Logistical model to approximate the S Curve of the planning of sewage projects
DOI:
https://doi.org/10.13140/RG.2.2.22509.33769Keywords:
S curve, logistic equation, construction projects planning, control of worksAbstract
The engineering projects have a plan of activities to be carried out in an estimated initial time, which is contrasted with the real time that the execution of the project took. This initial plan is of utmost importance for both the builder and the contracting entity of the work, since this represents a direct relationship of the costs of each stage and the time they demand. The graphic representation of this relationship is adopted as a planning resource, and its form is similar to the S curve. On this graph, it can be seen that at the beginning of the project the accumulated costs are increasing, and at the end of the project it is observed that they decrease. For these reasons, this paper presents a logistic equation model that predicts the planning of a sewer construction project based on a given budget for its execution and the estimated initial time. The model is constructed from a representative sample of sewerage projects executed in the province of Pichincha, and is validated using other that not taken into account in said sample. The model proposed in this paper has as an added value its usefulness in decision-making by public entities because it provides a more accurate estimate of the project's valued timeline
Downloads
References
A. Mattos and F. Valderrama, «Métodos de planificación y control de obras: Del diagrama de barras al BIM» Barcelona, 2014
G. A. Barraza, W. E. Back, and F. Mata, «Probabilistic monitoring of project performance using SS-curves» J. Constr. Eng. Manag., vol. 126, no. April, p. 32887, 2002
G. A. Barraza, W. E. Back, and F. Mata, «Probabilistic Forecasting of Project Performance Using Stochastic S Curves» J. Constr. Eng. Manag., vol. 130, no. 1, pp. 25–32, 2004
D. F. Cioffi, «A tool for managing projects: An analytic parameterization of the S-curve» Int. J. Proj. Manag., vol. 23, no. 3, pp. 215–222, 2005
L. Chao and C. Chien, «Estimating Project S-Curves Using Polynomial Function and Neural Networks» J. Constr. Eng. Manag., vol. 135, no. 3, pp. 169–177, 2009
L. C. Chao and C. F. Chien, «A Model for Updating Project S-curve by Using Neural Networks and Matching Progress» Autom. Constr., vol. 19, no. 1, pp. 84–91, 2010
Y.-M. Cheng, C.-H. Yu, and H.-T. Wang, «Short-Interval Dynamic Forecasting for Actual S -Curve in the Construction Phase» J. Constr. Eng. Manag., vol. 137, no. 11, pp. 933–941, 2011
M. Chiao Lin, H. Ping Tserng, S. Ping Ho, and D. L. Young, «A novel dynamic progress forecasting approach for construction projects» Expert Syst. Appl., vol. 39, no. 3, pp. 2247–2255, 2012
J. R. S. Cristóbal et al., «A Residual Grey Prediction Model for Predicting S-curves in Projects» Procedia Comput. Sci., vol. 64, pp. 586–593, 2015
A. Czarnigowska and A. Sobotka, «Time-cost relationship for predicting construction duration» Arch. Civ. Mech. Eng., vol. 13, no. 4, pp. 518–526, 2013
M. Kadry, H. Osman, and M. Georgy, «Causes of Construction Delays in Countries with High Geopolitical Risks» J. Constr. Eng. Manag., vol. 143, no. 2, p. 04016095, 2017
Published
How to Cite
Issue
Section
Copyrights of the author / s from the year of publication
This work is under international license Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0.
The opinions expressed by the authors do not necessarily reflect the position of the editor of the publication or UCLA. The total or partial reproduction of the texts published here is authorized, provided that the complete source and electronic address of this journal is cited. Authors have the right to use their articles for any purpose as long as it is done nonprofit. The authors can post on the internet or any other media the final approved version of their work.