Showing papers in "Quality and Reliability Engineering International in 2021"
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TL;DR: An overview of monitoring schemes from a class called generally weighted moving average (GWMA) is provided in this article, where a number of possible future GWMA-related schemes are documented and categorized in such a manner that it is easy to identify research gaps.
Abstract: An overview of monitoring schemes from a class called generally weighted moving average (GWMA) is provided. A GWMA scheme is an extended version of the exponentially weighted moving average (EWMA) scheme with an additional adjustment parameter that introduces more flexibility in the GWMA model as it adjusts the kurtosis of the weighting function so that the GWMA scheme can be designed such that it has an advantage over the corresponding EWMA scheme in the detection of certain shift values efficiently. The parametric and distribution-free GWMA schemes to monitor various quality characteristics and its existing enhanced versions (i.e. double GWMA, composite Shewhart-GWMA, mixed GWMA-CUSUM and mixed CUSUM-GWMA) have better performance than their corresponding EWMA counterparts in many situations; hence, all such existing research works discussing GWMA-related schemes (i.e. 61 publications in total) are documented and categorized in such a manner that it is easy to identify research gaps. Finally, a number of possible future research ideas are provided.
20 citations
TL;DR: An explainable AI model is provided that embeds Shapley values with a statistical normalization, based on Lorenz Zonoids, particularly suited for ordinal measurement variables that can be obtained to assess cyber risk.
20 citations
TL;DR: A prediction model based on phase space reconstruction, chaos analysis, and back propagation (BP) neural network is proposed to predict SMISs reliability and has more accurate prediction results compared with BP network, support vector machine, long short term memory networks (LSTM), and autoregressive model (AR).
TL;DR: This paper proposes an FMEA model based on multi‐granularity linguistic terms and the Dempster–Shafer evidence theory and applies it to an emergency department case, which shows the effectiveness of the method.
TL;DR: This work indicates that various vulnerability characteristics such as severity, type of vulnerabilities, different software configurations, and vulnerability scoring parameters are important features to be considered in judging an exploit, and it is possible to predict exploit‐prone vulnerabilities with an accuracy >85%.
TL;DR: The results indicate that experts prefer to express their preferences by fuzzy sets rather than crisp values, and the interdependencies between the CPCs can be better depicted in the proposed model.