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A Multi-layer Approach for the Identification and Evaluation of Collaborative Robotic Workplaces Within Industrial Production Plants

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Design Tools and Methods in Industrial Engineering (ADM 2019)

Abstract

Collaborative robotic solutions, where humans and robots share a common workspace performing tasks concurrently without physical safety barriers dividing them, are entering the 4.0 manufacturing market. Some proven and tested use cases of Human-Robot Collaboration have been implemented, but their identification process is often just based on the intuition of planning engineers. The purpose of this work is to propose a systematic approach for the identification of potential collaborative workstations within an industrial production plant. In order to do this a multi-layer modelling approach was used and enriched. The multi-layer approach defines the overall goal of the industrial process, the sub-processes that made it possible, the activity models that enables a flow of activities and, finally, a set of methods to carry out the activities. A morphological box of methods that can be used to achieve the specific goal of identifying suitable collaborative workplaces in an industrial plant, through a process of HRC potential analysis is, therefore, ready to be deeply investigated and used.

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Acknowledgements

The present work was developed with the economic support of MIUR (Italian Ministry of University and Research) performing the activities of the project ARS01_00861 “Integrated collaborative systems for smart factory - ICOSAF”.

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Correspondence to Stanislao Patalano .

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Vitolo, F., Pasquariello, A., Patalano, S., Gerbino, S. (2020). A Multi-layer Approach for the Identification and Evaluation of Collaborative Robotic Workplaces Within Industrial Production Plants. In: Rizzi, C., Andrisano, A.O., Leali, F., Gherardini, F., Pini, F., Vergnano, A. (eds) Design Tools and Methods in Industrial Engineering. ADM 2019. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-31154-4_61

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  • DOI: https://doi.org/10.1007/978-3-030-31154-4_61

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