Search Results (21)

Fault risks in marine diesel engines (MDEs) propagate across coupled subsystems and evolve with component degradation, but existing methods rarely integrate accident narratives, causal structure, and time-varying reliability. This study develops a novel framework that integrates large language models (LLMs), rough–fuzzy DEMATEL, interpretive structural modeling (ISM), and Bayesian networks (BNs) with service-time-dependent priors for time-varying failure analysis. First, the risk-influencing factors (RIFs) are extracted from accident and maintenance records using LLMs, text embeddings, semantic clustering, and expert consolidation. Rough–fuzzy DEMATEL and ISM are used to identify causal relationships and the hierarchical structure. The RIFs, bottom-level components, and target failure are then mapped into a multilayer BN parameterized using Noisy-OR relationships and Weibull-derived time-varying priors. In a case study of MDE hard starting, 338 cause descriptions from 35 records yielded 12 RIFs, with semantic coverage above 93% across four evaluation models. When hard starting was observed, the posterior probability of mechanical failure of the fuel injection system reached 60.92%, compared with 36.91% for governor and mechanical actuation system failure. Over 0–10,000 h of cumulative service, the model-inferred probability of hard starting during a single starting attempt increased from 38.09% to 75.23% under the specified model parameterization. The framework supports causal interpretation, troubleshooting prioritization, and service-time-dependent maintenance prioritization. Full article

Failure Mode and Effect Analysis (FMEA) is a widely applied preventive risk assessment approach to enhance product reliability and safety, yet its structural validity is frequently questioned. Existing improvement models generally overlook the interrelationships among failure modes and suffer from high uncertainty and instability in opinion aggregation, risk factor weight allocation, and Risk Priority Number (RPN) computation. To bridge these gaps, this study proposes an integrated decision-making model. First, the Decision Making and Trial Evaluation Laboratory (DEMATEL) method is employed to analyze interactions among failure modes, constructing an influential network diagram to identify critical items. Second, a Rough Dombi Aggregator is applied for opinion aggregation, minimizing data loss and handling uncertainties from experts’ diverse backgrounds. Third, the Full Consistency Method (FUCOM) is utilized to determine the relative weights of risk factors. Finally, four weighted aggregation methods are developed to calculate RPNs, mitigating the instability common in traditional methods. This vehicle power system case study, alongside model comparison and sensitivity analysis, demonstrates the model’s effectiveness and robustness. The results indicate that across 9 different weight fluctuation scenarios, the core high-risk item “FM₇: Generator coil burned out due to short circuit” consistently ranks 1st. This highlights the exceptional stability of the proposed model in overcoming evaluation fluctuations. Ultimately, this integrated framework not only enhances the accuracy and robustness of failure mode prioritization but also serves as a valuable practical reference for engineers formulating preventive maintenance strategies under limited resources. Full article

Sustainable supplier selection (SSS) is an essential part of the decision-making process in sustainable supply chains. Numerous research studies have been conducted using various decision-making methods to attend to this research-worthy issue. This literature review presents a comprehensive SSS analysis focusing on social, economic, and environmental aspects. The present study spans five years (2018–2022) and considers 101 papers. It provides a detailed breakdown of the papers based on their dates of publication, the countries of the writers, application fields, and journals, and it categorizes them based on their approaches. In addition, this review examines the use of single- or hybrid-form methodologies in the papers reviewed. It also identifies that the TOPSIS, AHP, VIKOR, BWM, DEA, DEMATEL, and MULTIMOORA methods and their extensions are the most frequently used methods in SSS studies. It is concluded that hybrid approaches and their rough, grey, and fuzzy extensions are used to solve real-world problems. However, state-of-the-art mathematical tools, such as soft sets and their hybrid versions with fuzzy sets, have not been utilized in SSS studies. Therefore, this study inspires and encourages the use of such tools in SSS research. Full article

Using green energy is an important way for businesses to achieve their ESG goals and ensure sustainable operations. Currently, however, green energy is not a stable source of power, and this instability poses certain risks to normal business operations and manufacturing processes. The installation of energy storage equipment has become an indispensable accompaniment to facilitating green energy use for an enterprise. However, businesses may encounter significant barriers during the process of installing energy storage equipment. This study aims to explore and discern the key barrier factors that influence the assessment and decision-making process of installing energy storage equipment. A hybrid approach combining the Decision-making and Trial Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) is developed to explore the causality relationships and degrees of influence among these key factors. The Z-number and Rough Dombi Weighted Geometric Averaging (RDWGA) methods are also utilized to integrate the experts’ varied opinions and uncertain judgements. Finally, recommendations are provided based on the results to assist businesses to make informed decisions while evaluating the installation of energy storage equipment, to ensure a stable and uninterrupted supply of green energy for use in normal operations. Full article

3D printing technology is suitable for application in advancing digitization in dentistry. However, the use of this technology in the dental field is not as widespread as expected. The study discusses the barriers to advancing 3D printing technology in dentistry. First, Fuzzy Delphi was used to conduct in-depth interviews with experts to explore what barriers prevent the advancement of 3D printing technology in dentistry. Second, the decision-making and trial assessment laboratory (DEMATEL) was used to identify the cause-and-effect relationship among barriers. Because DEMATEL relies on the expert decision-making system, experts often have different experiences and backgrounds, so judgment results are often uncertain and inconsistent. Therefore, this study proposes using a rough-Z-number to integrate opinions among experts, which can effectively overcome the problems of inconsistency and uncertainty. After analyzing the results, we found that “lack of standard infrastructure” is the most important barrier to the advancement of 3D printing in dentistry, and this study provides improvement strategies based on the results. The results put forward countermeasures for the barriers to the promotion of 3D printing technology in dentistry, which will make the development of dental digitization more effective. Full article

Increasing environmental awareness and stringent environmental norms of developed countries have demanded eco-friendly industrial practices from the leather industry. On the path to achieving sustainable development goals (SDGs), the concept of circular bio-economy (CBE) practices has gained significant attention from the leather industry with regards to waste management. CBE practices encourage the potential of recovering value from leather waste. However, the CBE concept has not been well received by the leather industries of developing countries for various reasons. Hence, this study aims to identify and evaluate various barriers to CBE practices from the context of the Indian leather industry. Twenty-five barriers to CBE practices in the leather industry are identified through literature review and interaction with managers. Then, a rough decision-making trial and evaluation laboratory (R-DEMATEL) was utilized to reveal the interrelationships among the barriers to CBE practices. Restrictiveness to change, difficulty in forming a reliable supplier network, difficulty in developing customers, lack of vision, and unclear and partial understanding of the CBE concept have been identified as the five most critical barriers to CBE practices in the leather industry. Furthermore, in the current study, nine barriers fall into the cause group and sixteen barriers fall into the effect group. The outcome of the study reveals the causal interrelationships among the barriers to CBE practices to the industrial management and policymakers. This study is the first of its kind to analyze the barriers to CBE practices in the Indian leather industry context. Full article

The proliferation of sustainability reporting (SR) is in response to environmental and social responsibility, but investors are increasingly concerned over the effects of sustainability reporting in corporate sustainability. The Sustainability Accounting Standard Board (SASB)’s sustainability standards are acknowledged as the main framework for implementing this activity, yet the influencing factors among sustainability reports highly correlate and are diverse and complicated, especially in the semiconductor industry, which is the key driving force for economic development in China. To exploit and evaluate those key factors, this research introduces a hybrid model that integrates fuzzy rough set theory with particle swarm optimization (FRST-PSO) and a fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL). FRST-PSO is adopted to filter out redundant and irrelevant factors, and the selected results are then inserted into fuzzy DEMATEL to depict the opaque relationships and set up a prioritization strategy for improvement among the factors. According to the findings on the magnitude of the impact, the priorities for improvement are environment, human capital, social capital, leadership and governance, and business model and innovation. Based on the results, an optimal and practical solution is proposed as the basis for information disclosure of sustainability reporting for the semiconductor industry. Full article

Infrastructure systems, such as bridges, are perpetually vulnerable to natural hazards such as seismic events, flooding, and landslides. This study aims to determine the relevant parameters required to increase the seismic resilience of bridge infrastructure based on the decisions of experts and prior research. To this end, the crisp DEMATEL (decision-making and trial evaluation laboratory) and rough DEMATEL methods are employed. Rough DEMATEL is a supplement to crisp DEMATEL that incorporates rough theory to handle ambiguity. The efficacies of the rough and crisp DEMATEL methods are then compared between the two approaches. This study found the most crucial seismic-resilience variables for bridges. The outcomes of this study reveal the significant order and cause-and-effect relationships. This research can assist transportation engineers and executive agencies in enhancing the seismic resilience of roadway bridges and bridge networks. Full article

To effectively quantify and control the credit risk of forest farmers under internet crowdfunding mode, the combined weighting of norm grey correlation, the improved analytic hierarchy process and empirical mode decomposition method are proposed to measure the credit risk, and the interval rough number DEMATEL method is used to analyze the credit risk factors of forest farmers. Through the calculation of comprehensive influence degree, it is concluded that the degree of investor information asymmetry, the intensity of supervision, the degree of innovation and cooperation between funders and investors are the main credit risk factors of forest farmers under internet crowdfunding mode, and a credit risk control mechanism is constructed according to the main credit risk factors to effectively improve the risk management and control level of forest farmers. Full article

Failure mode, effects and criticality analysis (FMECA) is a well-known reliability analysis tool for recognizing, evaluating and prioritizing the known or potential failures in system, design, and process. In conventional FMECA, the failure modes are evaluated by using three risk factors, severity (S), occurrence (O) and detectability (D), and their risk priorities are determined by multiplying the crisp values of risk factors to obtain their risk priority numbers (RPNs). However, the conventional RPN has been considerably criticized due to its various shortcomings. Although significant efforts have been made to enhance the performance of traditional FMECA, some drawbacks still exist and need to be addressed in the real application. In this paper, a new FMECA model for risk analysis is proposed by using an integrated approach, which introduces Z-number, Rough number, the Decision-making trial and evaluation laboratory (DEMATEL) method and the VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method to FMECA to overcome its deficiencies in real application. The novelty of this paper in theory is that the proposed approach integrates the strong expressive ability of Z-numbers to vagueness and uncertainty information, the strong point of DEMATEL method in studying the dependence among failure modes, the advantage of rough numbers for aggregating experts’ diversity evaluations, and the strength of VIKOR method to flexibly model multi-criteria decision-making problems. Based on the integrated approach, the proposed risk assessment model can favorably capture and aggregate FMECA team members’ diversity evaluations and prioritize failure modes under different types of uncertainties with considering the failure propagation. In terms of application, the proposed approach was applied to the risk analysis of failure modes in offshore wind turbine pitch system, and it can also be used in many industrial fields for risk assessment and safety analysis. Full article

Massive open online courses (MOOCs) have become a mainstream form of online learning. At present, various countries are vigorously developing MOOC platforms, which provide a helpful platform for people to acquire knowledge and skills. However, the quality of each MOOC platform is different, which is a challenge for learners seeking excellent courses. Since the evaluation of MOOC quality is a multiple criteria decision-making issue, it is important to find the major dimensions and criteria that determine the quality of platforms. This paper determines the weight of each dimension and criterion by using the best worst method (BWM). The results indicate that content accuracy has the greatest impact on MOOC quality. This paper selected five well-known domestic MOOC websites as research objects and used the VIKOR analysis method to rank the platform quality of the five chosen websites. The results show that IMOOC and Xuedong are ranked as the top two websites. This research result helps learners deepen their understanding of MOOC platforms and can serve as a reference for MOOC platforms to improve their quality. Techniques to reduce the uncertainty of expert judgments (such as rough sets, fuzzy theory, grey correlation, etc.) and models that clarify the influence relationship between criteria (DEMATEL-ANP) can be applied in future research. Full article

The main aim of this study is to identify the most important natural gas pipeline failure causes and interrelation analysis. In this research, the rough analytic hierarchy process (Rough-AHP) is used to identify the natural gas pipeline failure causes rank order. Then a combination of rough decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) method is applied to generate the level of importance. The comparison of traditional DEMATEL and Rough-DEMATEL are also performed to establish the cause-effect interrelation diagram. Finally, the Bayesian Belief Network (BBN) is combined with Rough DEMATEL and ISM to identify the interrelation analysis among the most crucial failure causes. As a result, the energy supply company and government policymaker can take necessary safety plan and improve the operation. The main outcome of this study is to improve the security management and reduce the potential failure risks. Full article

In competitive global markets, sustainable suppliers are critical success factors for sustainable supply chain operations. Sustainable supplier selection must be based on a complex network of numerous indicators and experts’ fuzzy linguistic terms. Considering the correlation between the evaluation criteria and the ambiguity of the criteria values, this paper proposes combining the rough DEMATEL method and the fuzzy VIKOR (FVIKOR) method to solve sustainable supplier selection problem. We determine 15 sustainable supplier evaluation criteria from economic, environmental and social dimensions. We also apply the rough DEMATEL method to determine the weight of evaluation indicators that are interrelated or even conflicting and use the FVIKOR method to determine supplier rankings by converting the fuzzy linguistic terms into precise information. The practicability of the proposed method is verified by an example of sustainable supplier selection. Full article

Many countries advocate sports for all to cultivate people’s interest in sports. In cities, cross-industry alliances between sports and tourism are one of the common practices. The following two important issues need to be discussed, namely, what factors should be paid attention to in the development of sports tourism, and what are the mutual influential relationships among these factors. This study proposes a novel two-stage multi-criteria decision-making (MCDM) model to incorporate the concept of sustainable development into sports tourism. First, the Bayesian best–worst method (Bayesian BWM) is used to screen out important criteria. Bayesian BWM solves the problem of expert opinion integration of conventional BWM. It is based on the statistical probability to estimate the optimal group criteria weights. Secondly, the rough decision making trial and evaluation laboratory (rough DEMATEL) technique is used to map out complex influential relationships. The introduction of DEMATEL from the rough set theory has better practicality. In the calculation program, interval types are used to replace crisp values in order to retain more expert information. A city in central Taiwan was used to demonstrate the effectiveness of the model. The results show that the quality of urban security, government marketing, business sponsorship and mass transit planning are the most important criteria. In addition, in conjunction with local festivals is the most influential factor for the overall evaluation system. Full article

Improving the quality of research information systems is an important goal in the process of improving the performance of research management in Chinese universities. Since the evaluation of information system (IS) quality is a multicriteria decision problem, it is critical to identify the interrelationships among the dimensions and criteria, and decide on the important criteria for proposed improvement strategies. This paper suggests a hybrid multicriteria decision-making (MCDM) model for improving the quality of a research information system. First, a rough method combined with the decision-making trial and evaluation laboratory and analytical network process (rough DANP) model is used to improve the objectivity of expert judgements. Additionally, the rough DANP can be used to construct an influential network relationship map (INRM) between research information system components to derive the criterion weights. The complex proportional assessment of alternatives with rough numbers (COPRAS-R) is applied to evaluate the performance of the research information system. A Chinese university research information system is chosen to illustrate the usefulness of the proposed model. The results show that efficiency, effectiveness, and user frequency have the highest priorities for improvement. Selected management implications based on the actual case study are supplied. Full article