| With rapid development of economic and market, the environment of project becomes more and more complicated, resulting from shorter due date, higher on-time completion rate and lower cost. Project management is facing a greater challenge. As a new project management methodology, Critical Chain Project Management (CCPM) has been successfully applied in the project environment with large uncertainty. Many theoretical books and articles have already appeared on the subject, and it also received considerable attention among practitioners, so CCPM has become one of the most hot and popular topic in the field of project management. Based on the synthetical application of project planning and control methods, Theory of Constraints, and statistical dependence model and Bayesian methods, this dissertation makes a systematic study of buffer sizing method and buffer monitoring method. The main research works are as follows:Firstly, the assumption of independence in most existing buffer sizing approaches is unrealistic, and a method for determining buffer sizes with dependence assumption between activities is introduced. In detail, the dependence relationship between activities is represented based on the model in schedule risk analysis method, and four dependence parameters are proposed. The effect of these parameters on project duration performance is analyzed by means of a large number of computational experiments. Two parameters with the obvious impacts, which are the dependence degree and the dependence factor, are integrated into the formulation of buffer sizing approach. The suggested method is tested and compared to the methods with independence assumption. The results indicate that the suggested method can provide better protection when at least one of the two definitions is at a high level.Secondly, a new method to determine the capacity constraints buffer size was proposed based on the characteristics of drum activities in critical chain multi-project scheduling. In detail, the difference between drum activities and activities on the feeding chain were discussed. Effects of drum resource tightness, drum network complexity and drum space interval were measured and integrated in this method, so that the various uncertain problems are solved and the project performances are improved in multi-project management. A simulation experiment was carried out to demonstrate the effectiveness and practicability of the proposed method.Thirdly, based on the decrease in the degree of uncertainty under dynamic environment, a dynamic buffer monitoring method was proposed. This method dynamically calculates the buffer size and the time instant for monitoring, adjusts the place of the two control trigger points to control the project, so that the proper warning information can be sent to the project manager to take correct action to meet project deadline. Then, the process of updating activities duration was illustrated by using the Linear Bayesian Method to expand the basic buffer management model. A simulation experiment was carried out to demonstrate the effectiveness and practicability of the proposed method.Finally, the dynamic buffer monitoring problem is studied from the perspective of project schedule monitoring. The current buffer monitoring methods may generate incorrect warning information because they neglect the project structure and activity informations. To solve this defect, the buffer monitoring method is combined with the schedule risk analysis method. Specifically, the activity sensitivity information is introduced as a basis for decision making. An activity cruciality index based bottom-up project monitoring method is triggered and integrated into buffer control process when buffer consumption penetrates into the yellow region. Experimental results show that the proposed hybrid monitoring method do better than the current buffer monitoring methods in the monitoring performance indicators when we reasonably set the action threshold of CRI.
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