Determination of Critical Chain Project Buffer Monitoring Cycle Based on Objective and Activity Risk
In order to enhance management efficiency,Goldratt proposed the critical chain project management method in 1997.This method applies the theory of constraints,which was initially used in the production field,to the realm of project management.Instead of focusing on the critical path,this method highlights the critical chain.Additionally,it places a greater emphasis on the limitation of resource constraints.To mitigate the impact of uncertainty,the method incorporates a buffer into the project timeline.This not only shortens the project duration but also reduces the impact of human behavioral factors on the project.Simultaneously,the project is monitored and controlled through reasonable measures during its implementation.Classical research presumes that buffers can be obtained at any time.However,it is often difficult to achieve in the practical implementation of projects.Excessive monitoring can result in project deviation from the initial plan.To ensure that each buffer monitoring is beneficial for the project implementation,this study propo-ses a method for determining the monitoring period based on project objectives and activity risks.Different projects have varying priorities regarding schedule,cost,and quality.The relationship between these factors is utilized to determine the appropriate monitoring frequency for different project priorities.The monitoring interval for each activity is then allocated according to the risk level of each activity.This determines the monitoring period for each activity.Consequently,the project can attain optimal benefits with a limited number of buffer monitoring instances.The purpose of monitoring buffer consumption is to ensure controllability during project execution and make timely adjustments when deviations occur.The classical approach to monitoring critical chain projects considers the impact of monitoring triggers and makes buffer monitoring a continuous state by default.However,frequent monitoring consumes considerable manpower and time,increasing project costs.Therefore,setting a reasonable monitoring period and frequency is crucial during actual project monitoring.The main objective in setting the monitoring cycle is optimising project comprehensive benefits.As various uncertainties affect project comprehen-sive benefits during implementation,the monitoring interval should be adjusted according to project objectives and activity risks.A uniform monitoring cycle should not be used to achieve optimal monitoring effects with appropriate efforts.The monitoring cycle should not be standardised to achieve optimal results with the most appropriate monitoring efforts.Each project differs in duration,cost,and quality requirements.These factors interact,and shortening duration increases costs and decreases quality.Improving quality requires extending the duration and increasing costs,but high-quality projects reduce rework costs later.Therefore,ensuring project comprehensive benefits is optimal.We determine the overall monitoring frequency based on project objectives,and then analyse activity risk impacts to set the monitoring period.In the planning stage,we estimate multiple risk impacts for each project activity.In the execution stage,we calculate the buffer consumption risk impacts for each activity by determining the ratio of various buffer usage to the planned buffer amount.We analyse the comprehensive risk impacts of activities using the critic method and calculate the comprehensive risk impact coefficients.We combine these with the monitoring frequency to set a reasonable monitoring cycle.Monte Carlo simulation is made using Matlab,assuming each activity duration obeys the lognormal distribu-tion,and generates 1000 random durations using Matlab.The experimental simulation using the static three-part method,the relative buffer monitoring method,and the proposed method shows that,compared to the comparative methods,the proposed method can shorten project duration and reduce costs while meeting quality requirements.
万方数据
维普
