Time-Uncertainty Analysis by Using Simulation in Project Scheduling Networks
Mohammed Omer, Anwar (1999) Time-Uncertainty Analysis by Using Simulation in Project Scheduling Networks. Masters thesis, Universiti Putra Malaysia.
Risks are inherently present In all construction projects. Quite often, construction projects fail to achieve their time quality and budget goals. Risk management is a subject, which has grown in popularity during the last decade. It is a formal orderly process for systematically identifying, analysing and responding to risks associated with construction projects so as to reduce the effects of these risks to an acceptable level. Risk analysis is primarily concerned with evaluating uncertainties. The purpose of risk analysis is to enable a decision-maker to take an appropriate response in advance against a possible occurrence of a problem. In this study, Monte Carlo simulation as a tool of risk analysis was used. The merge event bias as one of the essential problems associated with PERT is discussed, along with models and approaches developed by other researchers, namely, Probabilistic Network Evaluation Technique (PNET algorithm), Modified PNET, Back-Forward Uncertainly Estimation procedure (BFUE) and concept based on the robust reliability idea. These developed approaches are more reliable in planning construction projects compared to PERT because they attempt to handle the merge event bias problem. In addition, this study demonstrates a number of benefits. the most significant among them being that: (1) Formal risk management tec1miques are rarely used in construction. Dealing with risk management in construction is now essential for minimizing losses and to enhance profitability. (2) It is very dangerous to rely only on PERT/CPM conventional techniques in scheduling projects. (3) To use floats, as stated by traditional resource allocation method, is not practicable. (4) For a project network, the likelihood completion date of a project is exactly equal to the product of the probabilities of each path, separately, with respect to a project completion date. Using simulation now validates this statement. (5) The computation error of a project likelihood completion date is less than 10 percent if a path of a float greater than twice the larger standard deviation of this mentioned path and the critical path is dropped from the calculation, and (6) An effective risk response framework is introduced to help contractors systematically manage the risk in scheduling their projects.
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