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<p>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.</p>
</abstract>

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.

Comparative assessment of deterministic methodologies for estimating excavation productivity

Organization, Technology and Management in Construction: an International Journal

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper investigates the prediction capability of deterministic methodologies in estimating construction productivity for earthmoving operations. Published...

Comparative assessment of deterministic methodologies for estimating excavation productivity

Article Category: Research Paper

Publicado en línea: 11 sept 2023

Páginas: 63 - 78

Recibido: 31 ago 2022

Aceptado: 29 ene 2023

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

Palabras clave
construction productivity, estimation, excavation, statistical analysis

© 2023 Antonios Panas et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Comparative assessment of deterministic methodologies for estimating excavation productivity

Article Category: Research Paper

Publicado en línea: 11 sept 2023

Páginas: 63 - 78

Recibido: 31 ago 2022

Aceptado: 29 ene 2023

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

Palabras claveconstruction productivity, estimation, excavation, statistical analysis

© 2023 Antonios Panas et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
construction productivity, estimation, excavation, statistical analysis