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Evaluation of deterministic models for the excavator's theoretical productivity estimation in the digging and trenching operations

Molaei, Amirmasoud ORCID iD icon 1; Geimer, Marcus ORCID iD icon 1; Kolu, Antti
1 Institut für Fahrzeugsystemtechnik (FAST), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

This paper investigates the automatic theoretical productivity estimation of an excavator in digging and trenching operations. The actual productivity cannot solely reveal the machine's performance since there are various operating conditions that can significantly influence the excavator’s actual productivity. The theoretical productivity estimation is certainly required because it is the highest feasible productivity level and provides a reference to evaluate the actual productivity. In this paper, two of the most pertinent deterministic models to calculate the excavator's theoretical productivity are introduced. Then, the impacts of operating conditions are investigated. Finally, estimated theoretical cycle times are evaluated by comparison with the actual cycle times.


Verlagsausgabe §
DOI: 10.5445/IR/1000162816
Veröffentlicht am 17.10.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Fahrzeugsystemtechnik (FAST)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 10.07.2023
Sprache Englisch
Identifikator ISBN: 978-0-7017-0273-1
ISSN: 2684-1150
KITopen-ID: 1000162816
Erschienen in Proceedings of the 2023 European Conference on Computing in Construction and the 40th International CIB W78 Conference
Veranstaltung European Conference on Computing in Construction and the 40th International CIB W78 Conference (2023), Iraklio, Griechenland, 10.07.2023 – 12.07.2023
Verlag European Council for Computing in Construction (EC3)
Serie Series on Computing in Construction
Projektinformation MORE (EU, H2020, 858101)
Nachgewiesen in Dimensions
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