Buffer Sizing Model Incorporating Fuzzy Risk Assessment: Case Study on Concrete Gravity Dam and Hydroelectric Power Plant Projects

Balta, Semsettin; Birgönül, M. Talat; Dikmen, İrem

doi:10.1061/ajrua6.0000948

Cited by 7 publications

(4 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, time contingency can be established through subjective assessments, where individuals rely on their intuitive judgments. When employing subjective judgment, a time buffer of 25-50% of the overall project duration can be arbitrarily allocated and incorporated into the baseline schedule [44]. This buffer is meant to account for uncertainties that may arise during the estimation of the total project duration.…”

Section: B Estimation Of Time Contingencymentioning

confidence: 99%

Reliable Time Contingency Estimation Based on Adaptive Neuro-Fuzzy Inference System in Construction Projects

Doungsoma,

Pawan

2023

IEEE Access

View full text Add to dashboard Cite

Project scheduling is one of the most essential processes and plays a critical role in determining the success of construction projects. The reliable time contingency enables project planners to effectively address uncertainties and various types of risks that may affect the project duration. The traditional scheduling technique such as deterministic methods and probabilistic methods may not be suitable when used for planning construction projects with uncertainties and risks. This paper proposes a new framework that integrates risk management into project scheduling to establish a more reliable project schedule. The proposed model adopts the adaptive neuro-fuzzy inference system (ANFIS) called the ANFIS-TOOL to model the possibility of risk occurrences integrated with project scheduling in terms of risk lag time (ANFIS-RLT) to generate risk-integrated project duration (RPD). The learning capabilities of adaptive neural networks are utilized to adjust the parameters of the model according to the fuzzy rules, aiming to achieve the most suitable representation of the model. In a real-life case study, a sheet pile wall with a temporary bracing system (SPBS) was applied to demonstrate the application of this technique. The root mean square error (RMSE) was used to validate the accuracy of the model before being applied to real construction projects with a high degree of accuracy. This model can be used as an excellent tool to generate a more reliable schedule baseline in construction projects.INDEX TERMS Adaptive neuro-fuzzy inference system, risk management, time contingency, scheduling.

show abstract

Section: B Estimation Of Time Contingencymentioning

confidence: 99%

Reliable Time Contingency Estimation Based on Adaptive Neuro-Fuzzy Inference System in Construction Projects

Doungsoma,

Pawan

2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In this method, the tightness of physical resources and information resources are used in buffer sizing which the tightness of physical resources is calculated by determining a critical value for the use of resources and the tightness of information resources to the amount of rework due to the exchange of information between activities. Due to the importance of timely completion of dam projects and hydroelectric plants, a method for measuring time buffers based on fuzzy risk evaluation has been suggested for such projects by Balta et al [2]. Roghanian et al [8] considered a project scheduling model with resource constraints to determine the project schedule.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Estimating the actual cost and duration of construction projects is difficult due to the complexity and vulnerability of tasks to uncertainty. Scheduling a construction project is done under time, cost, and quality constraints, in which the crashing of activities may be associated with reduced quality [2][3][4][5]. Nowadays, projects are subject to a wide range of constraints.…”

Section: Introductionmentioning

confidence: 99%

A Bi-Objective Model for Scheduling Construction Projects Using Critical Chain Method and Interval-Valued Fuzzy Sets

et al. 2022

View full text Add to dashboard Cite

Numerous constraints affect construction projects, and lack of management may lead to schedule deviation. In the execution phase of the project, due to the lack of timely access to the required resources and the existence of uncertainty, the project activities do not progress following the schedule, and as a result, schedule deviation occurs. The scheduling addresses resource constraints by the critical chain method and deals with delays in activities by placing buffers that have emerged as a method for scheduling construction projects. This paper presents a new bi-objective mathematical model which aims to reduce delay and increase quality, based on the critical chain method and resource constraint for scheduling construction projects. In the proposed model, the activities have been considered multi-mode ones. Moreover, this paper has assumed each activity to be executed in a normal or crashing way. Due to the uncertainty in real-world problems, the duration of the activity is expressed using triangular interval-valued fuzzy numbers. A new interval-valued fuzzy solution process is presented in this paper using a two-step approach. First, the equivalent crisp model is given; then in the second step, a goal programming approach is applied for transforming the bi-objective model into the single-objective one. Finally, the mathematical model is implemented on a case study adapted from the literature, and sensitivity analysis of the results is conducted.

show abstract

“…The risk management framework for engineering projects mainly includes risk identification, analysis, assessment, and control [14]. Risk evaluation studies on internal factors such as the construction schedule, cost, and quality of hydropower projects are currently conducted through this framework [15][16][17]. At the same time, the social environment external risk control is also one of the elements of successful hydropower project construction, including social risks and environmental risks, such as policy changes, natural disasters, etc.…”

Section: Literature Review 21 Project Risk Managementmentioning

confidence: 99%

Stakeholder Behavior Risk Evaluation of Hydropower Projects Based on Social Network Analysis—A Case Study from a Project

Xiao

et al. 2022

Buildings

View full text Add to dashboard Cite

Since construction involves many stakeholders and their behavioral risk interaction, which brings risks to the project construction, it is necessary to strengthen the research on the risk management of hydropower projects. This study comprehensively considers the characteristics of hydropower project construction and identifies relevant stakeholders to build and improve the stakeholder behavior risk evaluation index system. On this basis, the social network analysis method is used to build an evaluation model of stakeholders’ behavioral risk transmission network, identify core factors and key relationships, analyze the path of behavioral risk transmission, take measures to cut off the transmission of core factors and key relationships, and test the effect of the risk network after control. The results show that: the evaluation model can effectively identify the core behavioral risk factors and key relationships in the construction process. Then, after taking targeted measures on the core behavioral risk factors and key relationships, hydropower projects are less affected by behavioral risk factors, and the risk transmission paths are reduced, which reduces the probability of behavioral risks arising from stakeholders and improves the behavioral governance efficiency of stakeholders. Applying this research model to the risk management of international hydropower projects can provide better guidance to the stakeholders and improve the accuracy and effectiveness of analyzing the behavioral risks of stakeholders in hydropower projects.

show abstract

Buffer Sizing Model Incorporating Fuzzy Risk Assessment: Case Study on Concrete Gravity Dam and Hydroelectric Power Plant Projects

Cited by 7 publications

References 24 publications

Reliable Time Contingency Estimation Based on Adaptive Neuro-Fuzzy Inference System in Construction Projects

Reliable Time Contingency Estimation Based on Adaptive Neuro-Fuzzy Inference System in Construction Projects

A Bi-Objective Model for Scheduling Construction Projects Using Critical Chain Method and Interval-Valued Fuzzy Sets

Stakeholder Behavior Risk Evaluation of Hydropower Projects Based on Social Network Analysis—A Case Study from a Project

Contact Info

Product

Resources

About