Despite the trend of automation of industrial tasks given by the huge technological advancements and the large possibilities they offer, still many tasks require a series of skills such as flexibility, dexterity and judgment that cannot be automated and performed by machines. The human is still essential in the modern industry and, for many tasks, cannot be outperformed and replaced by robots. Additionally, the new paradigms of Industry 5.0 (I5.0) endorsed by the EU which, integrating the paradigms of the well known Industry 4.0 (I4.0), aim to emphasize the role of industry’s contribution to society pushing towards a human-centered approach in the design and management of industrial systems. According to the EU and to the I5.0 principles, the humans are put in the center of the decision-making process and the new technologies have to support them and be adapted to their diversities and needs. Concerning the physical support of the operators, new physical support wearable devices called exoskeletons made their appearance in the last years attracting the attention of both academics and practitioners. These devices demonstrated their ability to reduce the biomechanical stress of the wearer both by reducing the muscular demand and the compression forces on the skeletal system in a variety of tasks. Active and passive exoskeletons exist. This classification is based on the technology they adopt to provide the supportive energy with the passive ones being less complex and more economic making them the ideal candidate for large industrial utilization. Despite their proven ability to reduce musculoskeletal stress in various tasks it remains unclear how they affect industrial processes by an operations management point of view. Literature studies did not investigate their joint impact on time performance, posture and the subjective feedback given by the users. Moreover, the placebo effect, which is always present when a human interacts with a device or a treatment, was not investigated in literature studies. Since the application and the benefits of adopting exoskeletons are highly task specific and logistics tasks are the ones with a high priority on optimization in industrial management, the focus of this work is to investigate their application in logistics systems and, in particular, on order picking. These tasks, according to the literature, are well supported by back support exoskeletons. Further, given that passive devices are the best candidates for large industrial deployment, the ones on the scope of this thesis will be the passive back support exoskeletons. The aim of this work is to assess if and how these devices influence picking task and then, to build a decision support system linking physiology and operations management to guide decisions on their deployment.

Applicabilità di esoscheletri passivi nei sistemi logistici

ASHTA, GJULIO
2025

Abstract

Despite the trend of automation of industrial tasks given by the huge technological advancements and the large possibilities they offer, still many tasks require a series of skills such as flexibility, dexterity and judgment that cannot be automated and performed by machines. The human is still essential in the modern industry and, for many tasks, cannot be outperformed and replaced by robots. Additionally, the new paradigms of Industry 5.0 (I5.0) endorsed by the EU which, integrating the paradigms of the well known Industry 4.0 (I4.0), aim to emphasize the role of industry’s contribution to society pushing towards a human-centered approach in the design and management of industrial systems. According to the EU and to the I5.0 principles, the humans are put in the center of the decision-making process and the new technologies have to support them and be adapted to their diversities and needs. Concerning the physical support of the operators, new physical support wearable devices called exoskeletons made their appearance in the last years attracting the attention of both academics and practitioners. These devices demonstrated their ability to reduce the biomechanical stress of the wearer both by reducing the muscular demand and the compression forces on the skeletal system in a variety of tasks. Active and passive exoskeletons exist. This classification is based on the technology they adopt to provide the supportive energy with the passive ones being less complex and more economic making them the ideal candidate for large industrial utilization. Despite their proven ability to reduce musculoskeletal stress in various tasks it remains unclear how they affect industrial processes by an operations management point of view. Literature studies did not investigate their joint impact on time performance, posture and the subjective feedback given by the users. Moreover, the placebo effect, which is always present when a human interacts with a device or a treatment, was not investigated in literature studies. Since the application and the benefits of adopting exoskeletons are highly task specific and logistics tasks are the ones with a high priority on optimization in industrial management, the focus of this work is to investigate their application in logistics systems and, in particular, on order picking. These tasks, according to the literature, are well supported by back support exoskeletons. Further, given that passive devices are the best candidates for large industrial deployment, the ones on the scope of this thesis will be the passive back support exoskeletons. The aim of this work is to assess if and how these devices influence picking task and then, to build a decision support system linking physiology and operations management to guide decisions on their deployment.
14-feb-2025
Inglese
PERSONA, ALESSANDRO
Università degli studi di Padova
File in questo prodotto:
File Dimensione Formato  
tesi_definitiva_Gjulio_Ashta.pdf

embargo fino al 14/02/2028

Dimensione 4.3 MB
Formato Adobe PDF
4.3 MB Adobe PDF

I documenti in UNITESI sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/208370
Il codice NBN di questa tesi è URN:NBN:IT:UNIPD-208370