Heavy Equipment Scheduling for Horizontal Construction Projects

G. Emre Gurcanli*, Harun Turkoglu, Senem Bilir

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

11 Citations (Scopus)

Abstract

Construction project scheduling requires additional parameters and estimation if the projects are equipment intensive. Since preventive maintenance, multiple movement operations, and sitting idle vehicles affect not only the activity or the total project duration, but also the budget of the project, heavy equipment scheduling deserves a special focus. In this study, a survey was conducted within construction companies to collect information about how their productivity analysis and project scheduling were executed, and upon which parameters they were based. Additionally, in a selected residential building construction project, Monte Carlo simulation was applied for estimating the productivity on a construction site with selected parameters. The results reveal that Turkish construction companies have a poor focus on heavy equipment scheduling as well as productivity and their productivity data just relies on daily documents from a machinery department and basic extrapolation for future construction activities. This paper briefly reveals the characteristics of the Turkish construction industry towards equipment scheduling and productivity analyses and recommends simulation methods such as Monte Carlo for cost, as well as productivity estimation to provide extensive cost savings during construction projects.

Original languageEnglish
Pages (from-to)265-273
Number of pages9
JournalProcedia Engineering
Volume182
DOIs
Publication statusPublished - 2017
Event7th International Conference on Engineering, Project, and Production Management, EPPM 2016 - Bialystok, Poland
Duration: 21 Sept 201623 Sept 2016

Bibliographical note

Publisher Copyright:
© 2016 The Authors. Published by Elsevier Ltd.

Keywords

  • Monte Carlo Simulation
  • construction projects
  • equipment planning
  • productivity

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