Experiment Description
The purpose of this experiment is the creation of a catalogue of experiments at cross-DIH level performed by DIHs together with the SMEs with which they collaborate. To serve as a paradigm for future inspiration, the catalogue of the realized experiments at cross-DIH level shall include:
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A description of the experiments
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A description of the type of the SMEs with which the experiment has been realized
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A detailed description of the DIHs involved.
Moreover, all SMEs involved in the experimentation should respect the following parameters:
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Registered office/offices
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Size of the company, region, focus of activity, production type
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Stage of digital maturity
Finally, experiments shall be categorized as well using the following criteria:
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Type of experiment: technology, advisory, education, etc.
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Technology supported
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Time framework
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Possibility of subsidy or loan gain
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Other parties involved (i.e., academy, innovation and research centers, infrastructures as Testbeds)
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Other significant information
The catalogue shall be fully compatible with the already existing DIH4AI portal.
List Title
Expected Impact
Through the implementation of this experiment, several real research and innovation results and direct benefits can be presented to the European innovation AI community and this would lead to the active dissemination of good practices within the European DIHs that could bring relevant economies of scale to both DIHs and SMEs.
In addition, by developing such catalogue of cross-DIH experiments, SMEs can also benefit from the following elements:
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Increased development of AI activities in the corporate sector
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Better information gained thanks to a more complete overview of the experiments performed at both national and European level
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Better application of R&D results in new products
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Access to new markets and increased competitiveness thanks to an increased added value of products and to implemented breakthrough innovation
Finally, the key results which are expected to be generated by the experiment can be listed as follows:
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Creating clear record of at least 30 high value-added experiments at cross-DIH level;
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Sharing the results with the industry practice and academy;
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Motivating at least 30 SMEs to boost their innovation performance and the intensity of R&D activities, increasing their involvement in knowledge and technology transfer and cooperation with research organizations;
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Increasing the number of innovation leaders within domestic SMEs, motivation to other experiment in the field of AI technology, faster transition of SMEs to digital technologies, including use of artificial intelligence, robotics, etc;
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Sufficient awareness of technological, organizational and business opportunities for the practical use of digital innovations for their rapid economic growth;
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Finding good practice examples: investment of SMEs in production with higher added value through innovation or technology development and interest in acquiring new technological devices and equipment, including the necessary infrastructure in accordance with the principles of P4.0 resulting in higher productivity and stronger position in value chains;
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Boosting digital and AI skills within SMEs´ employees – experiment can be good source of information for technical stuff and other experts;
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Boosting digital and AI skills by within industrial public – experiments can be good source of information for media.