Project description
Making data analysis software for manufacturing
Big Data can be used to pave the way for new methods of process control and quality assurance in the manufacturing sector. The right tools are needed for this job, however. The EU-funded DBP project will simplify complex production processes by developing a scalable software solution. Specifically, this is an automated data analysis software that enables users to identify hidden correlations in their production process. The consolidated data can be visualised, compared and evaluated. Relationships between input variables and quality features are recognised. With the use of AI algorithms, predictive models can be created. Facilitating proactive intervention can help prevent rejects and machine downtime.
Objective
Started with the first place at the Audi Smart Factory Hackathon and Audi as a first customer, DatenBerg is entering the manufacturing market with its machine-learning software. DatenBerg is driven by its mission: Simplify complex production processes. DatenBerg means “Data Mountain” in German and that is exactly, what it is all about: analyzing “mountains” of data to create valuable input. The company provides a holistic scalable software solution for the manufacturing industry. The automated data-analysis software, called DatenBerg Backpack, enables the customers to identify hidden correlations in their production process.
DatenBerg was founded in February 2018 and is today, mainly focusing on the rubber processing sector. The company is going to launch the beta version of DatenBerg Backpack in March 2019. The team consists of five team members with more than 50 years of experience in the manufacturing industry in total.
During the feasibility study, the first implementations of Backpack in the rubber processing industry will be accompanied and the business plan for the implementation of the software will be further developed.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence
- natural sciences computer and information sciences software software development
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
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H2020-EU.3. - PRIORITY 'Societal challenges
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H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
SME-1 - SME instrument phase 1
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-EIC-SMEInst-2018-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
76131 KARLSRUHE
Germany
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.