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A Smart Work Cell to Reduce Adoption Barriers of Collaborative Robotics

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Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures (APMS 2023)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 689))

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Abstract

Investment costs and lack of knowledge are often cited as barriers to adopting collaborative robots, especially for smaller businesses with limited budgets. Cobots demand specialised knowledge and skills not only for their installation and programming but also for effectively maintaining and adapting them to accommodate various product types. This paper presents a smart work cell solution using a collaborative robot to meet production requirements while overcoming the obstacles associated with small batch sizes and a wide range of product types. The solution provides simple and guided procedures for quick parameterization and setup, targeting non-expert users. A SME producing hand tweezers has applied and tested the proposed solution. The work also demonstrates the applicability of collaborative robots to high-dexterity tasks such as belt grinding and polishing.

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Notes

  1. 1.

    The focus of this work is on the welding, grinding, and polishing work cell. Despite the high yearly demand for tweezers passing through these processes, the cobot saturation currently stands at only 40-60%. Therefore, new applications in other work cells will soon be deployed to fully utilise the cobot’s potential. However, these new applications are beyond the scope of this work and will not be described herein.

References

  1. Aaltonen, I., Salmi, T.: Experiences and expectations of collaborative robots in industry and academia: barriers and development needs. Procedia Manufact. 38, 1151–1158 (2019). https://doi.org/10.1016/j.promfg.2020.01.204

    Article  Google Scholar 

  2. Abdous, M.A., Delorme, X., Battini, D., Sgarbossa, F., Berger-Douce, S.: Assembly line balancing problem with ergonomics: a new fatigue and recovery model. Int. J. Prod. Res. 61, 1–14 (2022). https://doi.org/10.1080/00207543.2021.2015081

  3. Bettoni, A., et al.: Mutualistic and adaptive human-machine collaboration based on machine learning in an injection moulding manufacturing line. Procedia CIRP 93, 395–400 (2020). https://doi.org/10.1016/j.procir.2020.04.119

    Article  Google Scholar 

  4. Daniele, F., et al.: Collaborative robotics adoption: KITT4SME report 2022 in collaboration with trinity robotics. Tech. Rep., University of Applied Science and Arts of Southern Switzerland (2022). https://doi.org/10.13140/RG.2.2.24439.50081

  5. Fast-Berglund, Å., Romero, D.: Strategies for implementing collaborative robot applications for the operator 4.0. IFIP Adv. Inf. Commun. Technol. 566, 682–689 (2019). https://doi.org/10.1007/978-3-030-30000-5_83

  6. Fritzsche, L., Wegge, J., Schmauder, M., Kliegel, M., Schmidt, K.H.: Good ergonomics and team diversity reduce absenteeism and errors in car manufacturing. Ergonomics 57(2), 148–161 (2014). https://doi.org/10.1080/00140139.2013.875597

    Article  Google Scholar 

  7. Liu, D., Cao, J.: Determinants of collaborative robots innovation adoption in small and medium-sized enterprises: an empirical study in China. Appl. Sci. 12(19), 10085 (2022). https://doi.org/10.3390/app121910085

    Article  Google Scholar 

  8. Montini, E., et al.: A framework for human-aware collaborative robotics systems development. Procedia CIRP (2023)

    Google Scholar 

  9. Niu, Y., Schulte, F.: Human aspects in collaborative order picking – what if robots learned how to give humans a break? In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds.) APMS 2021. IAICT, vol. 632, pp. 541–550. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-85906-0_59

    Chapter  Google Scholar 

  10. Park, J., Sørensen, L.C., Mathiesen, S.F., Schlette, C.: A digital twin-based workspace monitoring system for safe human-robot collaboration. In: 2022 10th International Conference on Control, Mechatronics and Automation (ICCMA), pp. 24–30. IEEE (2022). https://doi.org/10.1109/ICCMA56665.2022.10011622

  11. Raza, M., Malik, A.A., Bilberg, A.: PDCA integrated simulations enable effective deployment of collaborative robots: case of a manufacturing SME. Procedia CIRP 104, 1518–1522 (2021). https://doi.org/10.1016/j.procir.2021.11.256. 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0

  12. Salunkhe, O., Fager, P., Fast-Berglund, Å.: Framework for identifying gripper requirements for collaborative robot applications in manufacturing. In: Lalic, B., Majstorovic, V., Marjanovic, U., von Cieminski, G., Romero, D. (eds.) APMS 2020. IAICT, vol. 591, pp. 655–662. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-57993-7_74

    Chapter  Google Scholar 

  13. Schnell, M., Holm, M.: Challenges for manufacturing SMEs in the introduction of collaborative robots. In: SPS2022: Proceedings of the 10th Swedish Production Symposium, vol. 21, pp. 173–183. IOS Press (2022). https://doi.org/10.3233/ATDE220137

  14. Steinmetz, F., Weitschat, R.: Skill parametrization approaches and skill architecture for human-robot interaction. In: 2016 IEEE International Conference on Automation Science and Engineering (CASE), pp. 280–285. IEEE (2016). https://doi.org/10.1109/COASE.2016.7743419

  15. Xia, G., Li, C., Zhu, Q., Xie, X.: Hybrid force/position control of industrial robotic manipulator based on kalman filter. In: 2016 IEEE International Conference on Mechatronics and Automation, pp. 2070–2075 (2016). https://doi.org/10.1109/ICMA.2016.7558885

  16. Xu, X., Chen, W., Zhu, D., Yan, S., Ding, H.: Hybrid active/passive force control strategy for grinding marks suppression and profile accuracy enhancement in robotic belt grinding of turbine blade. Roboti. Comput.-Integr. Manufact. 67, 102047 (2021). https://doi.org/10.1016/j.rcim.2020.102047

    Article  Google Scholar 

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Acknowledgements

This work was supported by EU’s Horizon 2020 research and innovation program (Grant numbers 825196).

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Authors and Affiliations

  1. Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Lugano, Switzerland

    Elias Montini, Lorenzo Agbomemewa, Fabio Daniele, Vincenzo Cutrona, Matteo Confalonieri, Andrea Ferrario & Andrea Bettoni

  2. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy

    Elias Montini & Paolo Rocco

Authors
  1. Elias Montini
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  2. Lorenzo Agbomemewa
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  3. Fabio Daniele
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  4. Vincenzo Cutrona
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  5. Matteo Confalonieri
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  6. Andrea Ferrario
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  7. Paolo Rocco
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  8. Andrea Bettoni
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Corresponding author

Correspondence to Elias Montini .

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Editors and Affiliations

  1. Norwegian University of Science and Technology, Trondheim, Norway

    Erlend Alfnes

  2. Norwegian University of Science and Technology, Trondheim, Norway

    Anita Romsdal

  3. Norwegian University of Science and Technology, Trondheim, Norway

    Jan Ola Strandhagen

  4. ZF Friedrichshafen AG, Friedrichshafen, Germany

    Gregor von Cieminski

  5. Tecnológico de Monterrey, Mexico City, Mexico

    David Romero

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Montini, E. et al. (2023). A Smart Work Cell to Reduce Adoption Barriers of Collaborative Robotics. In: Alfnes, E., Romsdal, A., Strandhagen, J.O., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. APMS 2023. IFIP Advances in Information and Communication Technology, vol 689. Springer, Cham. https://doi.org/10.1007/978-3-031-43662-8_50

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  • DOI: https://doi.org/10.1007/978-3-031-43662-8_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43661-1

  • Online ISBN: 978-3-031-43662-8

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