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Arditi, D and Ongkasuwan, D (2009) Duties and Responsibilities of Construction Managers: Perceptions of Parties Involved in Construction. Journal of Construction Engineering and Management, 135(12), 1370–4.

Bayraktar, M E and Hastak, M (2009) Bayesian Belief Network Model for Decision Making in Highway Maintenance: Case Studies. Journal of Construction Engineering and Management, 135(12), 1357–69.

Braimah, N and Ndekugri, I (2009) Consultants’ Perceptions on Construction Delay Analysis Methodologies. Journal of Construction Engineering and Management, 135(12), 1279–88.

Davis, K A and Songer, A D (2009) Resistance to IT Change in the AEC Industry: Are the Stereotypes True?. Journal of Construction Engineering and Management, 135(12), 1324–33.

Fong, P S W and Kwok, C W C (2009) Organizational Culture and Knowledge Management Success at Project and Organizational Levels in Contracting Firms. Journal of Construction Engineering and Management, 135(12), 1348–56.

Hallowell, M R and Gambatese, J A (2009) Construction Safety Risk Mitigation. Journal of Construction Engineering and Management, 135(12), 1316–23.

Lee, H, Shin, J, Park, M and Ryu, H (2009) Probabilistic Duration Estimation Model for High-Rise Structural Work. Journal of Construction Engineering and Management, 135(12), 1289–98.

  • Type: Journal Article
  • Keywords: Simulation; Probability; Forecasting; Productivity; Buildings, high-rise; Construction management; Weather conditions;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000105
  • Abstract:
    The duration of a construction project is a key factor to consider before starting a new project, as it can determine project success or failure. Despite the high level of uncertainty and risk involved in construction, current construction planning relies on traditional deterministic scheduling methods that cannot clearly ascertain the level of uncertainty involved in a project. This, subsequently, can prolong a project’s duration, particularly when that project is high-rise structural work, which is not yet a common project type in Korea. Indeed, among construction processes, structural work is notable, as it is basically performed outdoors. Thus, no matter how precisely a schedule is developed, such projects can easily fail due to unexpected events that are beyond the planner’s control, such as changes in weather conditions. Therefore, in this study, to cope with the uncertainties involved in high-rise building projects, a probabilistic duration estimation model is developed in which both weather conditions and work cycle time for unit work are considered to predict structural work duration. According to the proposed estimation model, weather variables are divided into two types: weather conditions that result in nonworking days and weather conditions that result in work productivity rate (WPR) change. Obtained from actual previous data, the WPR is used with relevant nonworking day weather conditions to modify the actual number of working days per calendar days. Furthermore, on the basis of previous research results, the cycle time of the unit work area is assumed to follow the β probability distribution function. Thus, the probabilistic duration model is valid for 95% probability. Finally, a case study is conducted that confirms the model can be practically used to estimate more reliable and applicable probabilistic durations of structural work. Indeed, this model can assist schedulers and site workers by alerting them, at the beginning of a project, to project uncertainties that specifically pertain to structural work and the weather. Thus, the proposed model can enable personnel to easily amend, and increase the reliability of, the construction schedule at hand.

Sacks, R, Treckmann, M and Rozenfeld, O (2009) Visualization of work flow to support lean construction. Journal of Construction Engineering and Management, 135(12), 1307–15.

Tuuli, M M and Rowlinson, S (2009) Performance Consequences of Psychological Empowerment. Journal of Construction Engineering and Management, 135(12), 1334–47.

Williams, R C, Hildreth, J C and Vorster, M C (2009) Highway Construction Data Collection and Treatment in Preparation for Statistical Regression Analysis. Journal of Construction Engineering and Management, 135(12), 1299–306.