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Optimal constrained design of control charts using stochastic approximations J. Equal. Technol. (IF 2.5) Pub Date : 2024-04-05 Daniele Zago, Giovanna Capizzi, Peihua Qiu
In statistical process monitoring, control charts typically depend on a set of tuning parameters besides its control limit(s). Proper selection of these tuning parameters is crucial to their perfor...
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Nonparametric online monitoring of dynamic networks J. Equal. Technol. (IF 2.5) Pub Date : 2024-02-29 Yipeng Wang, Xiulin Xie, Peihua Qiu
Network sequence has been commonly used for describing the longitudinal pattern of a dynamic system. Proper online monitoring of a network sequence is thus important for detecting temporal structur...
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A blocked staggered-level design for an experiment with two hard-to-change factors J. Equal. Technol. (IF 2.5) Pub Date : 2024-02-08 Peter Goos, Katherine Brickey, Ying Chen
Staggered-level designs have been introduced in the literature as cost-efficient and statistically efficient alternatives to split-plot and split-split-plot designs for experiments with multiple ha...
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Quality prediction using functional linear regression with in-situ image and functional sensor data J. Equal. Technol. (IF 2.5) Pub Date : 2024-02-05 Yaser Zerehsaz, Wenbo Sun, Judy (Jionghua) Jin
This article studies a general regression model for a scalar quality response with mixed types of process predictors including process images, functional sensing signals, and scalar process setup a...
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Adaptive sampling and monitoring of partially observed images J. Equal. Technol. (IF 2.5) Pub Date : 2024-01-24 Jinwei Yao, Badrinath Balasubramaniam, Beiwen Li, Eric L. Kreiger, Chao Wang
Image-based monitoring techniques have achieved great success in many engineering applications. However, most existing image monitoring methods require fully observed images to implement modeling/m...
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Augmenting system tests with component tests for reliability assurance J. Equal. Technol. (IF 2.5) Pub Date : 2024-01-24 Richard L. Warr, Jace Ritchie, Michael Hamada
To successfully determine if a system meets some reliability standard, typically assurance tests are conducted on the full system. This proven approach is extremely effective. However, it can be co...
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Next Editor of the Journal of Quality Technology: Dr. Rong Pan J. Equal. Technol. (IF 2.5) Pub Date : 2024-01-17 Bianca M. Colosimi, L. Allison Jones-Farmer
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 56, No. 1, 2024)
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The 100th anniversary of the control chart J. Equal. Technol. (IF 2.5) Pub Date : 2024-01-17 Douglas C. Montgomery
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 56, No. 1, 2024)
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Correction J. Equal. Technol. (IF 2.5) Pub Date : 2024-01-17
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 56, No. 1, 2024)
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A change-point–based control chart for detecting sparse mean changes in high-dimensional heteroscedastic data J. Equal. Technol. (IF 2.5) Pub Date : 2024-01-17 Zezhong Wang, Inez Maria Zwetsloot
Because of the “curse of dimensionality,” high-dimensional processes present challenges to traditional multivariate statistical process monitoring (SPM) techniques. In addition, the unknown underly...
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Sequential Latin hypercube design for two-layer computer simulators J. Equal. Technol. (IF 2.5) Pub Date : 2024-01-17 Yan Wang, Dianpeng Wang, Xiaowei Yue
The two-layer computer simulators are commonly used to mimic multi-physics phenomena or systems. Usually, the outputs of the first-layer simulator (also called the inner simulator) are partial inpu...
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Federated generalized scalar-on-tensor regression J. Equal. Technol. (IF 2.5) Pub Date : 2024-01-17 Elif Konyar, Mostafa Reisi Gahrooei
Complex systems are generating more and more high-dimensional data for which tensor analysis showed promising results by capturing complex correlation structures of data. Such data is often distrib...
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Adaptive-region sequential design with quantitative and qualitative factors in application to HPC configuration J. Equal. Technol. (IF 2.5) Pub Date : 2024-01-17 Xia Cai, Li Xu, C. Devon Lin, Yili Hong, Xinwei Deng
Motivated by the need of finding optimal configuration in the high-performance computing (HPC) system, this work proposes an adaptive-region sequential design (ARSD) for optimization of computer ex...
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SpTe2M: An R package for nonparametric modeling and monitoring of spatiotemporal data J. Equal. Technol. (IF 2.5) Pub Date : 2023-11-30 Kai Yang, Peihua Qiu
Spatiotemporal data are common in practice. Such data often have complicated structures that are difficult to describe by parametric statistical models. Thus, it is often challenging to analyze spa...
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Spatial modeling and monitoring considering long-range dependence J. Equal. Technol. (IF 2.5) Pub Date : 2023-11-14 Yunfei Shao, Wujun Si, Yong Chen
Spatial modeling and monitoring are critical in geometric characterization and quality control of material/product surfaces. With advances in metrology technology, a long-range dependence (LRD) eff...
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Best practices for multi- and mixed-level supersaturated designs J. Equal. Technol. (IF 2.5) Pub Date : 2023-10-13 Rakhi Singh
Supersaturated designs offer cost-effective efficacy in discerning significant factors among a vast array of potential factors, thereby rendering them valuable. The current literature studies sever...
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Computational and Statistical Methods for Chemical Engineering J. Equal. Technol. (IF 2.5) Pub Date : 2023-09-21 Desy Permatasari
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 56, No. 2, 2024)
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Statistical Analytics for Health Data Science with SAS and R J. Equal. Technol. (IF 2.5) Pub Date : 2023-09-11 Xingyi Yang
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 56, No. 2, 2024)
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Multi-node system modeling and monitoring with extended directed graphical models J. Equal. Technol. (IF 2.5) Pub Date : 2023-07-19 Dengyu Li, Kaibo Wang
Complex manufacturing systems usually contain a large number of variables. Dominated by certain engineering mechanisms, these variables show complicated relationships that cannot be effectively exp...
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funcharts: control charts for multivariate functional data in R J. Equal. Technol. (IF 2.5) Pub Date : 2023-07-19 Christian Capezza, Fabio Centofanti, Antonio Lepore, Alessandra Menafoglio, Biagio Palumbo, Simone Vantini
Modern statistical process monitoring (SPM) applications focus on profile monitoring, i.e., the monitoring of process quality characteristics that can be modeled as profiles, also known as function...
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Scalable level-wise screening experiments using locating arrays J. Equal. Technol. (IF 2.5) Pub Date : 2023-07-07 Yasmeen Akhtar, Fan Zhang, Charles J. Colbourn, John Stufken, Violet R. Syrotiuk
Alternative design and analysis methods for screening experiments based on locating arrays are presented. The number of runs in a locating array grows logarithmically based on the number of factors...
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Phase I analysis of high-dimensional processes in the presence of outliers J. Equal. Technol. (IF 2.5) Pub Date : 2023-07-03 Mohsen Ebadi, Shoja’eddin Chenouri, Stefan H. Steiner
Abstract One of the significant challenges in monitoring the quality of products today is the high dimensionality of quality characteristics. In this paper, we address Phase I analysis of high-dimensional processes with individual observations when the available number of samples collected over time is limited. Using a new charting statistic, we propose a robust procedure for parameter estimation in
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A continual learning framework for adaptive defect classification and inspection J. Equal. Technol. (IF 2.5) Pub Date : 2023-06-30 Wenbo Sun, Raed Al Kontar, Judy (Jionghua) Jin, Tzyy-Shuh Chang
Machine-vision-based defect classification techniques have been widely adopted for automatic quality inspection in manufacturing processes. This article describes a general framework for classifyin...
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ANOVA and Mixed Models: A Short Introduction Using R J. Equal. Technol. (IF 2.5) Pub Date : 2023-06-26 Oluwagbenga David Agboola
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 56, No. 1, 2024)
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A non-linear mixed model approach for detecting outlying profiles J. Equal. Technol. (IF 2.5) Pub Date : 2023-06-21 A. Valeria Quevedo, G. Geoffrey Vining
In parametric non-linear profile modeling, it is crucial to map the impact of model parameters to a single metric. According to the profile monitoring literature, using multivariate T2 statistic to...
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Directional fault classification for correlated High-Dimensional data streams using hidden Markov models J. Equal. Technol. (IF 2.5) Pub Date : 2023-06-21 Yan He, Yicheng Kang, Fugee Tsung, Dongdong Xiang
Modern manufacturing systems are often installed with sensor networks which generate high-dimensional data at high velocity. These data streams offer valuable information about the industrial syste...
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A family of orthogonal main effects screening designs for mixed-level factors J. Equal. Technol. (IF 2.5) Pub Date : 2023-05-08 Bradley Jones, Ryan Lekivetz, Christopher Nachtsheim
There is limited literature on screening when some factors are at three levels and others are at two levels. This topic has seen renewed interest of late following the introduction of the definitiv...
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Blocking OMARS designs and definitive screening designs J. Equal. Technol. (IF 2.5) Pub Date : 2023-05-03 José Núñez Ares, Peter Goos
Abstract The family of orthogonal minimally aliased response surface or OMARS designs comprises traditional response surface designs, such as central composite designs and Box-Behnken designs, as well as definitive screening designs. Key features of OMARS designs are the facts that they are orthogonal for the main effects and that the main effects are not at all aliased with any two-factor interaction
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Statistics for Chemical and Process Engineers: A Modern Approach J. Equal. Technol. (IF 2.5) Pub Date : 2023-04-18 Lenny Rahmawati
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 55, No. 5, 2023)
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The Reliability of Generating Data J. Equal. Technol. (IF 2.5) Pub Date : 2023-04-13 Willis A. Jensen
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 56, No. 1, 2024)
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Foundations of Statistics for Data Scientists: With R and Python J. Equal. Technol. (IF 2.5) Pub Date : 2023-04-05 Lawrence Leemis
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 55, No. 5, 2023)
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Interaction effects in pairwise ordering model J. Equal. Technol. (IF 2.5) Pub Date : 2023-04-05 Chunyan Wang, Dennis K. J. Lin
Abstract In an order-of-addition (OofA) experiment, the response is a function of the addition order of components. The key objective of the OofA experiments is to find the optimal order of addition. The most popularly used model for OofA experiments is perhaps the pairwise ordering (PWO) model, which assumes that the response can be fully accounted by the pairwise ordering of components. Recently
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Use of the bias-corrected parametric bootstrap in sensitivity testing/analysis to construct confidence bounds with accurate levels of coverage J. Equal. Technol. (IF 2.5) Pub Date : 2023-04-05 Edward V. Thomas
Abstract Sensitivity testing often involves sequential design strategies in small-sample settings that provide binary data which are then used to develop generalized linear models. Model parameters are usually estimated via maximum likelihood methods. Often, confidence bounds relating to model parameters and quantiles are based on the likelihood ratio. In this paper, it is demonstrated how the bias-corrected
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Knots and their effect on the tensile strength of lumber: A case study J. Equal. Technol. (IF 2.5) Pub Date : 2023-03-27 Shuxian Fan, Samuel W. K. Wong, James V. Zidek
Abstract When assessing the strength of sawn lumber for use in engineering applications, the sizes and locations of knots are an important consideration. Knots are the most common visual characteristics of lumber, that result from the growth of tree branches. Large individual knots, as well as clusters of distinct knots, are known to have strength-reducing effects. However, industry grading rules that
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A review and comparison of control charts for ordinal samples J. Equal. Technol. (IF 2.5) Pub Date : 2023-02-28 Sebastian Ottenstreuer, Christian H. Weiß, Murat Caner Testik
Abstract Qualitative, more specifically, ordinal data generating processes are common in real-world process control implementations. In this study, a survey of control charts for the sample-based monitoring of independent and identically distributed ordinal data is provided together with critical comparisons of the control statistics, for memory-less Shewhart-type and for memory-utilizing exponentially
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Bayesian networks with examples in R J. Equal. Technol. (IF 2.5) Pub Date : 2023-02-22 Reviewer: Zhanpan Zhang
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 55, No. 4, 2023)
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Data Science: A First Introduction J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-27 Joseph Conklin
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 55, No. 4, 2023)
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Optimization of Pharmaceutical Processes J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-27 Novita Pratiwi Lembang
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 55, No. 3, 2023)
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Design and properties of the predictive ratio cusum (PRC) control charts J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-27 Konstantinos Bourazas, Frederic Sobas, Panagiotis Tsiamyrtzis
Abstract In statistical process control/monitoring (SPC/M), memory-based control charts aim to detect small/medium persistent parameter shifts. When a phase I calibration is not feasible, self-starting methods have been proposed, with the predictive ratio cusum (PRC) being one of them. To apply such methods in practice, one needs to derive the decision limit threshold that will guarantee a preset false
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Statistical Methods for Reliability Data J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-27 Hon Keung Tony Ng Reviewed by:
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 55, No. 3, 2023)
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Predictive ratio CUSUM (PRC): A Bayesian approach in online change point detection of short runs J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-27 Konstantinos Bourazas, Frederic Sobas, Panagiotis Tsiamyrtzis
Abstract The online quality monitoring of a process with low volume data is a very challenging task and the attention is most often placed in detecting when some of the underline (unknown) process parameter(s) experience a persistent shift. Self-starting methods, both in the frequentist and the Bayesian domain aim to offer a solution. Adopting the latter perspective, we propose a general closed-form
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Phase I control chart for individual autocorrelated data: application to prescription opioid monitoring J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-23 Yuhui Yao, Subha Chakraborti, Xin Yang, Jason Parton, Dwight Lewis Jr, Matthew Hudnall
Abstract Phase I or retrospective process monitoring plays a key part in an overall statistical process monitoring (SPM) regime and is increasingly emphasized in the recent literature. At present, a lot of the data in a variety of settings (public and private sector organizations) are collected individually and sequentially and thus are serially correlated (or autocorrelated). Though a reasonable amount
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Analysis of data from orthogonal minimally aliased response surface designs J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-23 Mohammed Saif Ismail Hameed, José Núñez Ares, Peter Goos
Abstract Experimental data are often highly structured due to the use of experimental designs. This does not only simplify the analysis, but it allows for tailored methods of analysis that extract more information from the data than generic methods. One group of three-level experimental designs that are suitable for such tailored methods are orthogonal minimally aliased response surface (OMARS) designs
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Lot acceptance testing using sample mean and extremum with finite qualification samples J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-20 Stefan Kloppenborg
Abstract In the aerospace composites industry, new material lots are tested to determine if they are suitable for use. It is common to accept or reject the material lot by comparing the sample mean and lower extremum to reference values that are established based on an initial (qualification) sample of material property measurements. Current industry practices assume that the samples are drawn from
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Message from the Editor J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-18 Allison Jones-Farmer
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 55, No. 1, 2023)
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Efficient analysis of split-plot experimental designs using model averaging J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-12 Chuen Yen Hong, David Fletcher, Jiaxu Zeng, Christina M. McGraw, Christopher E. Cornwall, Vonda J. Cummings, Neill G. Barr, Emily J. Frost, Peter W. Dillingham
Abstract Split-plot experimental data are often analyzed as if the data came from a completely randomized design. As is well known, ignoring the different levels of randomization and replication can lead to serious inferential errors. However, in some experiments, including many of the ocean global change experiments that motivated this research, variation between whole-plot experimental units may
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Constructing control charts for autocorrelated data using an exhaustive systematic samples pooled variance estimator J. Equal. Technol. (IF 2.5) Pub Date : 2023-01-12 Scott D. Grimshaw
Abstract SPC with positive autocorrelation is well known to result in frequent false alarms if the autocorrelation is ignored. The autocorrelation is a nuisance and not a feature that merits modeling and understanding. This paper proposes exhaustive systematic sampling, which is similar to Bayesian thinning except no observations are dropped, to create a pooled variance estimator that can be used in
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Augmenting definitive screening designs: Going outside the box J. Equal. Technol. (IF 2.5) Pub Date : 2022-11-03 Mengmeng Liu, Robert W. Mee, Yongdao Zhou
Abstract Definitive screening designs (DSDs) have grown rapidly in popularity since their introduction by Jones and Nachtsheim (2011 Jones, B., and C. J. Nachtsheim. 2011. A class of three-level designs for definitive screening in the presence of second-order effects. Journal of Quality Technology 43 (1):1–15. doi: 10.1080/00224065.2011.11917841.[Taylor & Francis Online], [Web of Science ®] , [Google
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Monitoring and diagnostics of correlated quality variables of different types J. Equal. Technol. (IF 2.5) Pub Date : 2022-08-22 Wei-Heng Huang, Jing Sun, Arthur B. Yeh
Abstract As data acquisition and processing technologies continue to advance rapidly, new challenges emerge for statistical process monitoring. One such challenge, especially in the era of big data analytics, is monitoring multivariate processes involving a mixture of continuous, categorical, and discrete quality variables. The existing multivariate control charts focus mostly on monitoring correlated
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Analyzing dispersion effects from replicated order-of-addition experiments J. Equal. Technol. (IF 2.5) Pub Date : 2022-08-22 Shin-Fu Tsai
Abstract Dispersion effects may play a vital role, in addition to location effects, in exploring optimal addition orders of several materials in some chemical, industrial and pharmaceutical studies. Two replication-based statistical methods developed using frequentist and fiducial probability arguments are introduced in this paper to identify active dispersion effects from replicated order-of-addition
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In-profile monitoring for cluster-correlated data in advanced manufacturing system J. Equal. Technol. (IF 2.5) Pub Date : 2022-08-16 Peiyao Liu, Juan Du, Yangyang Zang, Chen Zhang, Kaibo Wang
Abstract Nowadays advanced sensing technology enables real-time data collection of key variables during manufacturing, known as multi-channel profiles. These data facilitate in-process monitoring and anomaly detection, which have been extensively studied in recent years. However, most studies treat each profile as a whole, e.g., a high-dimensional vector or function, and construct monitoring schemes
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Open data for open science in Industry 4.0: In-situ monitoring of quality in additive manufacturing J. Equal. Technol. (IF 2.5) Pub Date : 2022-08-11 Marc Gronle, Marco Grasso, Emidio Granito, Frederik Schaal, Bianca Maria Colosimo
Abstract Open science has the capacity of boosting innovative solutions and knowledge development thanks to a transparent access to data shared within the research community and collaborative networks. Because of this, it has become a policy priority in various research and development strategy plans and roadmaps, but the awareness if its potential is still limited in industry. Additive manufacturing
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Bayesian sequential design for sensitivity experiments with hybrid responses J. Equal. Technol. (IF 2.5) Pub Date : 2022-07-25 Yuxia Liu, Yubin Tian, Dianpeng Wang
Abstract In experimental design, a common problem seen in practice is when the result includes one binary response and multiple continuous responses. However, this problem receives scant attention. Most studies pertaining to this problem usually consider the situation in which the continuous responses are independent of the stimulus level condition on the binary response. However, in many practical
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Learning Basse R, 2nd edition, Lawrence M. Leemis, 2022, Lightning Source, 368 pp., $40, ISBN: 978-0-9829174-5-9 J. Equal. Technol. (IF 2.5) Pub Date : 2022-07-20 Reviewer: Hao Zhao
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 55, No. 3, 2023)
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Monitoring reliability under competing risks using field data J. Equal. Technol. (IF 2.5) Pub Date : 2022-07-13 Francis G. Pascual, Joseph P. Navelski
Abstract Many modern products fail due to one of multiple causes called competing risks. In this article, we propose variable features for monitoring product failure by control charts under competing risks. Failure reports arrive one at a time from a sample of population of units. Features are derived from both the reports and the assumed competing-risk statistical model. To assess the efficacy of
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Design and Analysis of Experiments and Observational Studies using R J. Equal. Technol. (IF 2.5) Pub Date : 2022-07-12 Joseph Conklin
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 55, No. 2, 2023)
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Data-level transfer learning for degradation modeling and prognosis J. Equal. Technol. (IF 2.5) Pub Date : 2022-06-15 Amirhossein Fallahdizcheh, Chao Wang
Abstract The typical way to conduct data-driven prognosis is to train a degradation model with historical data, then apply the model to predict failure for in-service units. Most existing works assume the historical data and in-service data are from the same process. In practice, however, different but related processes can share similar degradation patterns. Thus, the historical data from these processes
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Spatio-temporal process monitoring using exponentially weighted spatial LASSO J. Equal. Technol. (IF 2.5) Pub Date : 2022-06-02 Peihua Qiu, Kai Yang
Abstract Spatio-temporal process monitoring (STPM) has received a considerable attention recently due to its broad applications in environment monitoring, disease surveillance, streaming image processing, and more. Because spatio-temporal data often have complicated structure, including latent spatio-temporal data correlation, complex spatio-temporal mean structure, and nonparametric data distribution
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Book review: Introduction to statistical process control J. Equal. Technol. (IF 2.5) Pub Date : 2022-04-12 William H. Woodall
Published in Journal of Quality Technology: A Quarterly Journal of Methods, Applications and Related Topics (Vol. 55, No. 2, 2023)
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Entropy-based adaptive design for contour finding and estimating reliability J. Equal. Technol. (IF 2.5) Pub Date : 2022-04-08 D. Austin Cole, Robert B. Gramacy, James E. Warner, Geoffrey F. Bomarito, Patrick E. Leser, William P. Leser
Abstract In reliability analysis, methods used to estimate failure probability are often limited by the costs associated with model evaluations. Many of these methods, such as multifidelity importance sampling (MFIS), rely upon a computationally efficient surrogate model like a Gaussian process (GP) to quickly generate predictions. The quality of the GP fit, particularly in the vicinity of the failure