Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 13-16 |
| Seitenumfang | 4 |
| Fachzeitschrift | CIRP annals |
| Jahrgang | 69 |
| Ausgabenummer | 1 |
| Frühes Online-Datum | 18 Mai 2020 |
| Publikationsstatus | Veröffentlicht - 2020 |
Abstract
With human-robot collaborations, companies are struggling to decide how to schedule tasks in an effective way. We propose an approach to find an eligible division of tasks that forgoes expert knowledge and simulations. Based on a recreation of the application using predefined basic processes and knowledge of the process constraints, the human and robot capabilities are examined. In addition, a time assumption inspired by the Methods-Time Measurement is carried out, to determine the subprocess times. Subsequently, a genetic algorithm assigns the tasks to the human and robot. Expert evaluation and real implementation prove the effectiveness of the proposed approach.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Maschinenbau
- Ingenieurwesen (insg.)
- Wirtschaftsingenieurwesen und Fertigungstechnik
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in: CIRP annals, Jahrgang 69, Nr. 1, 2020, S. 13-16.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Task scheduling method for HRC workplaces based on capabilities and execution time assumptions for robots
AU - Raatz, Annika
AU - Blankemeyer, Sebastian
AU - Recker, Tobias
AU - Pischke, Dennis
AU - Nyhuis, Peter
N1 - Funding Information: This research and development project “SafeMate” was funded by the German Federal Ministry of Education and Research ( BMBF ) within the “Innovations for Tomorrow's Production, Services, and Work” Program ( 02P15A080 ) and implemented by the Project Management Agency Karlsruhe (PTKA). The authors are responsible for the content of this publication.
PY - 2020
Y1 - 2020
N2 - With human-robot collaborations, companies are struggling to decide how to schedule tasks in an effective way. We propose an approach to find an eligible division of tasks that forgoes expert knowledge and simulations. Based on a recreation of the application using predefined basic processes and knowledge of the process constraints, the human and robot capabilities are examined. In addition, a time assumption inspired by the Methods-Time Measurement is carried out, to determine the subprocess times. Subsequently, a genetic algorithm assigns the tasks to the human and robot. Expert evaluation and real implementation prove the effectiveness of the proposed approach.
AB - With human-robot collaborations, companies are struggling to decide how to schedule tasks in an effective way. We propose an approach to find an eligible division of tasks that forgoes expert knowledge and simulations. Based on a recreation of the application using predefined basic processes and knowledge of the process constraints, the human and robot capabilities are examined. In addition, a time assumption inspired by the Methods-Time Measurement is carried out, to determine the subprocess times. Subsequently, a genetic algorithm assigns the tasks to the human and robot. Expert evaluation and real implementation prove the effectiveness of the proposed approach.
KW - Assembly
KW - Human-robot collaboration
KW - Scheduling
UR - http://www.scopus.com/inward/record.url?scp=85084668712&partnerID=8YFLogxK
U2 - 10.1016/j.cirp.2020.04.030
DO - 10.1016/j.cirp.2020.04.030
M3 - Article
AN - SCOPUS:85084668712
VL - 69
SP - 13
EP - 16
JO - CIRP annals
JF - CIRP annals
SN - 0007-8506
IS - 1
ER -