Quality and Reliability Engineering International最新文献_第4页

Software reliability prediction: A machine learning and approximation Bayesian inference approach 软件可靠性预测：机器学习和近似贝叶斯推理方法

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-07-26 DOI: 10.1002/qre.3616

Shahrzad Oveisi, Ali Moeini, Sayeh Mirzaei, Mohammad Ali Farsi

{"title":"Software reliability prediction: A machine learning and approximation Bayesian inference approach","authors":"Shahrzad Oveisi, Ali Moeini, Sayeh Mirzaei, Mohammad Ali Farsi","doi":"10.1002/qre.3616","DOIUrl":"https://doi.org/10.1002/qre.3616","url":null,"abstract":"Reliability growth models are commonly categorized into two primary groups: parametric and non‐parametric models. Parametric models, known as Software Reliability Growth Models (SRGM) rely on a set of hypotheses that can potentially affect the accuracy of model predictions, while non‐parametric models (such as neural networks) can predict the model solely based on training data without any assumptions regarding the model itself. In this paper, we propose several methods to enhance prediction accuracy in software reliability context. More specifically, we, on one hand, introduce two gradient‐based techniques for estimating parameters of classical SRGMs. On the other, we propose methods involving LSTM Encoder–Decoder and Bayesian approximation within Langevin Gradient and Variational inference neural networks. To evaluate our proposed models' performance, we compare them with various neural network‐based software reliability models using three real‐world software failure datasets and utilizing the Mean Square Error (MSE) as a model comparison criterion. The experimental results indicate that our proposed non‐parametric models outperform most classical parametric and non‐parametric models.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"7 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new kid on the block: The stratification pattern for space‐filling, with dimension by weight tables 新来的孩子空间填充的分层模式，按权重表划分维度

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-07-25 DOI: 10.1002/qre.3627

Ulrike Grömping

{"title":"A new kid on the block: The stratification pattern for space‐filling, with dimension by weight tables","authors":"Ulrike Grömping","doi":"10.1002/qre.3627","DOIUrl":"https://doi.org/10.1002/qre.3627","url":null,"abstract":"Designs for computer experiments in quantitative factors use columns with many levels. Filling the experimental space is their most important property, and there are many criteria that assess aspects of space‐filling. Recently, Tian and Xu proposed a stratification pattern for assessing the stratification‐related space‐filling properties of designs for quantitative experimental variables whose number of levels is a power of a – usually small – integer. Such designs have been named GSOAs, in generalization of the earlier proposal of strong – or stratum – orthogonal arrays (SOAs). Latin hypercube designs (LHDs) with a suitable number of levels are special cases of GSOAs. Tian and Xu proposed to use the stratification pattern as a means to ranking (G)SOAs. They reported a small simulation study in which arrays that fared well in that ranking performed well in predicting an unknown function. Shi and Xu refined the criterion and also demonstrated success of a design that fares well on their refined criterion. This paper explains the ideas behind the stratification pattern and the related ranking criteria. A practical example and several toy examples aid the illustration. The stratification pattern can be calculated using the R package SOAs, which does not only provide the pattern itself but also provides more detail in a dimension by weight table, in the spirit of the refinement by Shi and Xu.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"55 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The combined Shewhart–EWMA sign charts 合并的 Shewhart-EWMA 标志图

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-07-21 DOI: 10.1002/qre.3625

Mohammed Kadhim Shanshool, Shashibhushan B. Mahadik, Dadasaheb G. Godase, Michael B. C. Khoo

引用次数: 0

A novel equipment remaining useful life prediction approach considering dynamic maintenance threshold 考虑动态维护阈值的新型设备剩余使用寿命预测方法

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-07-17 DOI: 10.1002/qre.3623

Li'Na Ren, Kangning Li, Xueliang Li, Ziqian Wang

{"title":"A novel equipment remaining useful life prediction approach considering dynamic maintenance threshold","authors":"Li'Na Ren, Kangning Li, Xueliang Li, Ziqian Wang","doi":"10.1002/qre.3623","DOIUrl":"https://doi.org/10.1002/qre.3623","url":null,"abstract":"In conventional remaining useful life (RUL) prediction approaches grounded on maintenance, the maintenance threshold is typically established as a stationary value. However, the actual maintenance threshold may exceed its preset value due to the uncertainty of degradation and other factors. Therefore, it is necessary to consider the dynamic maintenance threshold to improve the precision of remaining useful life prediction. By considering the Wiener process, the maintenance threshold error is introduced to reflect the dynamic nature of the maintenance threshold. The influence of maintenance on degradation amount, degradation rate, and degradation path are comprehensively considered to establish a multi‐stage maintenance‐affected degradation process model. The RUL formula of the equipment is derived using the first hitting time (FHT). The maximum likelihood estimation (MLE) approach and Bayesian theory are employed to estimate the model's parameters. The proposed approach is validated using simulation data and gyroscope degradation data. The outcomes reveal that the proposed approach can significantly enhance the precision of life prediction for the equipment.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"92 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141737979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modelling and inference for a degradation process with partial maintenance effects 具有部分维护效果的退化过程的建模和推论

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-07-13 DOI: 10.1002/qre.3618

Margaux Leroy, Christophe Bérenguer, Laurent Doyen, Olivier Gaudoin

{"title":"Modelling and inference for a degradation process with partial maintenance effects","authors":"Margaux Leroy, Christophe Bérenguer, Laurent Doyen, Olivier Gaudoin","doi":"10.1002/qre.3618","DOIUrl":"https://doi.org/10.1002/qre.3618","url":null,"abstract":"This paper proposes a new way of modelling imperfect maintenance in degradation models, by assuming that maintenance affects only a part of the degradation process. More precisely, the global degradation process is the sum of two dependent Wiener processes with drift. Maintenance has an effect of the ‐type on only one of these processes: it reduces the degradation level of a quantity which is proportional to the amount of degradation of this process accumulated since previous maintenance. Two particular cases of the model are considered: perturbed and partial replacement models. The usual model is also a specific case of this new model. The system is regularly inspected in order to measure the global degradation level. Two observation schemes are considered. In the complete scheme, the degradation levels are measured both between maintenance actions and at maintenance times (just before and just after). In the general scheme, the degradation levels are measured only between maintenance actions. The maximum likelihood estimation of the model parameters is studied for both observation schemes in both particular models. The quality of the estimators is assessed through a simulation study.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"58 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141611026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Editorial for the special issue on experimental design for reliability and life testing 可靠性和寿命测试实验设计》特刊编辑

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-07-08 DOI: 10.1002/qre.3620

Rong Pan

引用次数: 0

Distribution‐free multivariate process monitoring: A rank‐energy statistic‐based approach 无分布多变量过程监控：基于秩能统计的方法

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-07-08 DOI: 10.1002/qre.3619

Niladri Chakraborty, Maxim Finkelstein

{"title":"Distribution‐free multivariate process monitoring: A rank‐energy statistic‐based approach","authors":"Niladri Chakraborty, Maxim Finkelstein","doi":"10.1002/qre.3619","DOIUrl":"https://doi.org/10.1002/qre.3619","url":null,"abstract":"In this paper, a multivariate process monitoring scheme based on the rank‐energy statistics is proposed which is suitable for high‐dimensional applications such as sensorless drive diagnosis. The rank‐energy statistic is based on multivariate ranks that is grounded on the measure transportation theory. Univariate ranks could be interpreted as a solution to an optimisation problem involving a given set of observations of size and the set {}. Recently, attaining greater robustness than spatial sign or depth‐based ranks, multivariate ranks are proposed as solutions to such optimisation problem in multivariate settings (measure transportation problem). The proposed multivariate process monitoring scheme based on the rank‐energy statistic, subsequently, attains greater robustness than existing nonparametric multivariate process monitoring methods based on spatial sign or depth‐based ranks. The proposed method is also applicable to high‐dimensional data unlike some of the existing nonparametric multivariate process monitoring methods. A rigorous simulation study demonstrates its effective shift detection ability and other important features. A practical application of the proposed method is demonstrated with the sensorless drive diagnosis case study.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"14 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141566706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unbiased process capability estimation for autocorrelated data using exhaustive systematic sampling 利用详尽系统抽样对自相关数据进行无偏过程能力估计

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-07-07 DOI: 10.1002/qre.3617

Scott D. Grimshaw, Zhupeng Guo, Tyler Duke

{"title":"Unbiased process capability estimation for autocorrelated data using exhaustive systematic sampling","authors":"Scott D. Grimshaw, Zhupeng Guo, Tyler Duke","doi":"10.1002/qre.3617","DOIUrl":"https://doi.org/10.1002/qre.3617","url":null,"abstract":"It is well known that process control index estimators are inflated when naively applied to positively autocorrelated data. The autocorrelation is a nuisance and not a feature that is captured in the process capability indices. This paper proposes exhaustive systematic sampling to create a pooled variance estimator that replaces the biased estimator of the process data standard deviation when data are autocorrelated. The proposed method is effective because the observations within a systematic sample are spread out in time and should be less correlated with each other as a result. It is similar to Bayesian thinning as a strategy for reducing the impact of autocorrelation except no observations are dropped. Properties of estimated process control indices are derived using quadratic forms and large sample theory that is nonparametric in the sense no distribution or time series model is assumed. Approximately unbiased estimates can be achieved for sufficiently large systematic sampling interval. The proposed method is compared to the time series method in a simulation study that demonstrates similar performance. The proposed method is applied to two examples that use because the target is not the midpoint of the specification limits and the mean differs from the target.","PeriodicalId":56088,"journal":{"name":"Quality and Reliability Engineering International","volume":"60 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141566708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Degradation index‐based prediction for remaining useful life using multivariate sensor data 利用多变量传感器数据，基于退化指数预测剩余使用寿命

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-07-06 DOI: 10.1002/qre.3615

Wenda Kang, Geurt Jongbloed, Yubin Tian, Piao Chen

引用次数: 0

A modular model for reliability analysis model of PMS with multiple K/N subsystems and mixed shocks 具有多个 K/N 子系统和混合冲击的 PMS 可靠性分析模型的模块化模型

IF 2.3 3区工程技术

Quality and Reliability Engineering International Pub Date : 2024-07-06 DOI: 10.1002/qre.3614

Weijie Wang, Xiangyu Li, Xiaoyan Xiong

引用次数: 0