•This paper provides a systematic review of researches on FMEA improvement.•A set of 236 journal articles published between 1998 and 2018 was identified.•Bibliometric analysis was conducted to ...provide insights into the research theme.•Research gaps and opportunities on the improvement of FMEA are identified.
Failure mode and effects analysis (FMEA) is a reliability management technique commonly utilized in various industries to guarantee the security and reliability of systems, services and projects. Nonetheless, the classical risk priority number (RPN) method has been criticized for many inherent deficiencies in the literature. Over the last decades, plenty of models and approaches have been employed to enhance the inherent characteristics of FMEA, but few contributions are devoted to review and summarize the related researches on FMEA improvement. Therefore, this paper aims to conduct a systematic review of the journal articles on the topic during the years between 1998 and 2018. A metadata statistical analysis is undertaken to present an overview of publication distribution across time and journals. Besides, a bibliometric analysis is performed to identify the most influential authors, institutions and areas, reveal the research hotspots and give an insight into the theme evolution in this field. The results indicated that the annual publications on FMEA improvement are rising quickly in the past two decades, especially after 2013; Liu HC, Chang KH, Kumar D, Sharma RK and You JX are the most prolific researchers; and Asian especially China is the major contributor in this field. Moreover, “healthcare failure mode”, “risk ranking”, “extended FMEA”, “gray theory”, “risk evaluation”, and “fuzzy inference” are the research focuses in improving the traditional FMEA.
Failure mode and effect analysis (FMEA) is a systematic, multidisciplinary team-based risk management tool used in diverse industries to help improve the safety and reliability of systems, designs, ...processes and/or services. However, the traditional FMEA method, when applied in real situations, shows some important drawbacks regarding failure mode evaluations, risk factor weights and risk priority ranking, etc. In this paper, we aim to develop an integrated risk prioritization approach to improve the performance of FMEA by using interval-valued intuitionistic fuzzy sets (IVIFSs) and the multi-attributive border approximation area comparison (MABAC) method. Moreover, a linear programming model is developed to obtain the optimal weights of risk factors when the weight information is incompletely known a priori. Finally, a practical example is presented to illustrate the applicability and effectiveness of the proposed FMEA, and results show that the new integrated approach offers a useful and reliable tool for rational criticality analysis.
•This study proposes a new risk priority model to improve the traditional FMEA.•Diversified assessments of experts are handled by interval-valued intuitionistic fuzzy sets.•An extended MABAC method is presented for ranking failure modes.•A linear programming model is used to determine risk factor weights with partial information.•The advantages of the new model are illustrated with a healthcare risk analysis case.
Microbially mediated anaerobic oxidation of methane (AOM) is a key process in the regulation of methane emissions to the atmosphere. Iron can serve as an electron acceptor for AOM, and it has been ...suggested that Fe(III)-dependent AOM potentially comprises a major global methane sink. Although it has been proposed that anaerobic methanotrophic (ANME) archaea can facilitate this process, their active metabolic pathways have not been confirmed. Here we report the enrichment and characterisation of a novel archaeon in a laboratory-scale bioreactor fed with Fe(III) oxide (ferrihydrite) and methane. Long-term performance data, in conjunction with the
C- and
Fe-labelling batch experiments, demonstrated that AOM was coupled to Fe(III) reduction to Fe(II) in this bioreactor. Metagenomic analysis showed that this archaeon belongs to a novel genus within family Candidatus Methanoperedenaceae, and possesses genes encoding the "reverse methanogenesis" pathway, as well as multi-heme c-type cytochromes which are hypothesised to facilitate dissimilatory Fe(III) reduction. Metatranscriptomic analysis revealed upregulation of these genes, supporting that this archaeon can independently mediate AOM using Fe(III) as the terminal electron acceptor. We propose the name Candidatus "Methanoperedens ferrireducens" for this microorganism. The potential role of "M. ferrireducens" in linking the carbon and iron cycles in environments rich in methane and iron should be investigated in future research.
Cu
2
Se is a p-type semiconducting compound that possesses excellent thermoelectric properties which exhibit great potential for practical applications. In recent years, there have been many ways to ...improve thermoelectric properties. Reducing the thermal conductivity is a very effective way to obtain high performance thermoelectric materials. In this study, a series of Cu
2−
x
Li
x
Se (
x
= 0, 0.01, 0.02 and 0.03) polycrystalline bulk samples were successfully prepared by hot-pressing the nanopowders made by hydrothermal synthesis to investigate the doping effects of Li on the phase structure, microstructure and thermoelectric properties of Cu
2
Se. Compared with the Li-free Cu
2
Se, the introduction of Li element increases the Seebeck coefficient. Importantly, both nanopores and Li substitution were observed which can reduce
κ
L
via
increased scattering phonons. At 973 K, the Cu
1.98
Li
0.02
Se sample presented an excellent
ZT
of 2.14.
Cu
2
Se is a p-type semiconducting compound that possesses excellent thermoelectric properties which exhibit great potential for practical applications.
Nowadays, failure mode and effect analysis (FMEA) is a widely used reliability analysis technique for products, processes, and services because of its relative simplicity. The conventional risk ...priority number method, however, has been criticized as having many limitations, such as in the assessment of failure modes, the weighting of risk factors, and the prioritization of failure modes. In this paper, we aim to develop a new risk priority model for FMEA by integrating hesitant 2-tuple linguistic term sets and an extended QUALIFLEX approach. The concept of hesitant 2-tuple linguistic term sets is first presented to express various uncertainties in the assessment information of FMEA team members. Borrowing the idea of grey relational analysis, a multiple objective optimization model is constructed to determine the relative weights of risk factors with incomplete weight information. The extended QUALIFLEX approach with an inclusion comparison method is then suggested to determine the risk ranking of failure modes identified in FMEA. Finally, the practicality and effectiveness of the proposed FMEA are demonstrated through a case study, and the results show that the new risk priority approach is useful and flexible for handling complicated FMEA problems and can yield a reasonable and credible priority ranking of failure modes.
The C‐REPEAT‐BINDING FACTOR (CBF) pathway has important roles in plant responses to cold stress. How the CBF genes themselves are activated after cold acclimation remains poorly understood. In this ...study, we characterized cold tolerance of null mutant of RNA‐DIRECTED DNA METHYLATION 4 (RDM4), which encodes a protein that associates with RNA polymerases Pol V and Pol II, and is required for RNA‐directed DNA methylation (RdDM) in Arabidopsis. The results showed that dysfunction of RDM4 reduced cold tolerance, as evidenced by decreased survival and increased electrolyte leakage. Mutation of RDM4 resulted in extensive transcriptomic reprogramming. CBFs and CBF regulon genes were down‐regulated in rdm4 but not nrpe1 (the largest subunit of PolV) mutants, suggesting that the role of RDM4 in cold stress responses is independent of the RdDM pathway. Overexpression of RDM4 constitutively increased the expression of CBFs and regulon genes and decreased cold‐induced membrane injury. A great proportion of genes affected by rdm4 overlapped with those affected by CBFs. Chromatin immunoprecipitation results suggested that RDM4 is important for Pol II occupancy at the promoters of CBF2 and CBF3. We present evidence of a considerable role for RDM4 in regulating gene expression at low temperature, including the CBF pathway in Arabidopsis.
A major challenge for the practical application of lithium-sulfur batteries is the polysulfide shuttling and sluggish redox kinetics due to the notorious adsorption-catalysis underperformance. ...However, conventional carbonaceous materials generally suffer from poor adsorption of polysulfides due to their intrinsic nonpolar surface. Herein, porous carbon nanosheets modified with metallic cobalt and nonmetallic nitrogen/boron heteroatoms, denoted as Co-NBC, is reported as sulfur immobilizer. The presence of conductive metallic cobalt as well as the doped N/B heteroatoms can enhance the electronic conductivity of carbon matrix, and significantly improve the chemical entrapment of soluble polysulfides. Kinetics measurements show that metallic Co catalysts can greatly promote the polysulfide redox kinetics of both liquid-liquid and liquid-solid conversion. As a result, the S/Co-NBC composite realizes remarkable rate performance with high specific capacity of 509 mAh g−1 at a high C-rate of 5 C, and excellent cycle stability with a low capacity fading rate of ∼0.09% per cycle within 500 cycles. Moreover, the S/Co-NBC cathodes realize promising cycle performance even at harsh working condition of high sulfur loading (∼4.6 mg cm−2) or low electrolyte addition (∼3 μL mg−1). This work proposes a meaningful strategy to obtain efficient carbon nanomaterials for high-performance Li–S batteries.
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Fuzzy Petri nets (FPNs) are a potential modeling technique for knowledge representation and reasoning of rule-based expert systems. To date, many studies have focused on the improvement of FPNs and ...various new algorithms and models have been proposed in the literature to enhance the modeling power and applicability of FPNs. However, no systematic and comprehensive review has been provided for FPNs as knowledge representation formalisms. Giving this evolving research area, this work presents an overview of the improved FPN theories and models from the perspectives of reasoning algorithms, knowledge representations and FPN models. In addition, we provide a survey of the applications of FPNs for solving practical problems in variety of fields. Finally, research trends in the current literature and potential directions for future investigations are pointed out, providing insights and robust roadmap for further studies in this field.
•We review the literature on FPNs published between 1988 and 2016.•The reviewed papers are classified based on reasoning algorithms, knowledge representations and FPN models.•A survey of the applications of FPNs for solving practical problems is provided.•We offer directions for future research to improve the FPN performance.
Failure mode and effect analysis (FMEA) is a prospective risk assessment tool used to identify, assess and eliminate potential failure modes in various industries to improve security and reliability. ...However, the conventional risk priority number (RPN) method has been widely criticized for the deficiencies in risk factor weights, calculation of RPN, evaluation of failure modes, etc. In this paper, we present a novel approach for FMEA based on interval-valued intuitionistic fuzzy sets (IVIFSs) and MULTIMOORA method to handle the uncertainty and vagueness from FMEA team members’ subjective assessments and to get a more accurate ranking of failure modes identified in FMEA. In this proposed model, interval-valued intuitionistic fuzzy (IVIF) continuous weighted entropy is applied for risk factor weighting and the IVIF-MULTIMOORA method is used to determine the risk priority order of failure modes. Finally, an illustrative case is provided to demonstrate the effectiveness and practicality of the proposed FMEA and a comparison analysis with other relevant methods is conducted to show its merits.
Health-care waste (HCW) management is a high priority public health and environmental concern particularly in developing countries. The decision to select an optimal technology for the disposal of ...HCW is a complicated multi-criteria decision analysis problem involving both qualitative and quantitative factors. Evaluating HCW treatment technologies may be based on imprecise information or uncertain data. Moreover, there can be significant dependence and feedbacks between the different dimensions and criteria. However, most existing decision models for HCW cannot capture these complex interrelationships. In response, this paper proposes a novel hybrid multi-criteria decision making (MCDM) model by integrating the 2-tuple DEMATEL technique and fuzzy MULTIMOORA method for selection of HCW treatment alternatives. It makes use of modified 2-tuple DEMATEL for obtaining the relative weights of criteria and fuzzy MULTIMOORA for assessing the alternatives according to each criterion. Specifically, an empirical case in Shanghai, one of the largest cities in China, is provided to illustrate the potential of the new model. Results show that the proposed framework for evaluating HCW treatment technologies is effective and provides meaningful implications for engineering designers to refer.
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