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https://doi.org/10.2478/otmcj-2023-0007

Comparative assessment of deterministic methodologies for estimating excavation productivity

Antonios Panas ; National Technical University of Athens: Ethniko Metsobio Polytechneio Athens, Greece *
John-Paris Pantouvakis ; National Technical University of Athens: Ethniko Metsobio Polytechneio Athens, Greece
Maria Kalogiannaki ; Hellenic Open University

* Dopisni autor.


Puni tekst: engleski pdf 1.534 Kb

str. 63-78

preuzimanja: 23

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Sažetak

This paper investigates the prediction capability
of deterministic methodologies in estimating construction
productivity for earthmoving operations. Published literature includes several estimation methodologies stemming
from (a) equipment manufacturers’ manuals, (b) editions
from German contractors’ associations or individual
researchers and (c) textbook editions. The purpose of this
research is to assess the yielded productivity estimation
results under the prism of 14 estimation methodologies.
It is – to the authors’ best knowledge – the first research
attempt for the comparative evaluation of such a diverse
set of estimation methodologies, with the aim of quantifying their effects on the operations analysis in earthmoving works. A uniform mathematical modelling approach
is used to formulate the relevant estimation equations
and, subsequently, a real-case scenario of an earthmoving
project in Greece is used as a benchmark against which
the robustness of each methodology is assessed. A sensitivity analysis on main productivity factors concludes the
research. The preliminary results indicate that equipment
manufacturers’ methods are more optimistic and present
higher sensitivity to specific productivity factors (e.g.
swing angle, excavation depth), whereas the German-
oriented approaches are more conservative with less variability due to differing productivity factors.

Ključne riječi

construction productivity, estimation, excavation, statistical analysis

Hrčak ID:

321165

URI

https://hrcak.srce.hr/321165

Datum izdavanja:

1.1.2023.

Posjeta: 65 *