Advances in Automatic Feature Inspection with a Robot UR5e Programmed Using Force or Impact Commands

Author:

Peña Cortes Cesar Augusto,Riaño Jaimes Cristhian Ivan,Mejia Bugallo Diego Armando

Publisher

Springer Nature Switzerland

Reference15 articles.

1. Wang, C., Tan, X., Tor, S.B., Lim, C.: Machine learning in additive manufacturing: state-of-the-art and perspectives. Addit. Manuf. 36, 101538 (2020)

2. Sathish, K., et al.: A comparative study on subtractive manufacturing and additive manufacturing. Adv. Mater. Sci. Eng. 1–8, 2022 (2022)

3. Gibson, I., et al.: Additive Manufacturing Technologies, vol. 17. Springer, New York (2021)

4. Tavares, T.M., Ganga, G.M.D., Godinho Filho, M., Rodrigues, V.P.: The benefits and barriers of additive manufacturing for circular economy: a framework proposal. Sustain. Prod. Consum. (2023)

5. Hedberg, T.D., Jr., et al.: Defining requirements for integrating information between design, manufacturing, and inspection. Int. J. Prod. Res. 60(11), 3339–59 (2022)

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