Stochastic dozer productivity estimation method

Young Jun Park, Han Seong Gwak, Byung Soo Kim, Dong Eun Lee

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper presents the Stochastic Dozer Productivity Estimation (SDPE) method. It integrates dozer production estimating curves and equipment specification obtained from manufacturers, defines the probability density functions (PDFs) of job condition correction factors, executes the dozer productivity estimating format (DPEF) for the user-defined number of iterations, and estimates the best-fit PDFs of productivity and that of total owning and operating (O&O) cost. The method also improves the reliability of the existing DPEF by effectively dealing with the uncertainties of the job condition correction factors and handling the variability of the productivity and O&O cost. Thus, this method allows an earthwork manager to quantify the risk involved in accepting the deterministic productivity and O&O cost computed by the existing DPEF. It simplifies the tedious and burdensome process involved in executing the DPEF and estimating the best-fit PDFs of productivity and O&O cost. The usability and validity of the system in practice were verified through test cases.

Original languageEnglish
Pages (from-to)1573-1580
Number of pages8
JournalKSCE Journal of Civil Engineering
Volume21
Issue number5
DOIs
StatePublished - 1 Jul 2017

Keywords

  • dozer
  • earthwork estimation
  • owning and operating cost
  • productivity estimating
  • risk

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