A framework to design smart manufacturing systems for Industry 5.0 based on the human-automation symbiosis

ABSTRACTThe concept of Industry 5.0 (I5.0) promotes the human-centricity as the core value behind the evolution of smart manufacturing systems (SMSs), based on a novel use of digital technologies in the design and management of modern industrial systems to take up the socio-technical challenges. In this context, the paper proposes a Smart Manufacturing Systems Design (SMSD) framework enabling I5.0, based on the human-automation symbiosis. Thanks to an 'Augmented Digital Twin' (ADT) able to integrate and digitize all the entities of the factory (i.e. machines, robots, environments, interfaces, people), AI-driven applications can be built to support the user domain and make people and machines co-evolve thanks to a systematic data sharing between physical and digital assets (e.g. digital twin, virtual mock-ups, human-machine interfaces), optimizing factory productivity and workers wellbeing. In this framework, machines and humans can both generate knowledge and learn from each other, generating a virtuous co-evolution, supporting the understanding of the human-machine interplay and the creation of an effective collaboration between people and SMSs. The framework was conceived and validated involving four industrial companies, belonging to diverse sectors, interested in overcoming the current limits of I4.0 lines by including the human factors for future SMS management.KEYWORDS: Industry 5.0Operator 4.0Operator 5.0augmented digital twinsmart manufacturing systemshuman-automation symbiosis AcknowledgementsThis research is funded by the European Community under two HORIZON 2020 programmes, grant agreement No. 958303 (PeneloPe) https://penelope-project.eu/ and grant agreement No. 101091780 (DaCapo) https://www.dacapo-project.eu/.Disclosure statementNo potential conflict of interest was reported by the author(s).Correction StatementThis article has been republished with minor changes. These changes do not impact the academic content of the article.Additional informationFundingThe work was supported by the H2020 Industrial Leadership [958303].