# Systematic Review on the Use of CCPM in Project Management: Empirical Applications and Trends
## 3 Results
The next article analyzed proposes the integration of fuzzy logic with QFD (Quality Function Deployment) to systematically cal culate buffer time in the Critical Chain, considering six project uncertainties (time, budget, resources, etc.). The approach defines weights and fuzzy membership functions for each activity based on the degree of uncertainty associated with it. Applied to a fictitious project, the method reduced the total time to 112.68 days, compared to 117.75 days with conventional CCPM and 157 days with PERT. The solution resulted in more accurate buffers, avoiding excessive delays and optimizing the schedule [65]. The next study proposes a Scenario-Based Proactive Robust Optimization (SBPRO) method that integrates scenario analysis and fuzzy logic to increase schedule robustness in CCPM projects. Validated in three case studies with real projects, SBPRO outperformed the traditional CCPM method in terms of robustness and probability of on-time completion. The model balances project duration and schedule robustness using a genetic algorithm and dual objective functions. In all simulated cases, SBPRO demonstrated greater resilience to uncertainty and superior performance in risk and delay management [66]. This article presents the application of the CCPM method to the assembly of a coal cutter, with a focus on the introduction of resources, feed, and design buffers. Based on historical data and statistical analysis (using Statistica software), three resource buffers and one feed buffer were estimated. Implementing these buffers reduced project duration by up to 56 days and costs by 8%. The analysis revealed that the use of buffers was crucial for overcoming resource conflicts and uncertainties, increasing schedule reliability in make-to-order environments [67]. The following study applies the CCPM method to scheduling a shearer loader assembly process, focusing on human resource conflicts (welders). The analysis compares schedules developed using the ASAP and ALAP principles, demonstrating that only CCPM enables realistic resource allocation. Resolving resource conflicts required task reordering, which increased the duration from 175 to 230 days; however, it resulted in a more feasible and robust schedule. The article highlights CCPM as superior to CPM for its focus on resource constraints and mitigating multitasking and delays [68]. The next article proposes a model for the transmission and control of duration risk based on CCPM and the theory of risk element transmission in projects. The approach enables the calculation of duration risk propagation along both critical and non-Critical Chains, considering risk absorption coefficients for each activity. The model identifies bottleneck activities and redefines buffer size based on accumulated systemic risk. A numerical example illustrates how to identify the points with the greatest impact on the project's overall risk, providing a more reliable basis for schedule planning [69]. The next article proposes an improved buffer management framework for CCPM, incorporating resource cost and schedule stability criteria. Reactive strategies, such as SOR, TSR, and ASR, are introduced to reschedule or reallocate resources in response to deviations. The planning phase considers a resource cut-off date to minimize costs for regular and emergency resources. Simulations with PSPLIB instances demonstrated that the use of the framework significantly reduces total costs and improves schedule stability, without compromising on-time delivery [70]. This paper proposes a method for integrating CCPM and LSM (Linear Scheduling Method) for repetitive projects. The model introduces a new buffer--the Resource Conflict Buffer (RCB)--and a systematic process for identifying multiple Critical Chains. The approach respects resource continuity and utilizes conservative estimates to minimize project duration.