Stochastic dozer productivity estimation method

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Stochastic dozer productivity estimation method

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

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.