologies and environmental modeling within manufacturing settings. The ideal partner should have extensive knowledge in calculating carbon emissions specific to manufacturing processes, including both direct and indirect emissions.
They should possess experience in developing customized carbon footprint models that can be integrated into digital twin and AI solutions. Familiarity with methods such as physics-informed neural networks and the ability to embed domain-specific knowledge into AI algorithms are essential.
The partner should be capable of working closely with the SME's development team, providing technical input on modeling, algorithm design, and system integration. They should assist in validating and calibrating the models using real-world data to ensure accuracy and reliability.
In terms of collaboration, the SME is looking for a research cooperation agreement. They are interested in partners who can contribute expertise rather than products or services for sale. Offers that focus solely on generic carbon accounting software without customization or integration capabilities would not be suitable.
As for financial aspects, the SME anticipates a collaborative research arrangement and is open to discussing cost-sharing models or joint funding applications. Specific prices or quantities are not applicable, as the focus is on expertise and collaboration rather than procurement of goods.
Partner Sought
- Expected Role of a Partner
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The partner is expected to contribute their domain expertise in carbon emission calculations to develop robust and accurate models for integration into the digital twin software. They will work closely with the SME's development team, providing technical guidance on modeling, algorithm design, and integration of domain knowledge into AI models. Additionally, the partner will assist in validating and calibrating the models using real-world data, ensuring the solution's reliability and accuracy.
Furthermore, the partner will provide insights into best practices for sustainability and help identify key areas where carbon emissions can be reduced. They will support the SME in exploring and applying for grants or local funding opportunities, leveraging their experience in funding applications and project management. Through training and knowledge transfer, they will help build the SME's internal capabilities in sustainability efforts and carbon emission analysis.
Offers that provide this specialized expertise and are willing to engage in a collaborative research partnership are sought. Offers that do not provide the necessary domain expertise or are not open to collaborative development would not be suitable - Type and Size of Partner
- University
- R&D Institution
- Type of partnership
- Research and development cooperation agreement
Dissemination
- Technology keywords
- 02003005 - Information processing & Systems, Workflow
- 01003023 - Environmental and Biometrics Sensors, Actuators
- 01003025 - Internet of Things
- 01003005 - Computer Hardware
- Market keywords
- 02007022 - Software services
- 02007016 - Artificial intelligence related software
- 08002001 - Energy management
- 02007014 - Other industry specific software
- Sector Groups Involved
- Digital
- Targeted countries
- All countries