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The Implementation Process and Factors that Influence the Quality of the Integration of Collaborative Robots in the Automotive Industry

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Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 472)

Abstract

The automotive manufacturing process has the role of manufacturing the finished products or final assembly of the products intended for vehicles. In automotive, industrial organizations must produce as quickly as possible, at the highest possible quality and at the lowest possible cost in order to continue to secure a competitive place on the market. Due to this requirement, it was necessary to discover certain solutions through which: the manufacturing speed will increase and remain constant during manufacturing, the quality of the manufacturing process will be improved because a qualitative process will always lead to quality products, and manufacturing costs generated during process time to be reduced. These requirements led, in time, to the emergence of collaborative robots. If traditional robots were intended for particular applications, collaborative robots have much greater flexibility. The scientific paper presents, in an elegant manner, the process of integration of collaborative robots and the steps to be followed in order to transform manual processes, old or new, into manufacturing processes with collaborative robots. Certain factors that influence the quality of integration of collaborative robots are presented.

Keywords

  • Collaborative robot
  • Process
  • Automotive
  • Quality
  • Manufacturing

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References

  1. Godina, R., Matias, J.C., Azevedo, S.G.: Quality improvement with statistical process control in the automotive industry. Int. J. Ind. Eng. Manag. 7(1), 1–8 (2016)

    Google Scholar 

  2. Hasta, A., Harwati, H.: Line balancing with reduced number of operator: a productivity improvement. IOP Conf. Ser.: Mater. Sci. Eng. 528(1), 012060 (2019). https://doi.org/10.1088/1757-899X/528/1/012060

    CrossRef  Google Scholar 

  3. Kragic, D., Gustafson, J., Karaoguz, H., Jensfelt, P., Krug, R.: Interactive, collaborative robots: challenges and opportunities. In: IJCAI, pp. 18–25. (2018). https://doi.org/10.24963/ijcai.2018/3

  4. Crosby, P.: Quality is Free. Ed. McGraw-Hill, New York, United States of America (1979)

    Google Scholar 

  5. Bragança, S., Costa, E., Castellucci, I., Arezes, P.M.: A Brief overview of the use of collaborative robots in industry 4.0: human role and safety. In: Arezes, P.M., et al. (eds.) Occupational and Environmental Safety and Health. SSDC, vol. 202, pp. 641–650. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-14730-3_68

    CrossRef  Google Scholar 

  6. Sherwani, F., Asad, M.M., Ibrahim, B.S.K.K.: Collaborative robots and industrial revolution 4.0 (ir 4.0). In: 2020 International Conference on Emerging Trends in Smart Technologies (ICETST), pp. 1–5. IEEE (2020). https://doi.org/10.1109/ICETST49965.2020.9080724

  7. Iqbal, Z., Pozzi, M., Prattichizzo, D., Salvietti, G.: Detachable Robotic Grippers for Human-Robot Collaboration. Front. Robot. AI 8, 644532 (2021). https://doi.org/10.3389/frobt.2021.644532

    CrossRef  Google Scholar 

  8. Bloss, R.: Collaborative robots are rapidly providing major improvements in productivity, safety, programing ease, portability and cost while addressing many new applications. Indus. Robot: An Int. J. 43, 463–468 (2016). https://doi.org/10.1108/IR-05-2016-0148

    CrossRef  Google Scholar 

  9. Pieskä, S., Kaarela, J., Mäkelä, J.: Simulation and programming experiences of collaborative robots for small-scale manufacturing. In: 2018 2nd International Symposium on Small-scale Intelligent Manufacturing Systems (SIMS), pp. 1–4. IEEE (2018). https://doi.org/10.1109/SIMS.2018.8355303

  10. Schou, C., Andersen, R.S., Chrysostomou, D., Bøgh, S., Madsen, O.: Skill-based instruction of collaborative robots in industrial settings. Robot. Comput. Integr. Manuf. 53, 72–80 (2018). https://doi.org/10.1016/j.rcim.2018.03.008

    CrossRef  Google Scholar 

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Correspondence to Aurel Mihail Titu .

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Gusan, V., Titu, A.M. (2022). The Implementation Process and Factors that Influence the Quality of the Integration of Collaborative Robots in the Automotive Industry. In: Karabegović, I., Kovačević, A., Mandžuka, S. (eds) New Technologies, Development and Application V. NT 2022. Lecture Notes in Networks and Systems, vol 472. Springer, Cham. https://doi.org/10.1007/978-3-031-05230-9_5

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