Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/18501
Title: Framework of modular industrial workstations for neuroergonomics experiments in a collaborative environment
Authors: Caiazzo, Carlo
Savković, Marija
Djapan, Marko
Vukicevic, Arso
Jovicic, Milos
Macuzic, Ivan
Issue Date: 2022
Abstract: Modern organizations aim to improve key economic parameters (productivity, effectiveness) in order to be competitive in global market. Furthermore, contemporary organizations strive to improve the health and safety of workers. One of the possible solutions to achieve that goal is to modernise production processes through the integration of lean principles and innovative technologies of Industry 4.0. However, in many monotonous and repetitive assembly operations, it is not possible to implement full digitalization. The focus of this research paper is to propose a modular human-robot workstation where the operator and collaborative robot share activities to improve workplace safety and worker's performance. The proposed modular assembly workstation, integrated with a poka-yoke system, is designed in accordance with the individual characteristics of the operator. Authors plan in future periods to conduct researches on this workstation in the field of neuroergonomics using an innovative electroencephalogram system (EEG) during assembly tasks with collaborative robot to prove that it will improve the physical, cognitive and organizational ergonomics and, at the same time, increase productivity and effectiveness.
URI: https://scidar.kg.ac.rs/handle/123456789/18501
Type: conferenceObject
DOI: 10.3850/981-973-0000-00-0_esrel2022-paper
Appears in Collections:Faculty of Engineering, Kragujevac

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