Towards Advancing Translators’ Guidance for Organisations Tackling Innovation Challenges in Manufacturing within an Industry 5.0 Context

Author:

Noeske Paul-Ludwig Michael1ORCID,Simperler Alexandra2ORCID,Leite Cavalcanti Welchy1ORCID,Beber Vinicius Carrillo1ORCID,Alliott Tasmin3,Schiffels Peter1,Goldbeck Gerhard2ORCID

Affiliation:

1. Fraunhofer Institute for Manufacturing Technology and Advanced Materials IFAM, 28359 Bremen, Germany

2. Goldbeck Consulting Limited, Cambridge CB4 0WS, UK

3. Composites Evolution Limited, Lincoln LN6 7YT, UK

Abstract

Following the vision of the European Commission, organisations and workers establishing Industry 5.0 approaches aspire to more future-proof, resilient, sustainable, and human-centred European industries. In this contribution, we explore how technological innovations that contribute to a “win–win” interaction with involved stakeholders may be advanced in a human-centred and transparent proceeding supported by impartial expert translators who provide information or knowledge-based guidance for decision-makers, initiators and implementers in manufacturing innovation driven by sustainability. We elaborate a stepwise procedure for agreeing on milestones and conjointly treading the path towards solving innovation challenges during a translation process. We exemplify the technological aspects of such a process using an innovation case aiming at identifying parameters for enhancements in a vacuum-bagging process applied to the manufacturing of composite parts from prepregs based on condensation-curing matrix resins made from renewable resources. In detail, we present a straightforward design of an experimental approach varying the dwelling temperature and the temperature ramps during the curing of stacked prepregs. In this way, we demonstrate that for cured composites comprising a poly(furfuryl alcohol)-based matrix, the porosity and connected mechanical properties achieved with autoclave-free curing processes sensitively depend on these process parameters. Applying the resulting data-based model is shown to support decision-making for sustainable composite manufacture.

Funder

European Union‘s Horizon 2020 research and innovation programme

Publisher

MDPI AG

Reference80 articles.

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