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Making our Workforce Fit for the Factory of the Future

Project description

Training for competitive European manufacturing

The increased globalisation in manufacturing, new technologies, automation and AI has transformed the demands of the labour markets. With expected automation in physical work estimated at 33 %, 22 % in data collection and 11 % in data processing, Europe must urgently confront present difficulties to address its future skills needs to ensure competitiveness. The EU-funded FIT4FoF project aims to help the European workforce obtain skills to fit the Factories of the Future. It will analyse present workers’ needs and technological trends in six industrial areas, like robotics, additive manufacturing, and data analytics, to inform and promote new education and training requirements across European regions.

Objective

Increased introduction of digital technologies into manufacturing is leading to increased automation. Estimates indicate that the potential for automation in predictable physical work is at 33% followed by 22% in data collection and 11% in data processing. The increased globalisation in manufacturing also introduces requirements in terms of team work, intercultural and language capabilities, the need to deal with shorter production cycles, and changes in demographics requiring workers to stay active for longer. Europe faces considerable challenges in addressing future skills needs. From the perspective of the workforce the issues are increasingly complex where current training and educational solutions are discrete and lack interconnections and are largely dissociated from work activities. Growing gaps in knowledge and know-how make it increasingly challenging to adapt, work proactively and contribute to innovations. FIT4FoF aims at addressing a range of these issues by analysing current skills initiatives, better to understand how to address workers' needs, analysing technology trends across 6 industrial areas of robotics, additive manufacturing, mechatronics/machine automation, data analytics, cybersecurity and human machine interaction, to define new job profiles, which will inform education and training requirements. FIT4FoF will develop a new education and training framework, which places workers (women and men) at the centre of a co-design and development process that recognises and addresses their skills needs. By applying educational approaches based on Communities of Practice, FIT4FoF will empower workers to be drivers of the design, development and delivery of their own upskilling programmes. FIT4FoF will develop Alliances of Communities of Practice to broaden the approach across Europe, creating replication strategies enabling educational/training design and development practices to be transferred between regional communities across Europe.

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Keywords

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Programme(s)

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Topic(s)

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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.

CSA - Coordination and support action

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-NMBP-TR-IND-2018-2020

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Coordinator

MUNSTER TECHNOLOGICAL UNIVERSITY
Net EU contribution

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.

€ 368 250,00
Address
ROSSA AVENUE BISHOPSTOWN
T12 P928 Cork
Ireland

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Region
Ireland Southern South-West
Activity type
Higher or Secondary Education Establishments
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Total cost

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.

€ 368 250,00

Participants (8)

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