Journal of Quality Technology

Papers
(The median citation count of Journal of Quality Technology is 0. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-03-01 to 2025-03-01.)
ArticleCitations
Learning Basse R, 2nd edition, Lawrence M. Leemis, 2022, Lightning Source, 368 pp., $40, ISBN: 978-0-9829174-5-936
Statistical Methods for Reliability Data30
Advanced Survival Models23
Probability and statistical inference: From basic principles to advanced models21
Directional fault classification for correlated High-Dimensional data streams using hidden Markov models20
Introduction to High-Dimensional Statistics, Christophe Giraud. Chapman\& Hall/CRC Press, 2021, 364 pp., $72.00 hardcover, ISBN 978-0-367-71622-6.16
Federated generalized scalar-on-tensor regression13
Letter to the editor11
Book review: Introduction to statistical process control11
Next Editor of the Journal of Quality Technology: Dr. L. Allison Jones-Farmer11
Change point detection and issue localization based on fleet-wide fault data9
An adaptive sensor selection framework for multisensor prognostics9
The Reliability of Generating Data The Reliability of Generating Data , by K. Krippendorf. Boca Raton, FL: Chapman and Hall/CRC, 2023, 328 pp., $130.00; ISBN 978-03676309
Open data for open science in Industry 4.0: In-situ monitoring of quality in additive manufacturing8
Toward a better monitoring statistic for profile monitoring via variational autoencoders8
Multimodal recognition and prognostics based on features extracted via multisensor degradation modeling8
Reliability: Probabilistic models and statistical methods8
Robust experimental designs for model calibration8
Adaptive sampling and monitoring of partially observed images7
Robustness with respect to class imbalance in artificial intelligence classification algorithms7
A graphical comparison of screening designs using support recovery probabilities6
Artificial intelligence and statistics for quality technology: an introduction to the special issue6
V2X, GNSS, radar, and camera-based intelligent system for adaptive control of heavy mining vehicles during foggy weather6
A change-point–based control chart for detecting sparse mean changes in high-dimensional heteroscedastic data6
Building a Platform for Data-Driven Pandemic Prediction from Data Modeling to Visualization – The CovidLP Project5
Controlling the conditional false alarm rate for the MEWMA control chart5
Predictive ratio CUSUM (PRC): A Bayesian approach in online change point detection of short runs5
Bayesian networks with examples in RBayesian networks with examples in R, 2nd Edition, by Marco Scutari and Jean-Baptiste Denis. Boca Raton, FL: Chapman & Hall/CRC Press, 2021. 258 pp., $93.10. IS5
Powerful and robust dispersion contrasts for replicated orthogonal designs4
A non-linear mixed model approach for detecting outlying profiles4
Measuring the robustness of predictive probability for early stopping in two-group comparisons4
Monitoring proportions with two components of common cause variation4
Blocking OMARS designs and definitive screening designs4
In-profile monitoring for cluster-correlated data in advanced manufacturing system4
Correction3
Statistical Design and Analysis of Biological Experiments3
Complex geometries in additive manufacturing: A new solution for lattice structure modeling and monitoring3
A comprehensive case study on the performance of machine learning methods on the classification of solar panel electroluminescence images3
Statistics for Chemical and Process Engineers: A Modern Approach Statistics for Chemical and Process Engineers: A Modern Approach , 2nd ed., by Yuri A. W. Shardt. Cham, 3
Augmenting definitive screening designs: Going outside the box3
Deep multistage multi-task learning for quality prediction of multistage manufacturing systems3
Optimization of Pharmaceutical Processes2
Boost-R: Gradient boosted trees for recurrence data2
An introduction to acceptance sampling and SPC with R2
Efficient analysis of split-plot experimental designs using model averaging2
Optimal constrained design of control charts using stochastic approximations2
A comprehensive toolbox for the gamma distribution: The gammadist package2
An adaptive multivariate functional EWMA control chart2
Spatial modeling and monitoring considering long-range dependence2
SpTe2M: An R package for nonparametric modeling and monitoring of spatiotemporal data2
Monitoring and diagnostics of correlated quality variables of different types2
Robust multivariate control chart based on shrinkage for individual observations2
Understanding elections through statistics by Ole J. Forsberg, CRC press, Taylor & Francis group, boca Raton, FL, 2020, 225 pp., $69.95, ISBN 978-03678953722
A family of orthogonal main effects screening designs for mixed-level factors1
Multi-sensor based landslide monitoring via transfer learning1
Correction1
Quality prediction using functional linear regression with in-situ image and functional sensor data1
Next Editor of the Journal of Quality Technology : Dr. Rong Pan1
Bayesian sequential design for sensitivity experiments with hybrid responses1
Statistical Analytics for Health Data Science with SAS and R Statistical Analytics for Health Data Science with SAS and R1
Predictive Control Charts (PCC): A Bayesian approach in online monitoring of short runs1
Analysis of data from orthogonal minimally aliased response surface designs1
ANOVA and Mixed Models: A Short Introduction Using R ANOVA and Mixed Models: A Short Introduction Using R , by Lukas Meier. ETH Zurich, Switzerland: Chapman & Hall, 1
Bayesian analysis and follow-up experiments for supersaturated multistratum designs1
Reliability estimation following a field intervention1
Optimal designs for two-stage inference1
Message from the Editor0
Utilizing individual clear effects for intelligent factor allocations and design selections0
Construction of orthogonal-MaxPro Latin hypercube designs0
ASQ Books0
Computational and Statistical Methods for Chemical Engineering0
Hierarchical point process models for recurring safety critical events involving commercial truck drivers: A reliability framework for human performance modeling0
Change detection in parametric multivariate dynamic data streams using the ARMAX-GARCH model0
Order-of-addition mixture experiments0
Constructing control charts for autocorrelated data using an exhaustive systematic samples pooled variance estimator0
A note on a useful yet overlooked algorithm for total system Bayesian reliability estimation0
Use of the bias-corrected parametric bootstrap in sensitivity testing/analysis to construct confidence bounds with accurate levels of coverage0
Best practices for multi- and mixed-level supersaturated designs0
Cluster-based data filtering for manufacturing big data systems0
Online automatic anomaly detection for photovoltaic systems using thermography imaging and low rank matrix decomposition0
Lot acceptance testing using sample mean and extremum with finite qualification samples0
Multivariate reparameterized inverse Gaussian processes with common effects for degradation-based reliability prediction0
Degradation modeling using Bayesian hierarchical piecewise linear models: A case study to predict void swelling in irradiated materials0
Deep least squares one-class classification0
Design and Analysis of Experiments and Observational Studies using R0
Design and properties of the predictive ratio cusum (PRC) control charts0
Bayesian Modeling and Computation in Python0
Applied categorical and count data analysis, 2nd edition0
Interaction effects in pairwise ordering model0
Self-starting process monitoring based on transfer learning0
Addendum to “Estimating pure-error from near replicates in design of experiments”0
cpss: an R package for change-point detection by sample-splitting methods0
Joint monitoring of location and scale for modern univariate processes0
Foundations of Statistics for Data Scientists: With R and Python Foundations of Statistics for Data Scientists: With R and Python , by AlanAgresti and MariaKateri. Boca 0
Statistical Machine Learning – A Unified Framework0
Entropy-based adaptive design for contour finding and estimating reliability0
Editorial advice for selecting an open-source license for your next paper: Navigating copyrights for publicly facing AI chatbots0
Multi-node system modeling and monitoring with extended directed graphical models0
Structural tensor-on-tensor regression with interaction effects and its application to a hot rolling process0
Real-time monitoring of functional data0
Estimating pure-error from near replicates in design of experiments0
Optimal design subsampling from Big Datasets0
Knots and their effect on the tensile strength of lumber: A case study0
A review and comparison of control charts for ordinal samples0
ASQ Membership0
Simulation experiment design for calibration via active learning0
Design strategies and approximation methods for high-performance computing variability management0
Nonparametric monitoring of sunspot number observations0
Adaptive-region sequential design with quantitative and qualitative factors in application to HPC configuration0
The fish patty experiment: a strip-plot look0
Monitoring reliability under competing risks using field data0
Augmenting system tests with component tests for reliability assurance0
Construction of orthogonal maximin distance designs0
Two-level orthogonal screening designs with 80, 96, and 112 runs, and up to 29 factors0
Group-wise monitoring of multivariate data with missing values0
Statistical monitoring of the covariance matrix in multivariate processes: A literature review0
Phase I analysis of high-dimensional processes in the presence of outliers0
Nonparametric online monitoring of dynamic networks0
Category tree Gaussian process for computer experiments with many-category qualitative factors and application to cooling system design0
The 100th anniversary of the control chart0
Design and analysis of facility location experiments applied to sanitizer dispensers0
Introduction to time series modeling with applications in R0
Analyzing dispersion effects from replicated order-of-addition experiments0
A critique of a variety of “memory-based” process monitoring methods0
Explanatory Model Analysis: Explore, Explain, and Examine Predictive Models0
Industrial Data Analytics for Diagnosis and Prognosis: A Random Effects Modeling Approach0
Multilevel model versus recurrent neural network: A case study to predict student success or failure revisited0
A blocked staggered-level design for an experiment with two hard-to-change factors0
Sequential Latin hypercube design for two-layer computer simulators0
Data Science: A First Introduction Data Science: A First Introduction , by Tiffany Timbers, Trevor Campbell, and Melissa Lee. Boca Raton, FL: CRC Press, 2022, xxiii + 420
Phase I control chart for individual autocorrelated data: application to prescription opioid monitoring0
A comprehensive survey of recent research on profile data analysis0
Introducing ChatSQC: Enhancing statistical quality control with augmented AI0
Batch sequential designs in Bayesian preference elicitation with application to tradespace exploration for vehicle concept design0
A unified framework for high-dimensional data stream analysis in fault diagnosis0
A continual learning framework for adaptive defect classification and inspection0
Spatio-temporal process monitoring using exponentially weighted spatial LASSO0
The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach0
Data-level transfer learning for degradation modeling and prognosis0
Scalable level-wise screening experiments using locating arrays0
funcharts: control charts for multivariate functional data in R0
Knowledge-infused process monitoring for quality improvement in solar cell manufacturing processes0
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