Muazu Ramat Abujiya

King Fahd University of Petroleum and Minerals | KFUPM · Department of Mathematics and Statistics

There are certain areas of science and technology, such as agriculture, ecology, and environmental studies, that emphasize designing competent sampling strategies. The ranked set schemes, particularly the neoteric ranked set sampling (NRSS), are one method that meets such objectives. The NRSS provides plans that incorporates expert knowledge while...

An adaptive cumulative sum (CUSUM) control chart based on the classical exponential weighted moving average (EWMA) statistic and Huber’s function, symbolized as an ACUSUME control chart, is an enhanced form of the classical CUSUM control chart that can identify different sizes of shift. However, the classical EWMA statistic for the ACUSUME control...

The effect of parameter estimation emanating from the retrospective stage on the monitoring stage of control charts cannot be overemphasized. These effects are born of but are not limited to the practitioner-to-practitioner variations in the amount and type of samples employed to estimate the process parameters. Another major factor to this effect...

When control charts monitor processes with unknown parameters, preliminary samples are required to estimate the process parameters. These estimates are instrumental to constructing the control charts limits. The variability in the samples used by practitioners and the presence of extreme values in those samples affect the efficiency of the resultin...

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 pro...

An adaptive CUSUM (ACUSUM) control chart got special attention against classical CUSUM control chart to detect a shift of different sizes in the process location. Similarly, an ACUSUM based on classical EWMA statistic and score function, denoted as a \({\text{ACUSUM}}_{{\text{E}}}\) control chart, is improved form of classical CUSUM control chart a...

Lately, the multivariate setup of control charts, especially the memory‐less chart has received less attention of researchers as compared to the univariate setup. However, the multivariate setup is of paramount importance in this big‐data era. In this research work, we study the multivariate Shewhart chart for monitoring location parameter by exami...

Existing multivariate cumulative sum (MCUSUM) control charts involve entire associated variables of a process to monitor variations in the mean vector. In this study, we have offered MCUSUM control charts with principal component method (PCM). The proposed MCUSUM control charts with PCM capture the whole process variations using fewer latent variab...

Shewhart control charts with estimated control limits are widely used in practice. However, the estimated control limits are often affected by phase-I estimation errors. These estimation errors arise due to variation in the practitioner’s choice of sample size as well as the presence of outlying errors in phase-I. The unnecessary variation, due to...

Cumulative sum control charts that are based on the estimated control limits are extensively used in practice. Such control limits are often characterized by a Phase I estimation error. The presence of these errors can cause a change in the location and/or width of control limits resulting in a deprived performance of the control chart. In this stu...

Memory control chart such as multivariate CUSUM (MCUSUM) and multivariate EWMA (MEWMA) control charts are considered superior for the detection of small-to-moderate variation in the process mean vector. In this article, we have proposed two advanced forms of memory multivariate charts to identify the small amount of shifts in the process mean vecto...

The cumulative sum (CUSUM) control charts are widely used for the monitoring of normal processes for changes in the location and dispersion parameters. This study presents several CUSUM charts designed structures based on the ranked set sampling (RSS) data for overall efficient detection of changes in the process mean and variance. The run-length p...

The Shewhart and exponentially weighted moving average (EWMA) charts for nonconformities are the most widely used procedures of choice for monitoring Poisson observations in modern industries. Individually, the Shewhart EWMA charts are only sensitive to large and small shifts, respectively. To enhance the detection abilities of the two schemes in m...

The examination of product characteristics using a statistical tool is an important step in a manufacturing environment to ensure product quality. Several methods are employed for maintaining product quality assurance. Quality control charts, which utilize statistical methods, are normally used to detect special causes. Shewhart control charts are...

The Exponentially Weighted Moving Average (EWMA) control chart is an effective tool for the detection of small shifts in the process variability. This research studied the properties of EWMA charts based on unbiased sample variance, S², for monitoring of changes in the process dispersion. However, since an increase in process variance could lead to...

A control chart is an important statistical tool for monitoring disturbances in a statistical process, and it is richly applied in the industrial sector, the health sector and the agricultural sector, among others. The Shewhart chart and the Cumulative Sum (CUSUM) chart are traditionally used for detecting large shifts and small shifts, respectivel...

Statistical process control deals with monitoring process to detect disturbances in the process. These disturbances may be from the process mean or variance. In this study, we propose some charts that are efficient for detecting early shifts in dispersion parameter, by applying the Fast Initial Response feature. Performance measures such as average...

Quality control charts based on exponentially weighted moving average (EWMA) has been widely used for monitoring continuous process data. However, many quality characteristics of interest are in the form of counts for nonconformities and are often monitored by a Poisson model. In this article, we introduce a new design structure for the Poisson EWM...

The combined application of a Shewhart chart and cumulative sum (CUSUM) control chart is an effective tool for the detection of all sizes of process shifts as the scheme combines the advantages of a CUSUM at detecting small to moderate shifts and Shewhart for the quick detection of very large shifts. This article proposes new combined Shewhart–CUSU...

The cumulative sum (CUSUM) control chart is widely used in industry for the detection of small and moderate shifts in process location and dispersion. For efficient monitoring of process variability, we present several CUSUM control charts for monitoring changes in standard deviation of a normal process. The newly developed control charts based on...

This study analyzes the performance of combined applications of the Shewhart and cumulative sum (CUSUM) range R chart and proposes modifications based on well-structured sampling techniques, the extreme variations of ranked set sampling, for efficient monitoring of changes in the process dispersion. In this combined scheme, the Shewhart feature ena...

A control chart is a graphical tool used for monitoring a production process and quality improvement. One such charting procedure is the Shewhart-type control chart, which is sensitive mainly to the large shifts. For small shifts, the cumulative sum (CUSUM) control charts and exponentially weighted moving average (EWMA) control charts were proposed...

The cumulative sum (CUSUM) chart is a very effective control charting procedure used for the quick detection of small-sized and moderate-sized changes. It can detect small process shifts missed by the Shewhart-type control chart, which is sensitive mainly to large shifts. To further enhance the sensitivity of the CUSUM control chart at detecting ve...

The combination of Shewhart control charts and an exponentially weighted moving average (EWMA) control charts to simultaneously monitor shifts in the mean output of a production process has proven very effective in handling both small and large shifts. To improve the sensitivity of the control chart to detect off-target processes, we propose a comb...

For an improved monitoring of process parameters, it is generally desirable to have efficient designs of control charting structures. The addition of Shewhart control limits to the cumulative sum (CUSUM) control chart is a simple monitoring scheme sensitive to wide range of mean shifts. To improve the detection ability of the combined Shewhart–CUSU...

This article investigated the performance of the three common statistical control charts, the Shewhart x̅ chart, cumulative sum (CUSUM) chart, and exponentially weighted moving average (EWMA) chart for location using ranked set sampling (RSS) instead of the traditional simple random sampling (SRS). Considering a normal population, a Monte Carlo sim...

Until recently, the application of the runs rules was restricted to the Shewhart-type control charts. In this paper, we propose an EWMA control chart with fast initial response (FIR) using íµí¿ íµí¿ ⁄ runs rule scheme for monitoring Poisson observations. Using Monte Carlo simulations, we studied and compared the average run length (ARL), the Aver...

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The efficiency of Double Ranked Set Sampling (DRSS) suggested by Al-Saleh and Al- Kadiri (2000) as a modification of the Ranked Set Sampling (RSS) depends largely on the success in ranking the variable of interest. With large sample size, it becomes more difficult to apply in real life situations. With this, we introduce Median Double Ranked Set Sa...

Some centered moments of the bivariate chi-square distribution are derived by the use of raw product moments. Standardized moments up to the third order are calculated for the distribution. In case the components of bivariate chi-square distribution are uncorrelated, the moments, as expected, are in agreement with the resulting situation of indepen...

A method called the Remainder Method is proposed for the calculation of sample quantiles of a given order, for example, quartiles, hexatiles, octatiles, deciles and percentiles assuming that all the observations are distinct. Proof is given for a special case of deciles. The criterion ‘equisegmentation’ is proposed, namely that the number of observ...

International Journal of Mathematical Education in Science and Technology Publication details, including instructions for authors and subscription information:page/terms-and-conditions This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensi...

In this paper, an attempt is made to develop Quality Control Charts for monitoring the process mean based on Double Ranked Set Sampling (DRSS) rather than the traditional Simple Random Sampling (SRS). Considering a normal population and several shift values, the performance of the Average Run Length (ARL) of these new charts was compared with the c...