Hard material small-batch industrial machining robot

Alberto Brunete (Corresponding Author), Ernesto Gambao (Corresponding Author), Jukka Koskinen, Tapio Heikkilä, Knut Berg Kaldestad, Ilya Tyapin, Geir Hovland, Dragoljub Surdilovic, Miguel Hernando, Aldo Bottero, Stefan Anton

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)

Abstract

Hard materials can be cost effectively machined with standard industrial robots by enhancing current state-of-the-art technologies. It is demonstrated that even hard metals with specific robotics-optimised novel hard-metal tools can be machined by standard industrial robots with an improved position-control approach and enhanced compliance-control functions. It also shows that the novel strategies to compensate for elastic robot errors, based on models and advanced control, as well as the utilisation of new affordable sensors and human-machine interfaces, can considerably improve the robot performance and applicability of robots in machining tasks. In conjunction with the development of safe robots for human-robot collaboration and cooperation, the results of this paper provide a solid background for establishing industrial robots for industrial-machining applications in both small- and medium-size enterprises and large industry. The planned short-term and long-term exploitation of the results should significantly increase the future robot usage in the machining operations.
Original languageEnglish
Pages (from-to)185-199
Number of pages15
JournalRobotics and Computer-Integrated Manufacturing
Volume54
DOIs
Publication statusPublished - 1 Dec 2018
MoE publication typeA1 Journal article-refereed

Fingerprint

Machining
Batch
Robot
Robots
Industrial Robot
Industrial robots
Metals
Compliance control
Human-machine Interface
Small and Medium-sized Enterprises
Position Control
Control Function
Position control
Compliance
Exploitation
Robotics
Industry
Sensor
Sensors
Costs

Keywords

  • Compliance control
  • HMI
  • Industrial
  • Machining
  • Path planning
  • Robot
  • Small-batch

Cite this

Brunete, A., Gambao, E., Koskinen, J., Heikkilä, T., Kaldestad, K. B., Tyapin, I., ... Anton, S. (2018). Hard material small-batch industrial machining robot. Robotics and Computer-Integrated Manufacturing, 54, 185-199. https://doi.org/10.1016/j.rcim.2017.11.004
Brunete, Alberto ; Gambao, Ernesto ; Koskinen, Jukka ; Heikkilä, Tapio ; Kaldestad, Knut Berg ; Tyapin, Ilya ; Hovland, Geir ; Surdilovic, Dragoljub ; Hernando, Miguel ; Bottero, Aldo ; Anton, Stefan. / Hard material small-batch industrial machining robot. In: Robotics and Computer-Integrated Manufacturing. 2018 ; Vol. 54. pp. 185-199.
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Brunete, A, Gambao, E, Koskinen, J, Heikkilä, T, Kaldestad, KB, Tyapin, I, Hovland, G, Surdilovic, D, Hernando, M, Bottero, A & Anton, S 2018, 'Hard material small-batch industrial machining robot', Robotics and Computer-Integrated Manufacturing, vol. 54, pp. 185-199. https://doi.org/10.1016/j.rcim.2017.11.004

Hard material small-batch industrial machining robot. / Brunete, Alberto (Corresponding Author); Gambao, Ernesto (Corresponding Author); Koskinen, Jukka; Heikkilä, Tapio; Kaldestad, Knut Berg; Tyapin, Ilya; Hovland, Geir; Surdilovic, Dragoljub; Hernando, Miguel; Bottero, Aldo; Anton, Stefan.

In: Robotics and Computer-Integrated Manufacturing, Vol. 54, 01.12.2018, p. 185-199.

Research output: Contribution to journalArticleScientificpeer-review

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T1 - Hard material small-batch industrial machining robot

AU - Brunete, Alberto

AU - Gambao, Ernesto

AU - Koskinen, Jukka

AU - Heikkilä, Tapio

AU - Kaldestad, Knut Berg

AU - Tyapin, Ilya

AU - Hovland, Geir

AU - Surdilovic, Dragoljub

AU - Hernando, Miguel

AU - Bottero, Aldo

AU - Anton, Stefan

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PY - 2018/12/1

Y1 - 2018/12/1

N2 - Hard materials can be cost effectively machined with standard industrial robots by enhancing current state-of-the-art technologies. It is demonstrated that even hard metals with specific robotics-optimised novel hard-metal tools can be machined by standard industrial robots with an improved position-control approach and enhanced compliance-control functions. It also shows that the novel strategies to compensate for elastic robot errors, based on models and advanced control, as well as the utilisation of new affordable sensors and human-machine interfaces, can considerably improve the robot performance and applicability of robots in machining tasks. In conjunction with the development of safe robots for human-robot collaboration and cooperation, the results of this paper provide a solid background for establishing industrial robots for industrial-machining applications in both small- and medium-size enterprises and large industry. The planned short-term and long-term exploitation of the results should significantly increase the future robot usage in the machining operations.

AB - Hard materials can be cost effectively machined with standard industrial robots by enhancing current state-of-the-art technologies. It is demonstrated that even hard metals with specific robotics-optimised novel hard-metal tools can be machined by standard industrial robots with an improved position-control approach and enhanced compliance-control functions. It also shows that the novel strategies to compensate for elastic robot errors, based on models and advanced control, as well as the utilisation of new affordable sensors and human-machine interfaces, can considerably improve the robot performance and applicability of robots in machining tasks. In conjunction with the development of safe robots for human-robot collaboration and cooperation, the results of this paper provide a solid background for establishing industrial robots for industrial-machining applications in both small- and medium-size enterprises and large industry. The planned short-term and long-term exploitation of the results should significantly increase the future robot usage in the machining operations.

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KW - HMI

KW - Industrial

KW - Machining

KW - Path planning

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