Physical and mental well‐being of cobot workers: A scoping review using the Software‐Hardware‐Environment‐Liveware‐Liveware‐Organization model. Issue 5 (11th April 2022)

• Record Type: Journal Article
• Authors: Storm, Fabio A.; Chiappini, Mattia; Dei, Carla; Piazza, Caterina; André, Elisabeth; Reißner, Nadine; Brdar, Ingrid; Delle Fave, Antonella; Gebhard, Patrick; Malosio, Matteo; Peña Fernández, Alberto; Štefok, Snježana; Reni, Gianluigi
• Is Part Of: Human factors and ergonomics in manufacturing and service industries. Volume 32:Issue 5(2022)
• Page Start: 419
• Page End: 435
• Publication Date: 2022-04-11
• Subjects: cobots -- health and well‐being -- human robot collaboration -- SHELLO model -- sociotechnical systems; Computer integrated manufacturing systems -- Periodicals; Human engineering -- Periodicals; 620.8205
• DOI: 10.1002/hfm.20952
• Languages: English
• ISSNs: 1090-8471

Abstract

Abstract: The present scoping review investigated the current state of the art concerning factors affecting physical and mental health and well‐being of workers using collaborative robots (cobots) in manufacturing industries. Each identified factor was classified using the SHELLO (Software‐Hardware‐Environment‐Liveware‐Liveware‐Organization) conceptual model. Strengths and limitations of such an approach were outlined. A total of 53 papers were included in the scoping review and analyzed following PRISMA guidelines. In 35 papers at least one risk factor referred to the SHELLO Liveware‐Hardware interaction, followed by factors concerning Liveware‐Software (16 papers), Liveware‐Liveware (11 papers), Liveware intrinsic factor (10 papers), Liveware‐Organization (8 papers), and Liveware‐Environment (8 papers). This work highlighted that methodological research is still primarily focused on traditional risk assessment and physical safety. However, several research directions concerning the design of cobots as active collaborators were identified, promoting workers' mental health and well‐being, too. The SHELLO model proved to effectively highlight human factors relevant for the design of cobots and can provide a systemic approach to investigate human factors in other complex sociotechnical systems. To the best of our knowledge, this is the first time the model is applied in the field of human–cobot interaction.