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.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Android, inc. (a). (Accessed 2014). “Android package index.” 〈http://developer.android.com/reference/packages.html〉.
Android, inc. (b). (Accessed 2014). “Android sensor overview.” 〈http://developer.android.com/guide/topics/sensors/sensors_overview.html〉.
Ang, A. H-S. and Tang, W. H. (1975). Probability Concepts in Engineering Planning and Design, Wiley, New York, N.Y., Vol. 1, DOI: 10.2307/2987875.
Baxter, L. A. (1992). “Probability, statistics, and queuing theory with computer science applications.” Technometrics, Taylor & Francis, Oxfordshire, U.K., Vol. 34, No. 2, pp. 240–241, DOI: 10.1080/00401706.1992.10484935.
Burdett, R., Kozan, E., and Kenley, R. (2015). “Block models for improved earthwork allocation planning in linear infrastructure construction.” Engineering Optimization, Taylor & Francis, Vol. 47, No. 3, pp. 347–369, DOI: 10.1080/0305215X.2014.892594.
Caterpillar, Inc. (2010). Caterpillar performance handbook. 40th ed., Caterpillar, Peoria.
Elazouni, A. (2009). “Heuristic method for multi-project finance-based scheduling.” Construction Management and Economics, Taylor & Francis, Vol. 27, No. 2, pp. 199–211, DOI: 10.1080/01446190802673110.
Flood, I. and Christophilos, P. (1996). “Modeling construction processes using artificial neural networks.” Automation in construction, Elsevier, Vol. 4, No. 4, pp. 307–320, DOI: 10.1016/0926-5805(95)00011-9.
Han, S. (2010). “Productivity analysis comparison of different types of earthmoving operations by means of various productivity measurements.” Journal of Asian Architecture and Building Engineering, JSTAGE, Vol. 9, No. 1, pp. 185–192, DOI: 10.3130/jaabe.9.185.
Han, S. W., Lee, S. Y., and Halpin, D. W. (2005). “Productivity evaluation of the conventional and GPS-based earthmoving systems using construction simulation.” Construction Research Congress, ASCE, pp. 178–182, DOI: 10.1061/40754(183)35.
Hare, W. L., Koch, V. R., and Lucet, Y. (2011). “Models and algorithms to improve earthwork operations in road design using mixed integer linear programming.” European Journal of Operational Research, Elsevier, Vol. 215, No. 2, pp. 470–480, DOI: 10.1016/j.ejor.2011.06.011.
Hoel, P. G. (1962). Introduction to mathematical statistics. 3nd ed., Wiley, New York, N.Y., DOI:10.1002/bimj.19670090111.
Kecojevic, V. J. and Mrugala, M. J. (2003). “Estimation of dozer production and costs.” International Journal of Surface Mining, Taylor & Francis, Vol. 17, No. 3, pp. 171–182, DOI:10.1076/ijsm.17.3.171.14771.
Khisty, C. J. and Mohammadi, J. (2001). Fundamentals of systems engineering: with economics, probability, and statistics, Prentice Hall, New Jersey.
Klanfar, M., Kujundžić, T., and Vrkljan, D. (2014). “Calculation analysis of bulldozer’s productivity in gravitational transport on open pits.” Tehnički vjesnik/Technical Gazette, Researchgate, Vol. 21, No. 3, pp. 517–523.
Lambropoulos, S., Manolopoulos, N., and Pantouvakis, J. P. (1996). “SEMANTIC: Smart earthmoving analysis and estimation of cost.” Construction Management & Economics, Taylor & Francis, Vol. 14, No. 2, pp. 79–92, DOI: 10.1080/014461996373539.
Lee, D.-E. and Arditi, D. (2006). “Automated statistical analysis in stochastic project scheduling simulation.” Journal of Construction Engineering and Management, ASCE, Vol. 132, No. 3, pp. 268–277, DOI:10.1061/(ASCE)0733-9364(2006)132:3(268).
Meeker, Q. Q. and Escobar, A. L. (1998). Statistical Methods for Reliability Data. 1st ed., John Wiley & Sons, Inc., New York, NY.
Nassar, K. and Hosny, O. (2012). “Solving the least-cost route cut and fill sequencing problem using particle swarm.” Journal of Construction Engineering and Management, ASCE, Vol. 138, No. 8, pp. 931–942, DOI: 10.1061/(ASCE)CO.1943-7862.0000512.
Ok, S. C. and Sinha, S. K. (2006). “Construction equipment productivity estimation using artificial neural network model.” Construction Management and Economics, Taylor & Francis, Vol. 24, No. 10, pp. 1029–1044, DOI: 10.1080/01446190600851033.
Parente, M., Correia, A. G., and Cortez, P. (2015). “Modern optimization in earthwork construction.” Proceedings of the Institution of Civil Engineers-Structures and Buildings, Vol. 164, No. 6, pp. 421–432, DOI: 10.1680/ecsmge.60678.vol2.031.
Peurifoy, R. L., Schexnayder, C. J., and Shapira, A. (2006) Construction planning, equipment, and methods. 7th ed., McGraw-Hill, Boston.
Wilcox, R. R. (2012). Introduction to robust estimation and hypothesis testing, Academic Press, San Diego, DOI: 10.1080/00401706.1998.10485491.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Park, Y.J., Gwak, H.S., Kim, B.S. et al. Stochastic dozer productivity estimation method. KSCE J Civ Eng 21, 1573–1580 (2017). https://doi.org/10.1007/s12205-016-1596-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12205-016-1596-9