Abstract:
Construction projects are usually broken into a series of tasks linked through a concise schedule. These tasks are interdependent and characterized by certain key events called milestones that mark the completion of a large phase of the project. The completion of a certain activity, task or milestone is on other hand defined by the submission of a certain deliverable. Since the nature of projects is described as none decomposable tree system, it is difficult to break it into complete independent parts. Even if it was well mapped into a defined structure, the interdependencies between parts from different categories are unseen and are hard to eliminate. This might lead to coordination, communication and information exchange problem. Existing modeling approaches have limitations when it comes to modeling the complexity of project deliverables. Hence, some propagation phenomena, such as chain reactions and loops, are not properly taken into account. This thesis work aims at analyzing and anticipating potential behavior of the network considering its structure and possible propagations, to help project managers making more reliable decisions. This is done by re-estimating project deliverable priority in terms of two complementary characteristics, their individual and collective importance. The originality of this work is to combine both analyses and to propose a tailored set of indicators for collective importance assessment, based on numerous existing works applied on several types of systems and networks. These indicators have already been proven to be useful for such analysis in complex product development networks. Several articles confirmed using both theoretical techniques and large-scale simulations that focusing engineering and management efforts on central elements of a network is likely to improve the performance of the overall network. Moreover, the failure of critical deliverables (individual or collective) is likely to affect the vulnerability of the overall project process, which is the reason why this
Description:
Thesis. M.E.M. American University of Beirut. Department of Industrial Engineering and Management, 2018. ET:6748$Advisor : Dr. Hadi Jaber, Visiting Assistant Professor, Industrial Engineering and Management ; Members of Committee : Dr. Bacel Maddah, Professor, Industrial Engineering and Management ; Dr. Selim Hani, Assistant Professor, Industrial Engineering and Management ; Dr. Hussein Tarhini, Assistant Professor, Industrial Engineering and Management.
Includes bibliographical references (leaves 70-71)