In the paradigm of smart factories, flexible and scalable manufacturing resources are essential. The human worker offers great flexibility; however, the operators are often a sparse resource in high-wage countries. Consequently, they are often responsible for several tasks at once and must prioritise the most critical ones. Consequently, the productivity on less critical tasks will suffer in the absence of the operator. In this paper, we present a case study on the effect on productivity when deploying a collaborative robot assistant in a plug and produce fashion to substitute a human worker at manual workstations on a production line. Realistic cycle and changeover times are derived from physical experiments and used in discrete event simulation to analyse two scenarios. The results show that if an operator must abandon his/her workstation, deploying a robot assistant as a substitute reduces the loss of productivity.


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    Titel :

    A Case Study of Plug and Produce Robot Assistants for Hybrid Manufacturing Workstations



    Erscheinungsdatum :

    2022-01-01


    Anmerkungen:

    Hjorth , S , Schou , C , Ribeiro da Silva , E , Tryggvason , F , Sparre Sørensen , M & Forbech , H 2022 , A Case Study of Plug and Produce Robot Assistants for Hybrid Manufacturing Workstations . in A-L Andersen , R Andersen , T D Brunoe , M S S Larsen , K Nielsen , A Napoleone & S Kjeldgaard (eds) , Towards Sustainable Customization : Bridging Smart Products and Manufacturing Systems - Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference CARV 2021 and 10th World Mass Customization and Personalization Conference MCPC 2021 . Springer , Lecture Notes in Mechanical Engineering , pp. 242-249 , 8th Changeable, Agile, Reconfigurable and Virtual Production Conference, CARV 2021 and 10th World Mass Customization and Personalization Conference, MCPC 2021 , Aalborg , Denmark , 01/11/2021 . https://doi.org/10.1007/978-3-030-90700-6_27



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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