Breakdown Structure Research Articles

Design and implementation of a project management training program to develop workforce ready skills and career readiness in STEM PhD students and postdoctoral trainees

A growing number of STEM doctorates pursue careers across the broader biomedical workforce, including industry, policy, and healthcare. Graduate and postdoctoral trainees need training to develop professional skills that prepare them for diverse workforce options. Through engagement with faculty and trainees, we determined that formal management skills are underdeveloped in trainees, particularly around managing projects in a way that is translatable to broader industries. At Georgetown University Medical Center, we adapted Kern's six-steps of curriculum design to develop the Academy for Transferable Management Skills (ATMS) program to help graduate and postdoctoral trainees develop linear experience in utilizing project management tools in their academic research contexts. ATMS includes a self-paced online CANVAS course with learning objectives and content modules that map to the project management cycle from initiation to closure, developed in consultation with PhD-level industry experts. From 2021–2024, 25 trainees have completed the ATMS program, including the capstone project and posttest evaluation. Trainees also complete brief quizzes after each module as a formative assessment of learning. The pre-test evaluation (n = 92) revealed a baseline of project management “pain points” regularly encountered by trainees (risk management, project charters, work breakdown structures, and managing project scope). Posttest data (n = 25) reveal a significant increase (p < 0.0001) in project management self-efficacy measures across the aforementioned pain point scales. Notably, 100% of trainees indicated that they may/would refer the program to colleagues. ATMS offers trainees the flexibility to pick frameworks that apply to their projects with trainees planning to use project schedules (84%), Work Break Down Structures (80%), lessons learned reports (68%), and communication plans (68%) in their work. This integrated experiential learning approach equips trainees to develop and execute their projects according to industry-informed project management principles, which allows them to perform their current research more efficiently and to utilize project management frameworks in a way that is directly transferable to broad careers.

Influence of macroeconomic factors on construction costs: an analysis of project cases

This study explores the relationship between price increase and project cost increase under macroeconomic shocks by considering the hierarchical structure within price categories, diversification of the cost breakdown structure, infrastructure sector, delivery system, construction methods, and type of bid. The analysis of a large construction company with five large projects as embedded units of analysis reveals significant variations in the relative influence of specific factors across the projects. Unit price categories located higher in the hierarchical breakdown structure display lower vulnerability to macroeconomic changes due to their unique and group-specific influencing factors while price categories influenced by macroeconomic factors depart at lower values in the hierarchical structure. Projects with low-cost breakdown structure diversification can either mitigate or exacerbate cost increases depending on construction methods (off-site or on-site), price drivers of most representative materials (global or local), and delivery systems risk allocation. Under macroeconomic crisis periods, public entities may consider giving high priority to projects more reliant on materials driven by regional dynamics (e.g., concrete pouring) over those driven by global market conditions (e.g., steel, aluminum) while prioritizing integrated delivery systems (e.g., design-build) that promote enhanced collaboration, proactive risk management, aligned incentives, and adaptability for managing complexities and volatilities. Complementary, for projects with higher reliance on global market-driven materials, the results suggest that contractors should prioritize early procurement and acquisition of highly volatile resources in projects under macroeconomic crises.

Surface roughness effects in a transonic axial flow compressor operating at near-stall conditions

Surface roughness is a major contributor to performance degradation in gas turbine engines. The fan and the compressor, as the first components in the engine's air path, are especially vulnerable to the effects of surface roughness. Debris ingestion, accumulation of grime, dust, or insect remnants, typically at low atmospheric conditions, over several cycles of operation are some major causes of surface roughness over the blade surfaces. The flow in compressor rotors is inherently highly complex. From the perspective of the component designers, it is, thus, important to study the effect of surface roughness on the performance and flow physics, especially at near-stall conditions. In this study, we examine the effect of surface roughness on flow physics such as shock-boundary layer interactions, tip and hub flow separations, the formation and changes in the critical points, and tip leakage vortices among other phenomena. Steady and unsteady Reynolds Averaged Navier Stokes calculations are conducted at near-stall conditions for smooth and rough National Aeronautics and Space Administration rotor 67 blades. Surface streamlines, Q-criterion, and entropy contours aid in analyzing the flow physics qualitatively and quantitatively. It is observed that from the onset of stall, to fully stalled conditions, the blockage varies from 21.7% to 59.6% from 90% span to the tip in the smooth case, and from 40.5% to 75.2% in the rough case. This significant blockage, caused by vortex breakdown and chaotic flow structures, leads to the onset of full rotor stall.

Healthcare can't stop evolving: innovation as the catalyst for unleashing the managerial potential of value-based healthcare by stimulating intangible assets and enhancing organizational resilience.

With increasing healthcare service utilization and the introduction of costly therapies, healthcare organizations are pressured to deliver cost-effective services within constrained budgets. Rising costs and the need for efficient healthcare delivery are major concerns for governments, insurers, and health plans. It aims to understand the impact of these intangible assets on creating value and organizational resilience in healthcare, informing better practices and strategies for VBHC implementation. An applied research approach using the Work Breakdown Structure (WBS) methodology was adopted. The research was divided into seven interconnected Work Packages (WPs), each designed to investigate different aspects of the integration between VBHC and intangible assets, with a focus on enhancing organizational resilience through innovative health processes. Key methodologies included literature reviews and qualitative analyses, employing Open Innovation and Design Thinking. The study revealed a dynamic interplay between VBHC, organizational resilience, and intangible assets. It showed that managerial effectiveness is influenced by direct patient outcomes and elements like intellectual capital and organizational reputation. Data integration from various Work Packages provided new insights into how intangible assets underpin VBHC strategies, proposing novel management approaches. Findings highlight the essential role of intangible assets in enhancing service delivery and fostering sustainable healthcare practices. The study highlights a significant oversight in the integration of intangible assets within healthcare organizations, despite their crucial role in optimizing VBHC. It supports literature emphasizing the importance of intellectual capital and organizational culture in enhancing healthcare management efficiency and resilience. A paradigm shift in VBHC to include these assets is needed for building a more adaptable and sustainable healthcare system. This integration can lead to better clinical outcomes, patient satisfaction, and overall healthcare efficiency, aligning more closely with VBHC goals. Recognizing and effectively managing intangible assets are paramount for the successful implementation of VBHC and enhanced organizational resilience. Strategic integration of these assets into healthcare management practices can significantly improve patient outcomes and create a more sustainable, patient-centered, and resilient healthcare system. Future studies should develop methodologies for robust measurement and integration of these assets to fully realize the potential of VBHC.

Development a risk assessment method for dimensional stone quarries

Over the last 20 years, the global production of dimension stones has grown rapidly. Today, seven countries—China, India, Turkey, Iran, Italy, Brazil, and Spain—account for around two-thirds of the world's output of dimension stones. Each one has annual production levels of nine to over twenty-two million tons. Mining operation in general is one of the most hazardous fields of engineering. A large amount of dimensional stone quarries require a special scheme of risk assessment. Risk Breakdown Structure is one of the major stages of risk assessment. In this paper, a detailed structure of risks of the dimension stone quarrying is formed, and divided into 17 main levels and 128 sublevels. The complexity of identifying different parameters made it requisite to use multi-attribute decision-making methods for prioritizing associated risks. As a case study, the main risks of the Ghasre Dasht marble mine are evaluated using the VIKOR method considering 10 major parameters under a Fuzzy environment. The results showed that the economic, Management, and Schedule risks are the most threatening risks of dimensional stone quarrying.

Development of a Risk Breakdown Structure in Mega Projects based on Different Case Studies

Rapid urbanization, globalization, and population growth have led to an increase in megaprojects in recent decades. Consequently, as construction projects move forward, a wider range of risks arise. By looking into and managing risk factors in advance of their occurrence, it is vital to reduce their negative effects. In construction projects, risk management is seen as a critical procedure that helps meet project objectives in relation to schedule, budget, quality, safety, and sustainability concerns. This study aims to examine and gain a deeper understanding of project-related risks in mega projects. This study also develops a risk breakdown structure in mega projects based on a literature review. This will help project participants manage these risks in their projects properly. Another objective of this study is to examine the methodologies used in data collection for determining and categorizing risks in mega projects. Finally, it is concluded that the risk factors in mega projects can be divided into two categories: internal and external risks whereas the main risk factors in mega projects are categorized as execution, construction, technical, economic and financial, environmental, social, political, and other.

Translational insights into the hormetic potential of carbon dioxide: from physiological mechanisms to innovative adjunct therapeutic potential for cancer.

Carbon dioxide (CO2), traditionally viewed as a mere byproduct of cellular respiration, plays a multifaceted role in human physiology beyond simple elimination through respiration. CO2 may regulate the tumor microenvironment by significantly affecting the release of oxygen (O2) to tissues through the Bohr effect and by modulating blood pH and vasodilation. Previous studies suggest hypercapnia (elevated CO2 levels) might trigger optimized cellular mechanisms with potential therapeutic benefits. The role of CO2 in cellular stress conditions within tumor environments and its impact on O2 utilization offers a new investigative area in oncology. This study aims to explore CO2's role in the tumor environment, particularly how its physiological properties and adaptive responses can influence therapeutic strategies. By applying a structured translational approach using the Work Breakdown Structure method, the study divided the analysis into six interconnected work packages to comprehensively analyze the interactions between carbon dioxide and the tumor microenvironment. Methods included systematic literature reviews, data analyses, data integration for identifying critical success factors and exploring extracellular environment modulation. The research used SMART criteria for assessing innovation and the applicability of results. The research revealed that the human body's adaptability to hypercapnic conditions could potentially inform innovative strategies for manipulating the tumor microenvironment. This could enhance O2 utilization efficiency and manage adaptive responses to cellular stress. The study proposed that carbon dioxide's hormetic potential could induce beneficial responses in the tumor microenvironment, prompting clinical protocols for experimental validation. The research underscored the importance of pH regulation, emphasizing CO2 and carbonic acid's role in modulating metabolic and signaling pathways related to cancer. The study underscores CO2 as vital to our physiology and suggests potential therapeutic uses within the tumor microenvironment. pH modulation and cellular oxygenation optimization via CO2 manipulation could offer innovative strategies to enhance existing cancer therapies. These findings encourage further exploration of CO2's therapeutic potential. Future research should focus on experimental validation and exploration of clinical applications, emphasizing the need for interdisciplinary and collaborative approaches to tackle current challenges in cancer treatment.

Risk Assessment of TBM Construction Based on a Matter-Element Extension Model with Optimized Weight Distribution

In order to effectively address the potential hazards associated with the construction of Phase II of the YE Water Supply Project’s KS tunnel in Xinjiang, this study employs the WBS-RBS (Work Breakdown Structure and Risk Breakdown Structure) method for risk identification. This approach aims to identify various risks that may arise during TBM (Tunnel Boring Machine) construction. To prevent incomplete risk factor identification resulting from subjective judgment, a risk index system is established based on the identification results. Subsequently, a matter-element extension model is utilized to quantify the risk factors within this index system, and comprehensive weights are determined using variable weight theory to assess construction risk levels. Importance analysis of each index is then conducted to identify those with significant impact on risk evaluation outcomes. Finally, by comparing actual engineering cases with other risk evaluation models, this paper verifies the reliability of its constructed risk assessment model and proposes measures for controlling potential risks based on these evaluations. The paper provides a clear definition of safety risks encountered during TBM construction and conducts comprehensive risk assessments as a valuable reference for research related to the tunnel boring machine construction period in tunnel engineering.

Hyundai's Modular MBSE Approach to ‘Purpose Built Vehicle’ Architecture Development

AbstractThis paper discusses an ongoing effort at Hyundai to develop a model‐based systems engineering (MBSE) methodology for cross‐domain vehicle architecture development that is practical at the enterprise level. Our approach follows a modular modeling process that complements MBSE. In the age of smart mobility, automobile systems are indeed interdependent elements of a system of systems (SoS). Connectedness favors numerous mobility features that emerge due to the interfaces among these constituent systems. Managing emergent product line variations, changing consumer demands coupled with faster market response require manufacturers to modularize their architecture development processes. This can help scale MBSE across vehicle programs. This study proposes a modular system architecture approach for developing Hyundai's purpose‐built vehicle (PBV) concept that maintains a link to the legacy vehicle breakdown structures already in use. Using the Arcadia method, the ‘to‐be’ developed electric vehicle is expressed as a hierarchical functional partitioning of the subsystem modules. A physical architecture is defined as a solution to the functional partitioning based on an existing vehicle breakdown in a combined ‘top‐down/bottom‐up’ workflow thus capturing a realistic system decomposition. In the SoS hierarchy, the PBV is at the top level and is partitioned into multiple levels of nested subsystem architectures owned and developed by designated module teams in a distributed modeling environment. Results of the preliminary architecture modularization effort indicate significant potential for benefits over classical architecture modeling such as iterative knowledge capture, enhanced reusability across projects, products and programs, and distributed vehicle performance development across the extended MBSE enterprise, which includes the tier 1/2 suppliers.

Do Algorithms Dream of Electric Requirements? Leveraging AI‐Based Approaches for Automated Allocation and Classification of Requirements in Railway Engineering

AbstractIn recent years, Artificial Intelligence has experienced an extraordinary growth. Systems Engineering is a discipline where the implementation of AI can be challenging, but that could immensely benefit from its capabilities. This paper presents one of the many implementations that AI can have within the Systems Engineering field. AI has been leveraged to create an algorithm that allows for the automatic identification and classification of requirements within a specific engineering sector: large railway projects. While text classification algorithms are well established, the key to a successful implementation of a requirements classification algorithm lays on the effective structurization of the data, as well as the high quality of the training datasets. This paper describes how an AI‐based requirements classification algorithm has been planned and trained to effectively classify requirements in future documents based on systems and subsystems from a System Breakdown Structure (SBS), as well as to predict the adequate method of verification for both the Design and Testing and Commissioning stages of a railway project.Finally, the paper showcases how the use of this AI‐based requirements classifier does not only lower the probability of human error, but also reduces ∼75% human workload per project. Additionally, overall ∼30% cost savings to organizations are expected in a 10‐year period in the task of classifying requirements with respect to manual classification performed by subject matter experts.

Public railway depot maintenance and maintenance work based on work breakdown structure (WBS) to improve maintenance and maintenance performance

Public railway depot maintenance and maintenance work based on work breakdown structure (WBS) to improve maintenance and maintenance performance

Revolutionizing Project Resilience through Advanced Risk Mitigation Strategy Launched

This study examines the risks associated with project delays in the Mover Tram rail line repair project at TMII and proposes mitigation strategies using a combination of Risk Breakdown Structure (RBS), Analytical Network Process (ANP), and Bow Tie Analysis methodologies. Through expert interviews, questionnaires, and document analysis, key risks were identified and prioritized. Results indicate that construction management emerged as the dominant risk group, with specific risks including delays in critical path tasks and discrepancies between drawings and methods. Mitigation strategies were developed focusing on these dominant risks. The study underscores the importance of integrating diverse risk assessment techniques for effective project management and suggests avenues for future research to enhance risk management frameworks in construction projects. Highlights: 1. Integrated risk analysis enhances project resilience.2. Construction management pivotal for identifying and mitigating project risks.3. Future research: Explore cost-related risks for improved project outcomes. Keywords: Project delays, Risk management, Construction projects, Mitigation strategies, Analytical methodologies

Decentralised automated BIM collaboration: a blockchain and WBS integrated platform

PurposeIn the current era of technological advancement, the architectural, engineering and construction (AEC) industry is undergoing a radical transformation, prompting researchers to explore new breakthroughs that can revolutionise the construction process. This paper delves into the use of cutting-edge technologies such as building information management (BIM), blockchain and the Internet of Things (IoT), along with advanced management techniques such as work breakdown structure (WBS) and Agile thinking, to enhance the industry’s efficiency, productivity, quality and cost-effectiveness. Moreover, the pressing need for a sustainable, secure and transparent sector amplifies the significance of the proposed research.Design/methodology/approachThis study’s research approach comprises an intensive literature review to construct a conceptual framework, followed by an exploratory questionnaire to validate the framework.FindingsThis paper demonstrates how blockchain combined with a WBS and a BIM platform may boost collaboration in order to experience efficient and trusted workflow scenarios that can overcome many of the challenges given in a traditional building technique. The research findings emphasise the benefits of the proposed new mentality approach, which incorporates all of the previously described tools/techniques to the business.Research limitations/implicationsThis paper highlights the advantages of leveraging a combination of blockchain, WBS and BIM platforms to boost collaboration and enable efficient and trustworthy workflow scenarios that can surmount the difficulties inherent in traditional AEC industry collaboration methods.Originality/valueThis study provides original insights into the challenges and opportunities of using blockchain for AEC collaboration, by exploring the potential of decentralised blockchain networks to improve the security, efficiency and transparency of collaborative data sharing and management.

Development of maintenance and care system for public railway facility infrastructure integrated with building information modeling (BIM) software based on work breakdown structure (WBS)

development of maintenance and care system for public railway facility infrastructure integrated with building information modeling (BIM) software based on work breakdown structure (WBS)

Non-targeted analysis of per- and polyfluorinated substances in consumer food packaging

This study sought to develop a non-targeted workflow using high-resolution mass spectrometry (HRMS) to investigate previously unknown PFAS in consumer food packaging samples. Samples composed of various materials for different food types were subjected to methanolic extraction, controlled migration with food simulants and total oxidizable precursor (TOP) assay. The developed HRMS workflow utilized many signatures unique to PFAS compounds: negative mass defect, diagnostic breakdown structures, as well as retention time prediction. Potential PFAS features were identified in all packaging studied, regardless of food and material types. Five tentatively identified compounds were confirmed with analytical standards: 6:2 fluorotelomer phosphate diester (6:2 diPAP) and one of its intermediate breakdown products 2H-perfluoro-2-octenoic acid (6:2 FTUCA), perfluoropentadecanoic acid (PFPeDA), perfluorohexadecanoic acid (PFHxDA) and perfluorooctadecanoic acid (PFOcDA). Longer perfluorocarboxylic acids including C17 and C19 to C24 were also found present within a foil sample. Concentrations of 6:2 FTUCA ranged from 0.78 to 127 ng g−1 in methanolic extracts and up to 6 ng g−1 in food simulant after 240 h migration test. These results demonstrate the prevalence of both emerging and legacy PFAS in food packaging samples and highlight the usefulness of non-targeted tools to identify PFAS not included in targeted methods.

Effect of Beneficiary Participation on Project Performance: A Case of an HIV Peer Education Project in Gicumbi District, Rwanda

The HIV/AIDS pandemic remains a significant global health challenge, particularly in Sub-Saharan Africa, where the prevalence rates are among the highest in the world. This study investigated the impact of beneficiary participation on the performance of an HIV peer education program implemented by the Rwanda Network of People Living with HIV (RRP+) in Gicumbi District from 2017 to 2020. Researchers examined three specific areas: project planning, implementation, and monitoring. Stakeholder and Engagement Theory alongside Participation Theory were reviewed. The study adopted a descriptive research design with qualitative and quantitative approaches. The total study population for this research was be 3,938 that included Recipients of Care (RoC) and stakeholders directly involved in the HIV peer education project implemented by the Rwanda Network of People Living with HIV (RRP+) in Gicumbi District, Rwanda, from 2017 to 2020. A mixed sampling approach was employed to select participants for this research. This approach involves a combination of probability and non-probability sampling methods. Therefore, the sample size calculated using the Yamane formula was 387 Recipients of Care (RoC) and stakeholders. Both descriptive and inferential statistics were used to analyse the data. Findings indicated significant beneficiary involvement in strategic planning and annual plans, with mean scores of 3.78 and 3.50, respectively, on a 1-4 scale. Moderate familiarity with the Work Breakdown Structure (WBS) (average 3.22) was observed. Statistical analysis confirmed a significant positive impact on Project Performance (p < 0.05). Beneficiaries reported satisfactory healthcare and psychosocial support (mean score 0.99) and moderate satisfaction with supportive supervision (mean score 1.62). Capacity-building (average 1.02) showed room for improvement, yet still had a significant positive influence on Project Performance (p < 0.05). Limited involvement in monitoring (mean score 1.04) was observed, with high satisfaction in feedback meetings (mean score 4.15). Feedback acceptability (average 3.42) indicated moderate acceptability, also positively impacting Project Performance (p < 0.05). The positive unstandardized coefficient (B) of 0.398 indicate that increased healthcare and psychosocial support are associated with higher project performance. The positive unstandardized coefficient (B) of 0.026 suggest that supportive supervision has a relatively positive relationship with project performance. The positive unstandardized coefficient (B) of 0.293 highlight the importance of training beneficiaries during project implementation. The study recommended foster greater beneficiary involvement in project planning by conducting regular consultations, workshops, and feedback sessions. Review and refine the supportive supervision approach to address the varying levels of satisfaction among beneficiaries. Maintain regular and productive feedback meetings to capture beneficiary input and concerns. Enhance feedback collection and analysis processes to ensure feedback is incorporated into project activities effectively. Form a strengthened system of monitoring and evaluation in order to consistently evaluate performance of project as well as adapt to evolving requirements of the beneficiary. Additionally, formulate models of sustainability to ascertain that favorable and positive impacts of the project are preserved after its overall completion.

Preliminary Estimation for Software Development Projects Empowered with a Method of Recommending Optimal Duration and Team Composition

In the early software development stages, the aim of estimation is to obtain a rough understanding of the timeline and resources required to implement a potential project. The current study is devoted to a method of preliminary estimation applicable at the beginning of the software development life cycle when the level of uncertainty is high. The authors’ concepts of the estimation life cycle, the estimable items breakdown structure, and a system of working-time balance equations in conjunction with an agile-fashioned sizing approach are used. To minimize the experts’ working time spent on preliminary estimation, the authors applied a decision support procedure based on integer programming and the analytic hierarchy process. The method’s outcomes are not definitive enough to make commitments; instead, they are supposed to be used for communication with project stakeholders or as inputs for the subsequent estimation stages. For practical usage of the preliminary estimation method, a semistructured business process is proposed.

A Work Breakdown Structure for Estimating Building Life Cycle Cost Aligned with Sustainable Assessment—Application to Functional Costs

The tools used for budgeting in the building design phase are still insufficient to address the life cycle of the building in terms of environmental and cost impacts. The main objective of this research is to define a model for extending existing cost databases to accommodate life cycle sustainability assessment. For this, current classification systems are reviewed and a case study has been analysed using the new approach. To this end, a new system of classification of construction information is proposed for the evaluation of early design costs, when data are scarce and the only information available refers to the gross interior area and the plot. The classification organizes the costs in a similar way to the sustainability assessment in EN-15643. A subcategory has been added for revenue, developer costs, and taxes at all stages of the lifecycle. The resulting classification is applied to the functional elements of a secondary school project. In the case study, construction costs represent 21% while the use stage accounts for 72% in a 100-year lifespan. The results show that, starting from generic cost bases, more complex costs and functional costs can be defined at different stages of the life cycle and adjusted to sustainability assessment standards.

Safety Risk Analysis of Urban Viaduct Construction Based on Dynamic Weight

The safety risk analysis of urban elevated bridge construction is an important management method to reduce the loss of safety accidents, and it has significant scientific research value and engineering application value. Therefore, this study proposes a novel analysis method to address these challenges. Firstly, this paper constructs a Work Breakdown Structure (WBS)–Risk Breakdown Structure (RBS) matrix for the safety risk of urban elevated bridge construction in order to achieve a comprehensive and complete identification of the indicator system. Then, a combination of static weights and dynamic weights calculation methods is developed. The static weights are obtained using the analytic hierarchy process, while the dynamic weights are obtained based on the relationship between the dynamic scores of construction safety risk indicators in different construction stages and the preset evaluation levels. Finally, a case study of the Longlingshan elevated bridge project in Wuhan, China, is conducted to validate the feasibility of the proposed model and its potential application in projects. The case analysis for the first time reveals that with the progress of construction, the weights of each indicator continuously change, and the secondary indicators related to environmental factors, such as extreme high-temperature weather, undergo the greatest changes. A comparison of different dynamic weight calculation methods is conducted to highlight the advancement of the proposed model. The research findings of this paper will provide new insights and guidance for improving the construction safety of urban elevated bridge projects.

An MCDM Approach for Evaluating Construction-Related Risks using a Combined Fuzzy Grey DEMATEL Method

There is a need for more research into prioritizing project risks based on a sound technique due to the complicated and disorganized character of this stage. The project risk management process typically begins with the identification of critical hazards. This study presents a Grey Fuzzy Decision-Making Trial and Evaluation Laboratory (FGDEMATEL) approach to prioritize potential causes of project risks within Multi-Criteria Decision-Making (MCDM). This framework organizes the numerous risks using the Risk Breakdown Structure (RBS) of the Project Management Institute (PMI). The risk information used in this analysis comes mostly from the views and choices of project experts. Grey theory, which takes language phrases for preference collections and translates them into numerical intervals, is responsible for controlling uncertainty and variance in experts' preferences. As each expert has unique skills and experiences, it evaluates the significance of their opinions using a fuzzy number system that incorporates three dimensions. In the end, the FGDEMATEL approach devised a method to rank various project risks.