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

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

1 Downloads (Pure)

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.

Original language	English
Title of host publication	Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings
Pages	319-326
Number of pages	8
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-13769-3_39
Publication status	Published - 2010
Event	5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010 - San Sebastian, Spain Duration: 23 Jun 2010 → 25 Jun 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	6076 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010
Country/Territory	Spain
City	San Sebastian
Period	23/06/10 → 25/06/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Genetic Algorithm
Off-line Path Planning
Virtual Manufacturing

Access to Document

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

Stamping Line OptimizationFinal published version, 277 KB

Cite this

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. In 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, No. 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\}",

year = "2010",

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

language = "English",

isbn = "3642137687",

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

number = "PART 1",

pages = "319--326",

booktitle = "Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings",

edition = "PART 1",

note = "5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010 ; Conference date: 23-06-2010 Through 25-06-2010",

}

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. in Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 6076 LNAI, pp. 319-326, 5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010, San Sebastian, Spain, 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, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

Y1 - 2010

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

KW - Off-line Path Planning

KW - Virtual Manufacturing

UR - https://www.scopus.com/pages/publications/77954570794

U2 - 10.1007/978-3-642-13769-3_39

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

M3 - Conference contribution

AN - SCOPUS:77954570794

SN - 3642137687

SN - 9783642137686

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

SP - 319

EP - 326

BT - Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings

T2 - 5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010

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. In 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

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this