# Systematic Review on the Use of CCPM in Project Management: Empirical Applications and Trends
## 3 Results
According to the projected data and the main contributions of the work, this new concept in CCPM is called resource-based reliability, which better reflects the uncertainty in resource availability in the project schedule, and a new formulation for buffer sizing in CCPM, based on reliability theory, which improves the accuracy of buffer determination [32]. In the paper presented at the conference, a case study in the construction industry evaluated the project schedule to determine the optimum schedule for implementing the project. With the application of CCPM, a feed buffer of four days and a project duration with a total buffer of 53 days were achieved, with existing scheduling from 432 to 379 days without buffer consumption [33]. In the next research article, which employed modeling and simulation, time buffers were dimensioned in two stages using both deterministic and stochastic optimization techniques, considering the needs of construction management. The optimization criteria are based on the cash flow analysis of the wind power generator installation construction project. The results show that the approach guarantees the protection of the scheduled construction completion date and the stability of the schedule [38]. In the next study, modeling and simulation are employed to present a project management method in scenarios where network of activities is necessary. By proposing a model that integrates CCPM, the design structure matrix method, and the max-plus method, it was possible to achieve greater accuracy of activity completion times, more reliable deliveries, and reduced project risks and uncertainties [23]. The sixteenth study presents a simulation-supported model integrating the last planner system (LPS), the linear programming method (LSM), and CCPM to develop project tracking and control procedures. The results indicate that the comparison between the schedule developed by the proposed model and the Monte Carlo simulation showed that the baseline duration generated by the simulation exceeds that produced by the developed method by 12% and 10% for schedules with a confidence level of 50% and 90%, respectively [37]. The next article proposes a new buffer sizing procedure based on network decomposition through modeling and simulation. Computational tests using both empirical and simulated data demonstrate that the proposed method provides more accurate estimates of project execution time and smaller feed buffers. Additional benefits include lower expenses, reduced parallel work, multitasking, and rework, as well as risk reduction. The next research presents an unprecedented discussion of a case study on highway construction. The work developed an improved CCPM framework for effectively implementing construction-related projects. Considering the TOC concept, a methodology was developed to analyze bottlenecks and promote improvements in highway projects in India through the formulation of the Current Reality Tree (ARA), Evaporating Clouds (EN), Future Reality Tree (ARF), Prerequisite Tree (AP), and Transition Tree (AT) of the TOC Thinking Process [36]. In a paper presented at a conference, the CPM-Project Evaluation Review Technique (PERT) and CCPM methods were proposed, supported by modeling and simulation, for developing a project schedule that reduces late deliveries and the consequent payment of fines in the construction industry. The results indicate that the probability of the project not being delayed is very low. Only 55% of projects can be completed on time, which is not an effective strategy [34]. In other research presented at a conference, the aim was to apply CCPM and a set of Lean tools to construction projects. Supported by modeling and simulation, the results indicate that by combining Lean Production methods, 5 Whys, FMEA, and CCPM, losses are reduced without the need for buffers, and the total project time decreases by more than 50% [7]. In the twentieth study evaluated, the planned time of a project was reduced using modeling and simulation, with the help of BIM and CCPM.