Environmental control: charting a course for the Navajo reservation through road construction, 1945–1978

This article examines the history of road planning in the decades following the Second World War on the Navajo Nation. Federal highway planners and Navajo residents had conflicting ideas about the role of roads in the Nation's postwar development. The planners’ support for highways near uranium mines undermined efforts towards Navajo self-development and modernization. Federally planned and subsidized highways granted extractive industries control over large portions of the Nation. Those highways locked in a regime of environmental exploitation that caused severe and debilitating public health consequences for Navajo communities.

Using the Statistical Process Control to evaluate the learning process in Higher Education / Aplicación del Control Estadístico de Procesos para la evaluación de procesos de aprendizaje en la Educación Superior

The purpose of this paper is to propose an approach for incorporating Statistical Process Control (SPC) charting technique to monitor and continuously improve the learning processes by monitoring the satisfaction of students who used an interactive computer-based learning material, which was produced to solve problems in the Operation Management course. By applying SPC methods, the authors examine the sources of process variation (common or special causes) and analyse the ability of teaching strategies to ensure the acquisition and development of the competencies and skills demanded in current university studies. A total of 184 students participated in the learning experience. The findings show that the learning process is under control and therefore the variation of process is due to common causes. However, the Capability Analysis carried out, reveals that process has not enough capacity to achieve the specifications required by the teachers involved in the educational project. This quantitative approach will not only allow self-assessment, but can be used for comparative purposes (other teaching strategies, colleges, etc.). Thus, the control charting is a complementary assessment technique that should be included within the current Quality and Learning Assurance Systems at higher education institutions.

Robust Multivariate Shewhart Control Chart Based on the Stahel-Donoho Robust Estimator and Mahalanobis Distance for Multivariate Outlier Detection

While researchers and practitioners may seamlessly develop methods of detecting outliers in control charts under a univariate setup, detecting and screening outliers in multivariate control charts pose serious challenges. In this study, we propose a robust multivariate control chart based on the Stahel-Donoho robust estimator (SDRE), whilst the process parameters are estimated from phase-I. Through intensive Monte-Carlo simulation, the study presents how the estimation of parameters and presence of outliers affect the efficacy of the Hotelling T2 chart, and then how the proposed outlier detector brings the chart back to normalcy by restoring its efficacy and sensitivity. Run-length properties are used as the performance measures. The run length properties establish the superiority of the proposed scheme over the default multivariate Shewhart control charting scheme. The applicability of the study includes but is not limited to manufacturing and health industries. The study concludes with a real-life application of the proposed chart on a dataset extracted from the manufacturing process of carbon fiber tubes.

Monitoring the Zero-Inflated Time Series Model of Counts with Random Coefficient

In this research, we consider monitoring mean and correlation changes from zero-inflated autocorrelated count data based on the integer-valued time series model with random survival rate. A cumulative sum control chart is constructed due to its efficiency, the corresponding calculation methods of average run length and the standard deviation of the run length are given. Practical guidelines concerning the chart design are investigated. Extensive computations based on designs of experiments are conducted to illustrate the validity of the proposed method. Comparisons with the conventional control charting procedure are also provided. The analysis of the monthly number of drug crimes in the city of Pittsburgh is displayed to illustrate our current method of process monitoring.

On the Development of Triple Homogeneously Weighted Moving Average Control Chart

To detect sustainable changes in the manufacturing processes, memory-type charting schemes are frequently functioning. The recently designed, homogenously weighted moving average (HWMA) technique is effective for identifying substantial changes in the processes. To make the HWMA chart more effective for persistent shifts in the industrial processes, a double HWMA (DHWMA) chart has been proposed recently. This study intends to develop a triple HWMA (THWMA) chart for efficient monitoring of the process mean under zero- and steady-state scenarios. The non-normal effects of monitoring characteristics under in-control situations for heavy-tailed highly skewed and contaminated normal environments are computed under both states. The relative efficiency of the proposed structure is compared with HWMA, DHWMA, exponentially weighted moving average (EWMA), double EWMA, and the more effective triple EWMA control charting schemes. The relative analysis reveals that the proposed THWMA design performs more efficiently than the existing counterparts. An illustrative application related to substrate manufacturing is also incorporated to demonstrate the proposal.

Inverse Maxwell Distribution and Statistical Process Control: An Efficient Approach for Monitoring Positively Skewed Process

(1) Background: The literature discusses the inverse Maxwell distribution theoretically without application. Control charting is promising, but needs development for inverse Maxwell processes. (2) Methods: Thus, we develop the VIM control chart for monitoring the inverse Maxwell scale parameter and studied its statistical properties. The chart’s performance is evaluated using power curves and run length properties. (3) Results: Further, we use simulated data to compare the shift detection capability of our chart with Weibull, gamma, and lognormal charts. (4) Conclusion: The analysis demonstrates our chart’s efficiency for monitoring skewed processes. Finally, we apply our chart for monitoring real world lifetimes of car brake pads.

Control Charting Genomic Data

Background Control charting is routine in the quality assurance of traditional clinical laboratory testing. Genomic tests are not typically managed by control charting. We examined control charting to monitor the performance of a clinical next-generation sequencing (NGS) assay. Methods We retrospectively examined 3 years of control material (NA12878) data from clinical genomic epilepsy testing. Levey-Jennings plots were used to visualize changes in control material depth of sequencing coverage in genomic regions of an epilepsy genomic panel. Changes in depth of coverage were correlated with changes in the manufactured lot of capture probe reagent. Depth of coverage was also correlated between quality control material and clinical samples. Results Fifty-seven sequencing runs of NA12878 were analyzed for 1811 genomic regions targeting 108 genes. Manufactured probe lot changes were associated with significant changes in the average coverage of 537 genomic regions and the lowest coverage of 173 regions (using a critical cut-off of P < 5.52 x 10−6). Genomic regions with the highest sensitivity to lot-to-lot variation by average sequencing depth of coverage were not the same regions with the highest sensitivity by lowest sequencing depth of coverage. Levey-Jennings plots displayed differences in genomic depth of coverage across capture probe reagent lot changes. There was moderate correlation between the changes in depth of sequencing across lot changes for control material and clinical cases (r2 = 0.45). Conclusions Genomic control charting can be used routinely by clinical laboratories to monitor assay performance and ensure the quality of testing.