Stamping line optimization using genetic algorithms and virtual 3D line simulation

Javier A. García-Sedano; Jon Alzola Bernardo; Asier González González; Óscar Berasategui Ruiz De Gauna; Rafael Yuguero González De Mendivil

doi:10.1007/978-3-642-13769-3_39

Stamping line optimization using genetic algorithms and virtual 3D line simulation

Javier A. García-Sedano
, Jon Alzola Bernardo
, Asier González González
, Óscar Berasategui Ruiz De Gauna
, Rafael Yuguero González De Mendivil

Fundación TECNALIA Research & Innovation
Sankyo Desarrollos Técnicos, S.L.

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

6 Citas (Scopus)

1 Descargas (Pure)

Resumen

This paper describes the use of a genetic algorithm (GA) in order to optimize the trajectory followed by industrial robots (IRs) in stamping lines. The objective is to generate valid paths or trajectories without collisions in order to minimize the cycle time required to complete all the operations in an individual stamping cell of the line. A commercial software tool is used to simulate the virtual trajectories and potential collisions, taking into account the specific geometries of the different parts involved: robot arms, columns, dies and manipulators. Then, a genetic algorithm is proposed to optimize trajectories. Both systems, the GA and the simulator, communicate as client - server in order to evaluate solutions proposed by the GA. The novelty of the idea is to consider the geometry of the specific components to adjust robot paths to optimize cycle time in a given stamping cell.

Idioma original	Inglés
Título de la publicación alojada	Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings
Páginas	319-326
Número de páginas	8
Edición	PART 1
DOI	https://doi.org/10.1007/978-3-642-13769-3_39
Estado	Publicada - 2010
Evento	5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010 - San Sebastian, Espana Duración: 23 jun 2010 → 25 jun 2010

Serie de la publicación

Nombre	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Número	PART 1
Volumen	6076 LNAI
ISSN (versión impresa)	0302-9743
ISSN (versión digital)	1611-3349

Conferencia

Conferencia	5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010
País/Territorio	Espana
Ciudad	San Sebastian
Período	23/06/10 → 25/06/10

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 9: Industria, innovación e infraestructura

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10.1007/978-3-642-13769-3_39

Stamping Line OptimizationVersión publicada final, 277 KB

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García-Sedano, J. A., Bernardo, J. A., González, A. G., De Gauna, Ó. B. R., & De Mendivil, R. Y. G. (2010). Stamping line optimization using genetic algorithms and virtual 3D line simulation. En Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings (PART 1 ed., pp. 319-326). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6076 LNAI, N.º PART 1). https://doi.org/10.1007/978-3-642-13769-3_39

García-Sedano, Javier A. ; Bernardo, Jon Alzola ; González, Asier González et al. / Stamping line optimization using genetic algorithms and virtual 3D line simulation. Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings. PART 1. ed. 2010. pp. 319-326 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{3d82ab6ba9454058b3fe93266137afab,

title = "Stamping line optimization using genetic algorithms and virtual 3D line simulation",

abstract = "This paper describes the use of a genetic algorithm (GA) in order to optimize the trajectory followed by industrial robots (IRs) in stamping lines. The objective is to generate valid paths or trajectories without collisions in order to minimize the cycle time required to complete all the operations in an individual stamping cell of the line. A commercial software tool is used to simulate the virtual trajectories and potential collisions, taking into account the specific geometries of the different parts involved: robot arms, columns, dies and manipulators. Then, a genetic algorithm is proposed to optimize trajectories. Both systems, the GA and the simulator, communicate as client - server in order to evaluate solutions proposed by the GA. The novelty of the idea is to consider the geometry of the specific components to adjust robot paths to optimize cycle time in a given stamping cell.",

keywords = "Genetic Algorithm, Off-line Path Planning, Virtual Manufacturing",

author = "Garc{\'i}a-Sedano, \{Javier A.\} and Bernardo, \{Jon Alzola\} and Gonz{\'a}lez, \{Asier Gonz{\'a}lez\} and \{De Gauna\}, \{{\'O}scar Berasategui Ruiz\} and \{De Mendivil\}, \{Rafael Yuguero Gonz{\'a}lez\}",

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doi = "10.1007/978-3-642-13769-3\_39",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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García-Sedano, JA, Bernardo, JA, González, AG, De Gauna, ÓBR & De Mendivil, RYG 2010, Stamping line optimization using genetic algorithms and virtual 3D line simulation. En Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings. PART 1 ed., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), n.º PART 1, vol. 6076 LNAI, pp. 319-326, 5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010, San Sebastian, Espana, 23/06/10. https://doi.org/10.1007/978-3-642-13769-3_39

Stamping line optimization using genetic algorithms and virtual 3D line simulation. / García-Sedano, Javier A.; Bernardo, Jon Alzola; González, Asier González et al.
Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings. PART 1. ed. 2010. p. 319-326 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6076 LNAI, N.º PART 1).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Stamping line optimization using genetic algorithms and virtual 3D line simulation

AU - García-Sedano, Javier A.

AU - Bernardo, Jon Alzola

AU - González, Asier González

AU - De Gauna, Óscar Berasategui Ruiz

AU - De Mendivil, Rafael Yuguero González

PY - 2010

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N2 - This paper describes the use of a genetic algorithm (GA) in order to optimize the trajectory followed by industrial robots (IRs) in stamping lines. The objective is to generate valid paths or trajectories without collisions in order to minimize the cycle time required to complete all the operations in an individual stamping cell of the line. A commercial software tool is used to simulate the virtual trajectories and potential collisions, taking into account the specific geometries of the different parts involved: robot arms, columns, dies and manipulators. Then, a genetic algorithm is proposed to optimize trajectories. Both systems, the GA and the simulator, communicate as client - server in order to evaluate solutions proposed by the GA. The novelty of the idea is to consider the geometry of the specific components to adjust robot paths to optimize cycle time in a given stamping cell.

AB - This paper describes the use of a genetic algorithm (GA) in order to optimize the trajectory followed by industrial robots (IRs) in stamping lines. The objective is to generate valid paths or trajectories without collisions in order to minimize the cycle time required to complete all the operations in an individual stamping cell of the line. A commercial software tool is used to simulate the virtual trajectories and potential collisions, taking into account the specific geometries of the different parts involved: robot arms, columns, dies and manipulators. Then, a genetic algorithm is proposed to optimize trajectories. Both systems, the GA and the simulator, communicate as client - server in order to evaluate solutions proposed by the GA. The novelty of the idea is to consider the geometry of the specific components to adjust robot paths to optimize cycle time in a given stamping cell.

KW - Genetic Algorithm

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SN - 9783642137686

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Y2 - 23 June 2010 through 25 June 2010

ER -

García-Sedano JA, Bernardo JA, González AG, De Gauna ÓBR, De Mendivil RYG. Stamping line optimization using genetic algorithms and virtual 3D line simulation. En Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings. PART 1 ed. 2010. p. 319-326. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-13769-3_39

Stamping line optimization using genetic algorithms and virtual 3D line simulation

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