Search

Failure mode and effects analysis (FMEA) is a systematic and proactive risk prevention and management tool used to improve the reliability and safety of a system, process or service. However, many defects around the traditional FMEA affect the effectiveness of its practical applications. When dealing with the FMEA problems, the first and the most important step is to collect the risk assessment information of experts regarding failure modes. Moreover, clustering failure modes is more adaptable to actual needs, especially under a tight resource constraint. In this article, a new FMEA model using double hierarchy hesitant fuzzy linguistic term sets (DHHFLTSs) and k-means clustering is developed to evaluate and cluster the risk of failure modes. First, the DHHFLTSs are utilized to describe the complex linguistic assessments on failure modes given by FMEA team members. Next, an improved k-means algorithm is proposed and used to cluster failure modes into priority classes. Finally, a case study concerning the risk evaluation over floating offshore wind turbine is provided to illustrate the effectiveness and usefulness of our proposed FMEA. The results show that the new risk classification approach is more reasonable and practical for risk management decision making.

Quality function deployment (QFD) is a team-based product development technique for determining critical engineering characteristics based on customer requirements to realize higher customer satisfaction. Given its simplicity and visibility, the QFD has been broadly utilized in a variety of industries for product or service planning. However, traditional QFD method assumes that the behavior of domain experts is completely rational, and is only suitable for product development problems with a small number of experts. In this paper, we aim to develop a new large group QFD approach based on an extended TODIM (Portuguese acronym for interactive multi-criteria decision making) method under interval type-2 fuzzy context. The interval type-2 fuzzy sets are utilized to describe the imprecise and uncertain correlation assessment information between customer requirements and engineering characteristics. The normal TODIM is modified and used to derive the priority of engineering characteristics considering the psychological factors of experts. Also, an entropy weighting method was adopted to derive the weights of customer requirements objectively. Finally, we provide an electric vehicle product development case and perform a comparison analysis with previous methods to reveal the effectiveness and practicability of the proposed large group QFD approach.

Fuzzy Petri nets (FPNs) are a graphical-based knowledge representation and reasoning tool widely used in many fields for intelligent decision making. However, the traditional FPNs could not accurately represent domain experts’ uncertain and ambiguous knowledge with the increasing complexity of knowledge base systems. Additionally, the task of assessing the truth degrees of input places is limited to small-scale expert groups in current practices. In response to these problems, we develop a new type of FPN model, called Pythagorean FPNs (PFPNs), for knowledge representation and reasoning in the large group context. Pythagorean fuzzy sets are introduced to capture imprecise and ambiguous knowledge and a large group truth determination method is proposed to get the truth degrees of input places with massive data. Finally, an application example regarding security risk assessment is given to show the effectiveness and advantages of our proposed PFPNs.

Failure mode and effects analysis (FMEA) is known to be a proactive reliability analysis model broadly utilized to recognize and evaluate potential failure modes in various industries. The normal risk priority number (RPN) method, however, has suffers from a lot of criticisms, such as requirement of precise risk estimation, lack of scientific basis in computing RPN, and neglecting the weights of risk factors. Therefore, this paper devises a new FMEA model to evaluate and prioritize the risk of failure modes by integrating probabilistic linguistic term sets and TODIM (an acronym in Portuguese for interactive multi-criteria decision making) method. The probabilistic linguistic term sets are utilized to handle the intrinsic ambiguity existed in the risk assessments of FMEA team members, whilst an extended TODIM method is employed for determining the priority ranking of the individuated failure modes. Further, based on the technique for order of preference by similarity to ideal solution (TOPSIS), an objective weighting method is presented to derive the relative weights of risk factors. Finally, two illustrative examples are implemented and comparisons with other existing methods are performed to demonstrate the rationality and superiority of our proposed FMEA model.

With the increased awareness of environmental issues worldwide, sustainable production and development have become very important for various industries. Through green supplier selection and order allocation (GSSOA), companies can save costs, improve their green performance and thus build competitive advantage. To select appropriate supply partners and reasonable allocate order quantity, this paper develops a new integrated GSSOA model through the combination of linguistic Z-numbers, alternative queuing method (AQM) and multi-objective line programming (MOLP) model. The principal contribution of this work lies in the following aspects: Firstly, the linguistic Z-numbers are adopted to express decision-makers’ performance evaluations of alternative suppliers comprehensively. Secondly, a step-weight assessment ratio analysis (SWARA) technique is used to calculate the weights of selection criteria. Then, an extended AQM is proposed for the ranking of the given green suppliers. Finally, a MOLP model is established to determine the optimal order quantity for the qualified green suppliers according to their priority values. An empirical example and a comparison analysis with the existing methods are presented to illustrate the rationality and efficiency of our developed GSSOA model.

Failure mode and effect analysis (FMEA) is a proactive reliability management technique extensively utilized in a variety of fields. To enhance the effectiveness of FMEA, a great many multi-criteria decision making (MCDM) methods have been applied for properly evaluating the risk of failure modes over the past two decades. However, there is a lack of study concerning systematic literature review and classification of the researches on this topic. This article aims to provide a comprehensive review of the FMEA studies using MCDM approaches for evaluation and prioritization of failure modes. To do so, a total of 169 journal papers extracted from the online database over the period of 1998–2018 were selected and reviewed. These publications were classified into 10 categories according to the used MCDM methods, and analyzed in regard to the risk factors, risk factor weighting methods, and risk assessment methods in FMEA. Furthermore, a bibliometric analysis was performed based on the frequency of MCDM methods, number of citations, year of publication, appeared journals, country of origin and application areas. This research supports academics and practitioners in effectively adopting MCDM methods to overcome the deficiencies of the traditional FMEA and provides an insight into its state-of-the-art.

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.

In this experiment, directional solidification method was used to prepare metallurgical grade silicon ingot. We have studied the solidification rate which influenced the results of the experiment. Experimental results showed that the impurities were concentrated mostly in the top of silicon ingot. It was inferred that second or more times directional solidification experiments is needed to remove the impurities. What’s more, it showed that the best solidification rate is 1.5mm/min in this study.

// Du He 1, 2, * , Xue Huang 1, 2, * , Zai-Ping Wang 1, 2, * , Dian Chen 1, 2 , Jun Chen 1, 2 and Chun-Yan Duan 1, 2 1 Department of Oncology, The Central Hospital of Enshi Autonomous Prefecture, Enshi 445000, China 2 Enshi Clinical College of Wuhan University, Enshi 445000, China * These authors contributed equally to this work Correspondence to: Jun Chen, email: hdu1234@163.com Chun-Yan Duan, email: shwh312@163.com Keywords: fat intake, esophageal carcinoma, risk, meta-analysis Received: May 27, 2017 Accepted: September 21, 2017 Published: October 03, 2017 ABSTRACT Dietary fat intake is potentially associated with the onset of esophageal carcinoma (EC), but evidence from observational studies has remained unclear. This study aimed to evaluate the role of fat intake in the development of esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC). A systematic search was conducted in PubMed and Web of Science to identify all relevant studies. Study-specific relative risks (RR) for the highest versus the lowest intake categories and 95% confidence intervals (CI) were pooled using a random-effects model. Seventeen case-control studies (2058 EAC cases, 1581 ESCC cases and 11696 controls) and two prospective cohort studies (494, 978 participants and 630 EAC cases and 215 ESCC cases) were identified. In EAC, the RRs (95% CI) were 1.69 (1.14–2.50) for total fat intake, 1.88 (1.28–2.77) for saturated fat (SFA) intake, 1.04 (0.86–1.27) for polyunsaturated fat (PUFA) intake and 1.70 (1.01–2.84) for monounsaturated fat (MUFA) intake. In ESCC, the RRs (95% CI) were 1.12 (0.84–1.51) for total fat, 1.38 (0.91–2.08) for SFA, 0.95 (0.55–1.62) for PUFA and 1.04 (0.65–1.66) for MUFA. In conclusion, total fat, SFA and MUFA intake were associated with EAC risk, but fat intake showed no significant association with ESCC risk. Large-scale prospective cohort studies are needed to confirm our findings.

The third-party platform named ECO system is used by many transnational companies to monitor the sustainability performance of their global suppliers because of its easiness and shareability. Nonetheless, methods used in this platform for evaluating and calculating the sustainability performance of the alternative suppliers are criticized for their lack of accuracy. In response to these problems, this paper presents a heterogeneous multi-criteria decision-making (MCDM) method based on interval-valued intuitionistic fuzzy--an acronym in Portuguese for interactive multi-criteria decision making (IVIF--TODIM) to improve the efficiency of the evaluation model. Considering the varying features of evaluation criteria, i.e., either quantitative or qualitative, the evaluation values under different criteria are expressed in their appropriate information types. In this paper, a general method based on the relative closeness to the technique for order preference by similarity to ideal solution (TOPSIS) method is applied for aggregating the heterogeneous assessment information, including crisp numbers, interval numbers, and triangular fuzzy numbers (TFNs), into interval-valued intuitionistic fuzzy numbers (IVIFNs). Then, the TODIM (an acronym in Portuguese for interactive multi-criteria decision making) is extended and employed to prioritize the alternative suppliers. Finally, the applicability and effectiveness of the proposed method is verified by a practical example of polymer manufacturing company and a comparison analysis with existing methods.

In order to reveal the effect of vegetation type and soil physicochemical properties on the distribution of soil organic carbon and its components, a field survey was carried out on nine different plant communities along a water table gradient in the Huixian wetland with samples of soil at 0-10 cm, 10-20 cm, and 20-30 cm in depth. The soil organic carbon (SOC), light fraction organic carbon (LFOC), heavy fraction organic carbon (HFOC), easily oxidized organic carbon (EOC), dissolved organic carbon (DOC), particulate organic carbon (POC), and microbial biomass carbon (MBC) were measured. The correlations among soil organic carbon components and soil physicochemical properties were also examined. The results showed that:① The average proportion of LFOC and HFOC to SOC at 0-30 cm soil depth was 11.10% and 88.90%, respectively. The distribution ratio of the heavy component was much higher than of the light component in soils. ② The content of SOC, DOC, EOC, POC, and MBC (except in the

With strengthening global consciousness of environmental protection, green supply chain management plays an increasingly important role in modern enterprise production operation management. A critical means to implement green supply chain management is incorporating environmental requirements into the supplier selection practices. In this paper, we put forward a novel integrated approach by using interval-valued intuitionistic uncertain linguistic sets (IVIULSs) and grey relational analysis (GRA)-technique for order preference by similarity to ideal solution (TOPSIS) method for the evaluation and selection of green suppliers. First, various qualitative assessments of alternatives provided by decision makers are described by the IVIULSs. Then, the GRA-TOPSIS method is extended and employed to prioritize the alternative suppliers. The proposed model can handle the uncertainty and fuzziness of decision makers’ subjective evaluations more easily and get a more realistic and accurate ranking of green suppliers. Finally, an illustrative example in the agri-food industry is presented to verify the proposed green supplier selection model and demonstrate its practicality and effectiveness.

Background Recently, miR-22 is identified as a tumor-suppressing microRNA in many human cancers. CD147 is a novel cancer-associated biomarker that plays an important role in the invasion and metastasis of malignant tumor. However, the involvement of miR-22 in CD147 regulation and hepatocellular carcinoma (HCC) progression and metastasis has not been investigated. Methods We measured miR-22 expression level in 34 paired of HCC and matched normal tissues, HCC cell lines by real-time quantitative RT-PCR. Invasion assay, MTT proliferation assay and wound-healing assay were performed to test the invasion and proliferation of HCC cell after overexpression of miR-22. The effect of miR-22 on HCC in vivo was validated by murine xenograft model. The relationship of miR-22 and its target gene CD147 was also investigated. Results We found that the expression of miR-22 in HCC tissues and cell lines were much lower than that in normal control, respectively. The expression of miR-22 was inversely correlated with HCC metastatic ability. Moreover, overexpression of miR-22 could significantly inhibit the HCC cell proliferation, migration and invasion in vitro and decrease HCC tumor growth in vivo. Finally, we found that miR-22 interacted with CD147 and decreased its expression, via a specific target site within the CD147 3′UTR by luciferase reporter assay. The expression of CD147 was inversely correlated with miR-22 expression in HCC tissues. Conclusion Our results suggested that miR-22 was downexpressed in HCC and inhibited HCC cell proliferation, migration and invasion through downregulating cancer-associated gene CD147 which may provide a new bio-target for HCC therapy.

Au nanoparticles arrays for silicon solar cells were fabricated by self-assembly method to accommodate manufacturing process of traditional silicon solar cells. Surface morphologies of 10-30 nm thick films after annealing treatment at 600 °C and 700 °C were analyzed. It indicated that morphological features of Au nanoparticles arrays such as particle shapes, size distribution vary with thicknesses of Au films, annealing temperatures and surface morphologies of substrates.

Ag nanoparticles arrays were fabricated by self-assembly method to accommodate manufacturing process of traditional silicon solar cells. Surface morphologies of films (5-27.5 nm) after annealing treatment with 260 °C and 400 °C were analyzed. The results showed that annealing temperature has important impact on self-assembled nanoparticles arrays. The tuning function of SiNx dielectric film was also analyzed. The absorption peak generates a redshift with the maximum range about 100 nm in the absorption spectrum, and the peak widths become wider with the increase of thickness of SiNx dielectric film for the same particle size distribution of Ag nanoparticles arrays.

Selected area laser-annealed polycrystalline silicon (p-Si) thin films were prepared by a 248 nm excimer laser. 1 μm thick p-Si films with grain size less than 100 nm were deposited on SiO2substrate by chemical vapor deposition using atmospheric pressure (APCVD). Grain sizes before and after annealing was examined by scanning electron microscopy (SEM) and the mechanism of grain growth was discussed in detail. The maximum grain size of a selected area laser-annealed p-Si film can be increased from 100 nm up to 2.9 μm on SiO2substrate by using appropriate laser energy densities. It indicated that silicon grains in laser-annealed regions had grown up competitively with three stages.

The aim of this study is to evaluate the effect of boric acid as an additive for gelled electrolytes. Cyclic voltammetry (CV), linear sweep voltammetry (LSV), electrochemical impedance spectroscopy (EIS) and an equivalent circuit analysis were employed to study the electrochemical performance of the gelled electrolyte with the addition of varying amounts of boric acid. Scanning electron microscope (SEM) was employed to observe the grid corrosion in corrosion test. For moderate contents of boric acid, the electrode capacity improved, as well as the oxygen evolution profermance. However, the adverse effects of boric acid were found to include increased electrical resistance, decreased hydrogen evolution overpotential and promote the corrosion of the grid. The experimental results indicates that the optimum content was 0.4wt.%.

Directional solidification is one of the most important processes to purify the impurities in the metallurgical grade silicon. A lot of factors could influence the result of directional solidification. In this paper, we researched cooling water flow which could influence the result of directional solidification. We have studied three data of cooling water flow which influenced the results of the removal efficiency of the impurities. Experimental results showed that cooling water flow can influence the density of dislocations and twins in the ingot. The metal impurities of Al, Fe and Ca were concentrated in the middle of the silicon ingot mostly. It was inferred that the bigger cooling water flow was better to the efficiency of the purification in the experiment.

We have investigated the deposition of silicon films on SiO2 patterned Si(111) substrates by atmospheric pressure chemical vapor deposition (APCVD) under standard condition. Oxidized silicon wafers with different sizes of circular and striated patterns were used as substrates for deposition of 35 μm silicon films. The influence of surface morphologies of substrates on epitaxial Si films has been discussed. The crystalline structures of the epitaxial Si films rely on the prepatterned substrates. Triangular prism-shaped grains have been obtained after depositing silicon film on substrates with circular patterns. While different size polycrystalline silicon grains appear on surfaces of Si films grown on SiO2 regions of substrates along the axis of striated patterns. Twins defects were observed in epitaxial Si films grown on SiO2 layers of the pretreated substrates.

To investigate whether the phosphorylation (functionally inhibitive) of eukaryotic initiation factor 2-alpha (eIF2-a) affects the molecular mechanism of cisplatin-induced cellular apoptosis in human hepatocellular carcinoma (HCC).The human HCC cultured cell lines SMMC-7221 and HepG2 were treated with cisplatin alone (controls; 24 h) or in combination with pre-transfection of a dominant-negative eIF2-a mutant (eIF2aS51A) or pre-exposure to an eIF2-a-specific phosphatase inhibitor (salubrinal) to decrease or increase the phosphorylation level, respectively. Changes in expression of apoptosis markers were quantitatively and qualitatively assessed by flow cytometry and western blot analysis. The significance of differences among groups was assessed by analysis of variance testing and of differences between groups was assessed by t-test.Cisplatin treatment induced the appropriate functional-inhibitive phosphorylation of eIF2-a on serine 51. Cisplatin treatment (10 mg/ml) induced significant apoptosis in the eIF2aS51A pre-transfected SMMC-7721 (control: 21.7 +/- 1.5% vs. 50.7 +/- 2.1%, t = 19.454, P less than 0.05) and HepG2 (21.0 +/- 1.0% vs. 57.3 +/- 2.1%, t = 27.250, P less than 0.05). Salubrinal pre-treatment significantly inhibited the cisplatin (15 mg/ml)-induced apoptosis in SMMC-7721 (control: 50.3 +/- 2.5% vs. 16.3 +/- 2.1%, t = 18.031, P less than 0.05) and HepG2 (42.0 +/- 2.6% vs. 12.0 +/- 2.0%, t = 15.667, P less than 0.05).Phosphorylation of eIF2-a may act to inhibit cisplatin-induced apoptosis of HCC.

The objective of this study was to compare the hand disinfectant effects between super hypochlorous water and 7.5% povidone-iodine. Subjects included thirty pediatric dentists. They first watched the educational videotape for hand disinfection. They then pressed their right five fingers on Brain Heart Infusion (BHI) agars. They disinfected their hands under running super hypochlorous water until they considered to be enough clean, removed the excess water using a paper towel and again pressed their fingers on the BHI agars. Furthermore, the individual disinfectant time was measured. The agars were incubated at 37°C for 48 h, the colonies counted and calculated as logarithmic values. The same procedures were performed using 75% povidone- iodine two months later. As results, the following observations were shown. The disinfectant effects of super hypochlorous water were significantly more effective than that of 7.5% povidone-iodine. There was no correlation between disinfectant effects of both disinfectants and the hand disinfecting times.

To investigate the cross-talk between the PI3K/Akt and MEK/ERK pathways and its role in cell cycle regulation under endoplasmic reticulum stress in human hepatocellular carcinoma cells.PI3K inhibitor LY294002 and MEK inhibitor U0126 were used to block the PI3K/Akt and MEK/ERK pathways respectively, and constitutively activated Akt mutant construct was used to activate the PI3K/Akt pathway. Western blot was used to study the potential cross-talk between the PI3K/Akt and MEK/ERK pathways under endoplasmic reticulum stress in human hepatocellular carcinoma cells. the role of the cross-talk between the PI3K/Akt and MEK/ERK pathways in cell cycle regulation was investigated by using propidium iodide staining.LY294002 not only blocked Akt activation efficiently but also increased ERK phosphorylation markedly under endoplasmic reticulum stress in SMMC-7721 and Hep3B cells. Furthermore, myr-Akt inhibited endoplasmic reticulum stress-mediated ERK phosphorylation. In contrast, MEK inhibitor U0126 had no effect on endoplasmic reticulum stress-induced Akt activation. It is notable that both myr-Akt overexpression and MEK inhibitor U0126 inhibited endoplasmic reticulum stress-induced G0/G1 phase arrest in SMMC-7721 cells.Endoplasmic reticulum stress-induced Akt activation is mediated through PI3K and the PI3K/Akt pathway inactivation is involved in increased ERK activity in human hepatocellular carcinoma cells. The cross-talk between the PI3K/Akt and MEK/ERK cascades plays an important role in endoplasmic reticulum stress-induced human hepatocellular carcinoma cell cycle arrest.