# Systematic Review on the Use of CCPM in Project Management: Empirical Applications and Trends
## 3 Results
This paper proposes a robust multi-attribute buffer sizing model based on CCPM, incorporating metrics of complexity, flexibility, robustness, dependency, and risk. The model was tested in a real-world case study of gas infrastructure construction in Iran. Compared to the C&PM, RSEM, and ICC/PM methods, the model reduced the total buffer size by up to 15% and increased scheduling robustness, with a 97.3% on-time completion probability. The approach demonstrated greater cost-effectiveness and reliability under conditions of uncertainty [10]. The following article proposes a conceptual model that integrates the Critical Chain methodology with agile development lifecycles in the automotive industry, with a focus on embedded software projects. The proposal aims to mitigate delays caused by frequent changes in requirements, which are common in this sector. The approach combines the traditional V-model with agile methodologies, such as Adaptive Software Development (ASD), allowing greater tolerance for change without rework. The model is presented in a didactic manner, without empirical application, with a focus on reducing lead time and increasing schedule resilience [52]. The next study under review develops a probabilistic model of construction schedule reliability based on the Critical Chain, using the beta distribution to estimate the probability of meeting deadlines. Simulations demonstrate that applying the model can increase reliability from 50% to up to 90% by adopting more stringent deadlines and final buffers. The model considers the impact of management decisions and levels of control on time distribution, proposing a framework for more effective decision-making in schedule risk management in civil construction [53]. This study uses Monte Carlo simulations to identify a practical limit between \"good\" and \"bad\" multitasking in multi-project environments with different levels of resource availability. Ten portfolios with varying complexity, uncertainty, and resource constraints were simulated. The results show that multitasking of up to two activities can be beneficial when resource availability is below 170%, while multitasking above that level is detrimental. The work proposes an objective criterion to limit multitasking without compromising the principles of the Critical Chain [54]. The study proposes a robust optimization model for the resource-constrained project scheduling problem (RCPSP) based on the Critical Chain, considering uncertainties in activity durations. A genetic algorithm is used to solve the model. Tests have shown that, although the expected project time increases slightly (from 25 to 27.5 days), the duration variance is significantly reduced (from 4.1 to 3.2 days), making the schedule more robust and less susceptible to risks [55]. This article examines the scheduling management of a mobile banking payment project utilizing an enhanced version of the Critical Chain method. It integrates techniques such as the Analytical Hierarchy Process (AHP) and gray scale to define buffers based on uncertainty factors. Applied to a real-world case study at a rural credit union in China, the model reduced the project duration from 550 to 484 days, and later to 426 days with precise buffers. The approach provided better schedule control, greater predictability, and significant operational gains [56]. The following article proposes an integrated Critical Chain Risk Management (CCPM) framework to increase schedule reliability in EPC projects. It uses Fuzzy FMEA to identify critical risk events, complemented by FTA and ETA for mitigation. Applied to a real-world scenario in the electricity sector, the model demonstrated that project duration would have increased significantly (by up to 1311 days in construction) without mitigation; however, integration with CCPM enabled buffers to be dimensioned and delays to be mitigated. The approach proved effective for proactive risk control and increased delivery reliability [57].