Search Results (9)

Proper management of vehicle structural factors related to public transportation safety is vital to formulate maintenance strategies and to enhance transportation safety. Therefore, this work aims to comprehensively identify potential structural factors, assess their impacts as regards causing public transportation vehicle malfunctions, and understand their cause–effect interrelationships. Maintenance management can be improved based on the analysis outcomes. Multi-Criteria Decision-Making (MCDM) techniques are widely applied to decision-making problems. However, due to the advanced and complex structures of modern vehicles, conventional single-used MCDM techniques encounter limitations in their ability to thoroughly account for all potential failure factors and to systematically manage the causal interrelationships, which makes the analysis results less practically applicable. To overcome these challenges, this article proposes an innovative MCDM framework. Specifically, Failure Tree Analysis (FTA) and the Interval-Valued Pythagorean Fuzzy Analytic Hierarchy Process (IVPF-AHP) are integrated to construct the logical relationships between the failure structural factors from real-world maintenance records. The factors are ranked and selected based on their severity influence and occurrence likelihood influence. Subsequently, the Interval-Valued Pythagorean Fuzzy Decision-Making Trial and Evaluation Laboratory (IVPF-DEMATEL) takes causal diagrams to identify interdependencies between the factors based on the mitigated ambiguity of human assessments. A case study in the public transportation bus domain is conducted to demonstrate the effectiveness of the proposed MCDM framework. The results offer insightful maintenance suggestions for public transportation operators and engineers to save human labor and material resources. Full article

Off-site construction (OFC) is a hot topic to remedy the chronic issues of the construction industry, such as low levels of productivity, waste, safety risks, environmental pollution, poor quality, and time and cost issues. However, the lack of standards and knowledge about OFC projects hamper the adaptation process. Disputes are one of the most important hampering factors. Therefore, this study aims to identify contractual and financial disputes and to detect the importance level of disputes in OFC projects. In the study, the Focus Group Discussion (FGD) technique, Pythagorean fuzzy AHP, and fuzzy TOPSIS were employed. As a result of FGD, 42 dispute causes for off-site construction projects were found. The Pythagorean fuzzy AHP method was used to calculate the weights of the criteria (occurrences, severity, and detection) that were used in the evaluation of dispute causes. The Pythagorean fuzzy AHP analysis results indicated that “detection” is more important than other criteria in the evaluation of off-site construction dispute causes. After that, the fuzzy TOPSIS method was used to determine the importance level of off-site construction dispute causes. The analysis results showed that “Increase in contract value due to revision in scope of work” in the contractual factor group and “Extra money for the additional works” in the financial factor group are the most important dispute causes, respectively. The study findings can be used for the evaluation and analysis of OFC project contracts. Full article

Mining is a high-risk industry where occupational accidents are common due to its complex nature. Therefore, providing a more holistic and dynamic risk assessment framework is essential to identify and minimize the potential risks and enhance safety measures. Unfortunately, traditional risk assessment methods have limitations and shortcomings, such as uncertainty, differences in experience backgrounds, and insufficiency to articulate the opinions of experts. In this paper, a novel risk assessment method precisely for such cases in the mining sector is proposed, applied, and compared with traditional methods. The objective of this study is to determine the risk scores of Turkish Coal Enterprises, based on non-fatal occupational accidents, which operates eight large-scale open-cast coal mine enterprises in Türkiye. The causes of the accidents were categorized into 25 sub-criteria under 6 main criteria. The risk scores for these criteria were computed using the Pythagorean fuzzy Analytical Hierarchy Process (PFAHP) method. The first shift (8–16 h) (0.6341) for the shift category is ranked highest out of the 25 sub-risk factors, followed by maintenance personnel (0.5633) for the occupation category; the open-cast mining area (0.5524) for the area category, the 45–57 age range (0.5279) for employee age category, and the mining machine (0.4247) for the reason category, respectively. The methodologies proposed in this study not only identify the most important risk factors in enterprises, but also provide a mechanism for risk-based rankings of enterprises by their calculated risk scores. The enterprises were risk-based ranked with the fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) method and Paksoy approach based on interval type-2 fuzzy sets (IT2FSs). The findings indicate that the first three risk score rankings of enterprises are the same for both approaches. To examine the consistency of the applied methods, sensitivity analyses were performed. The results of the study also indicate that the proposed approaches are recommended for effective use in the mining sector due to their ease of application compared to other methods and their dynamic nature in the risk assessment process. Full article

An integral aspect of global businesses and economic activities is the supply chain networks. Importantly, the coronavirus (COVID-19) pandemic scenario has further shown that the outbreak of diseases can create a global network-scale disruption to supply chain or logistics, thereby damaging several aspects of economic activities and business life. Hence, this study aims to assess the resilient supplier selection (RSS) process in the wake of the COVID-19 outbreak. A two-stage hybrid decision model using Pythagorean fuzzy sets was proposed as a case study from the automotive industry to deal with RSS during the COVID-19 outbreak. In the first stage, significant criteria and their corresponding sub-criteria were determined through a vast review of the literature and nominal group technique, while the relative weights for RSS were obtained through the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) method. In the second stage, nine suppliers were evaluated with Pythagorean Fuzzy VIKOR (PFVIKOR) method. The results of the hybrid approach revealed that flexibility is the most important criterion among resilience criteria that constitute the most significant dimensions for RSS. In many studies, strategic criteria such as quality, cost, and delivery are found to be the most important criteria in supplier selection, however, in the wake of the COVID-19 outbreak, the opinions of decision-makers were significantly changed as the present study reveals that flexibility is the most important criterion to improve the operations of the supply chain for RSS. Next to flexibility is process capabilities, while quality (Q), and cost (C) existed as the first and second in the category of influential criteria for strategic supplier selection criteria, respectively. The managerial and practical implication is that, in the wake of COVID-19 disruptions, suppliers need to be re-evaluated based on resilience-related indicators. Full article

Blockchain technology has emerged as a promising solution to enhance supply chain transparency and sustainability in the construction industry. However, the widespread adoption of blockchain faces several barriers that need to be identified and understood. The construction industry faces significant challenges regarding supply chain transparency and sustainability. Current practices lack visibility, leading to difficulties in tracing material origins, tracking movement, and ensuring compliance. To fill this gap, this study employed a three-phase approach. In the first phase, a comprehensive literature review identified 37 potential barriers. Subsequently, expert discussions were held to refine the list, ultimately selecting 15 barriers of utmost importance. In the second phase, data were collected from 17 experts representing academia and industry. Finally, in the last phase, the collected data were analyzed using the Pythagorean fuzzy analytical hierarchical process (AHP) methodology. The findings revealed that the “transparency range” category was the most critical barrier, closely followed by “inadequate access to institutional finance”. Surprisingly, the study identified the “security environment” as the most significant barrier. These results offer construction companies, policymakers, and other industry stakeholders a comprehensive understanding of blockchain adoption’s challenges. With this knowledge, stakeholders can design effective strategies and policies to address these barriers. Moreover, the research highlights the importance of considering uncertainty in decision making when assessing technology adoption, making the findings applicable beyond the construction industry. Full article

In construction projects, a significant part of construction work is done by subcontractors (SCs). Therefore, their management by main contractors (MCs) becomes an important issue as the density of SCs is created at the construction sites. In recent years, more focus on SC evaluation and selection in bidding process has been on the agenda whereas the subject of SC performance appraisal on-site during the project execution phase has been untended in the literature. Thus, this study aims to focus on the measurement and evaluation of the performance of SCs in the project execution phase, and to provide a tentative performance-based dynamic management framework that MCs will use in the management of SCs in order to take proactive measures. In line with the aim, a total number of 23 performance measurement criteria (PMC) under 7 main groups were determined as a result of a comprehensive literature review and expert evaluations. Knowing that not every criterion will have the same effect in performance measurement, pairwise comparisons of the criteria were made using the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) method and their importance weights were determined. The PFAHP method was obtained by integrating the Pythagorean fuzzy set into the AHP method and chosen with the aim of improving the fuzzy AHP method and obtaining more consistent results by eliminating the uncertainty since Pythagorean fuzzy sets is more capable than fuzzy sets at expressing and handling uncertainty in uncertain environments. Lastly, a framework for SC performance measurement and evaluation on project execution phase is presented. It is believed that the presented framework will allow for a proactive management style that will enable effective decisions to be made while the project is ongoing, and a dynamic way of working instead of static and conventional work. Full article

Buildings can be made more user-friendly and secure by putting “smart” design strategies and technology processes in place. Such strategies and processes increase energy efficiency, make it possible to use resources rationally, and lower maintenance and construction costs. In addition to using wireless technologies and sensors to improve thermal, visual, and acoustic comfort, “smart” buildings are known for their energy, materials, water, and land management systems. Smart buildings use wireless technologies and sensors to improve thermal, visual, and acoustic comfort. These systems are known for managing energy, materials, water, and land. The task of the study is to consider the indicators that form the basis of the framework for evaluating intelligent buildings. The indicators for the development of “smart” buildings are classified into six categories in this paper: green building construction, energy management systems, safety and security management systems, occupant comfort and health, building automation and control management systems, and communication and data sharing. The paper aims to develop a scoring model for the smartness of public buildings. In developing the scoring system, the decision-making process requires an appropriate selection of the optimal solution. The contents of the research are the methods known as the Pythagorean Fuzzy Analytic Hierarchy Process (PF-AHP), Interval Valued Pythagorean Fuzzy AHP with differences (IVPF-AHP d), and the proposed method Interval Valued Pythagorean Fuzzy AHP (IVPF-AHP p). The research focuses on the IVPF-AHP as one of the methods of Multi-Criteria Decision-Making (MCDM) and its implementation. The comparative analysis of the three presented methods indicates a significant degree of similarity in the ranking, which confirms the ranking similarity. The results highlight the importance of bioclimatic design, smart metering, ecological materials, and renewable energy systems. Full article

Single-minute exchange of dies (SMED) is one of the most significant lean tools which reduces the required time for setup operations. The consideration of appropriate ergonomic interferences during the SMED implementation improves working conditions, productivity, and flexibility. The SMED literature has an opportunity for expansion with ergonomic assessment. Moreover, ergonomic assessment studies have various limitations in terms of a broad hierarchy of ergonomic factors and their weighting. Therefore, this study enriches the literature by providing the ergonomic assessment of the setup process through integrating multi-criteria decision-making (MCDM) into SMED. In this context, a wide hierarchy of ergonomic risk factors is compiled for ergonomic assessment. The Interval Valued Pythagorean Fuzzy Analytic Hierarchy Process (IVPF-AHP) method is used to determine the weights of factors. Then, Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used to prioritize setup tasks in terms of ergonomic factors by using the Interval Valued Pythagorean Fuzzy Sets (IVPFSs). The proposed model was validated by applying it to a real-life manufacturing system in the white goods supplier industry. The application results justify the proposed model with a setup time reduction of 58% and an ergonomic improvement of 19%. Full article

Human behavior has been estimated as a factor too uncertain and complex to investigate road safety issues. By utilizing recent expansions of ordinary fuzzy sets, experts in the field have intended to handle the vagueness of human behavior in sustainable transport systems by using linguistic terms for assessment. Pythagorean Fuzzy sets (PFSs) are considered a superior method that has been developed for multi-criteria decision-making (MCDM), which enables assigning of both membership and non-membership functions in a large domain area. A novel Pythagorean Fuzzy Analytic Hierarchy Process (PF-AHP) is performed to assess and prioritize critical driver behavior criteria designed into a hierarchical model based on data gathered from observed driver groups in Budapest city. Accordingly, based on the aggregated weights, the criterion ‘lapses’ is prioritized as the most critical factor connected to road safety. The criterion ‘disobey speed limits’ is found to be the least critical factor, followed by ‘disobey overtaking rules’ as the second least. For a comparative analysis, the case of dependent criteria has been considered. Pythagorean Fuzzy DEMATEL method has been applied to determine dependencies between the criteria. Through the dependencies, a network of criteria has been constructed and the Pythagorean Fuzzy Analytic Network Process (ANP) conducted to interpret the results. Moreover, sensitivity analyses have been carried out to examine its robustness by applying different case scenarios. Full article