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Quality Technology & Quantitative Management is a peer-reviewed journal published by Taylor & Francis, covering Advanced Statistical Process Monitoring, Reliability and Maintenance Optimization, Advanced Statistical Methods and Models.
| Publisher | Taylor & Francis |
|---|---|
| Reference style | Author–year (Chicago, T&F) Author–year — (Smith, 2023) in the text Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." Quality Technology & Quantitative Management 12 (3): 45–58.
Formats any DOI in Quality Technology & Quantitative Management style. No sign-up. |
| Publishes research in | Advanced Statistical Process Monitoring Reliability and Maintenance Optimization Advanced Statistical Methods and Models Advanced Queuing Theory Analysis Statistical Distribution Estimation and Applications |
| ISSN | 1684-3703 |
| Citation impact (2-yr) | 2.3 |
| h-index | 41 |
| i10-index | 378 |
| Total citations | 11,018 |
| Top institutions publishing here | National Taichung University of Science and Technology |
| Journal website | www.tandfonline.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
In the control chart literature, a number of one-and two-chart schemes has been developed to simultaneously monitor the mean and variance parameters of normally distributed processes. These “joint” monitoring schemes are useful for situations in which special causes can result in a change in both the mean and the variance, and they allow practitioners to…
In this paper, we review multivariate control charts designed for monitoring changes in a covariance matrix that have been developed in the last 15 years. The focus is on control charts developed for multivariate normal processes, assuming that independent subgroups of observations or independent individual observations are sampled as process monitoring proceeds. Control charts developed…
AbstractThe inference about the statistical properties of quality control methodologies is based on the assumptions of normality and independence. In real industrial environments though process data is often correlated or exhibits some serial dependence affecting the efficiency of Statistical Process Control (SPC) methodologies. New technology gives managers the option of using more sophisticated SPC models…
This paper proposes a practical methodology for the solution of multi-objective system reliability optimization problems. The new method is based on the sequential combination of multi-objective evolutionary algorithms and data clustering on the prospective solutions to yield a smaller, more manageable sets of prospective solutions. Existing methods for multiple objective problems involve either the consolidation…
In this paper, we extend the exponentially weighted moving average (EWMA) technique to double exponentially weighted moving average (DEWMA) technique. We show that DEWMA mean charts perform better than EWMA mean charts in detecting small mean shifts ranging from 0.1 to 0.5 of the process standard deviation, and that the two types of charts perform…
