American Society of Civil Engineers

Estimating Labor Production Rates for Industrial Construction Activities

by S. AbouRizk, (Prof., Dept. of Civ. and Envir. Engrg., Univ. of Alberta, Edmonton, AB, Canada T6G 2G7. E-mail:, P. Knowles, (Proj. Coordinator, PCL Construction Management Inc., Bldg. 4, 5400 – 99 St., Edmonton, AB, Canada T6E 3N7. E-mail:, and U. R. Hermann, (Sr. Engr., PCL Industrial Constructors Inc., 5402 – 99 St., Edmonton, AB, Canada T6E 3N7. E-mail:

Journal of Construction Engineering and Management, Vol. 127, No. 6, November/December 2001, pp. 502-511, (doi:

     Access full text
     Purchase Subscription
     Permissions for Reuse  

Document type: Journal Paper
Abstract: This paper discusses an approach based on artificial neural networks that enables an estimator to produce accurate labor production rates (labor/unit) for industrial construction tasks such as welding and pipe installation. The paper first reviews factors that were found to affect labor production rates on industrial construction tasks, current estimating practices and their limitations, and the process followed in collecting historical production rates. An artificial neural network model is then described. The model is composed of a two-stage artificial neural network, which is used to predict an efficiency multiplier (an index) based on input factors identified by the user. The multiplier is then used to adjust an average production rate given in man-hours/unit for use on a specific project. Estimates of production rates from the new approach are compared to the existing estimating practices and conclusions are presented.

ASCE Subject Headings:
Neural networks