eng Science and Education Publishing American Journal of Civil Engineering and Architecture 2328-3998 2018-02-26 6 2 80 92 10.12691/ajcea-6-2-5 AJCEA2018625 article Hamed Nabizadeh Rafsanjani hnabizadehrafsanj2@unl.edu 1 Yaghob Gholipour 2 Xiaoxiang Xue 3 Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln, Lincoln, NE 68588, USA; formerly, School of Civil Engineering, University of Tehran, Tehran 14155, Iran School of Civil Engineering, University of Tehran, Tehran 14155, Iran Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln, Omaha, NE 68182, USA; Project Engineer, Jacobs Engineering Group, Omaha, NE 68134, USA Estimating the actual production rate of construction machinery which clearly differs from nominal production provided by machinery manufacturers always is a critical challenge in construction projects execution. Studies indicate that true estimation of actual production is a key element in estimating the time and cost required to terminate construction operations. However, current literature shows that it is still a quite challenging to estimate actual production. In particular, there are various independent parameters that affect the actual production rate. Understanding the role and importance of each parameter could lead to an accurate estimation for production rates. To this end, this paper presents a statistical-based approach to find the discrepancies between the nominal and actual production rates of crawler-type dozers and to understand how various parameters could affects the actual production rates. The data for the actual production of machine were records from productivity measurement of 39 dozers. Working condition, type of materials, and ground slope are three main independent parameters considered and evaluated for each machine. The results obtained from statistical analyses on the data and a comparison between these results with the data provided by Caterpillar and Komatsu manufacturers show a) the discrepancies between the actual and nominal hourly production, b) the effect of individual parameters on actual production, and c) the relationship between machinery working age and discrepancies. The findings of this study could be a unique help for project managers in planning of machinery and equipment in a project site. http://pubs.sciepub.com/ajcea/6/2/5/ajcea-6-2-5.pdf heavy construction machinery crawler-type dozer actual hourly production estimation production parameters statistical analysis case study