Human factors integration is definitely a transdisciplinary and urgent matter in modern factories. Despite the great surge in factory automation in recent years, human-machine interaction is still a crucial aspect and companies need to take care of the workers' wellbeing and performance to enhance the overall system quality and productivity. Nevertheless, ergonomics is poorly considered during the design of complex industrial systems, such as automatic machinery, especially for the lack of practical methodologies and guidelines to promote human factors from the early stages of design or redesign. To overcome this issue, this work proposes a transdisciplinary approach to redesign automatic machinery in compliance with factory ergonomics, using a combination of digital technologies (e.g., digital human simulation, human physiological data monitoring). The paper defines a structure method and related tools to apply a human-centric approach to industrial cases and their validation of a real case, concerning the redesign of a packaging automatic machine. Results show how the proposed approach is useful to detect possible ergonomic issues at the shop floor, identifying in advance risky situations for the operators during operating or maintenance tasks, and leading to an optimized machine able to enhance the workers’ wellbeing and factory productivity at the same time.

Digital Technologies to Redesign Automatic Machines with a Human-Centric Approach: Application in Industry / Grandi, Fabio; Peruzzini, Margherita; Khamaisi, Riccardo Karim; Lettori, Jacopo; Pellicciari, Marcello. - 28:(2022), pp. 390-399. ((Intervento presentato al convegno 29th International Society of Transdisciplinary Engineering (ISTE) Global Conference tenutosi a Cambridge, MA, USA nel 5-8 July, 2022 [10.3233/ATDE220668].

Digital Technologies to Redesign Automatic Machines with a Human-Centric Approach: Application in Industry

Grandi, Fabio;Peruzzini, Margherita;Khamaisi, Riccardo Karim;Lettori, Jacopo;Pellicciari, Marcello
2022-01-01

Abstract

Human factors integration is definitely a transdisciplinary and urgent matter in modern factories. Despite the great surge in factory automation in recent years, human-machine interaction is still a crucial aspect and companies need to take care of the workers' wellbeing and performance to enhance the overall system quality and productivity. Nevertheless, ergonomics is poorly considered during the design of complex industrial systems, such as automatic machinery, especially for the lack of practical methodologies and guidelines to promote human factors from the early stages of design or redesign. To overcome this issue, this work proposes a transdisciplinary approach to redesign automatic machinery in compliance with factory ergonomics, using a combination of digital technologies (e.g., digital human simulation, human physiological data monitoring). The paper defines a structure method and related tools to apply a human-centric approach to industrial cases and their validation of a real case, concerning the redesign of a packaging automatic machine. Results show how the proposed approach is useful to detect possible ergonomic issues at the shop floor, identifying in advance risky situations for the operators during operating or maintenance tasks, and leading to an optimized machine able to enhance the workers’ wellbeing and factory productivity at the same time.
29th International Society of Transdisciplinary Engineering (ISTE) Global Conference
Cambridge, MA, USA
5-8 July, 2022
28
390
399
Grandi, Fabio; Peruzzini, Margherita; Khamaisi, Riccardo Karim; Lettori, Jacopo; Pellicciari, Marcello
Digital Technologies to Redesign Automatic Machines with a Human-Centric Approach: Application in Industry / Grandi, Fabio; Peruzzini, Margherita; Khamaisi, Riccardo Karim; Lettori, Jacopo; Pellicciari, Marcello. - 28:(2022), pp. 390-399. ((Intervento presentato al convegno 29th International Society of Transdisciplinary Engineering (ISTE) Global Conference tenutosi a Cambridge, MA, USA nel 5-8 July, 2022 [10.3233/ATDE220668].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1291384
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