Izvorni znanstveni članak
Multi-Attribute Regression Analysis for Concrete Pavement Productivity Estimation
Antonis Panas
John-Paris Pantouvakis
Sažetak
The estimation of concrete pavement productivity is intricate because of several factors, such as the available working width and length, the concrete layer thickness, the construction methodology, automation capabilities and the working conditions.
This study intends to assess the productivity of the concrete pavement operations by taking into consideration the effect of the above factors using the regression analysis technique. In regression models, one dependent variable (productivity) is considered against several independent variables (width, length, working conditions, health & safety level). Direct observation, site visits and video recording of actual concrete pavement activities on a construction site over a period of four months has been used for data collection. The regression relationships are plotted, so as to derive empirical nomographs and correction coeffcients which can be used to adjust actual productivity against theoretical baselines. In this sense, process-oriented estimation methodologies for specific construction
operations can be developed, by which each factor’s contribution
to productivity can be estimated. The results indicate that a larger
working area increases productivity for a given concrete layer thickness.
The estimated correction factors fit the actual measurements in a statistically significant fashion, however their predictive capability is expected to improve as the study sample increases.
Ključne riječi
Concrete paving; Cost; Model; Productivity; Regression
Hrčak ID:
74978
URI
Datum izdavanja:
1.12.2011.
Posjeta: 2.035 *