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The widespread environmental contamination of chlorpyrifos (CP) has raised human health concerns and necessitated cost-effective methods for its remediation. The current study evaluated the degradation behavior of CP in compost and biochar amended and unamended (original and sterilized) soils in an incubation trial. Two levels of CP (100 and 200 mg kg-1), compost and biochar (0.50%) were applied, and soil was collected at different time intervals. At the higher CP level (200 mg kg-1), CP a showed lower degradation rate (ƙ = 0.0102 mg kg-1 d-1) compared with a low CP level (ƙ = 0.0173 mg kg-1 d-1). The half-lives of CP were 40 and 68 days for CP at 100 and 200 mg kg-1 in original soil, respectively, and increased to 94 and 141 days in sterilized soils. CP degradation was accelerated in compost amended soils, while suppressed in biochar amended soils. Lower half lives of 20 and 37 days were observed with compost application at CP 100 and 200 mg kg-1 doses, respectively. The activities of soil enzymes were considerably affected by the CP contamination and significantly recovered in compost and biochar amended soils. In conclusion, the application of organic amendments especially compost is an important strategy for the remediation of CP contaminated soil.
Humera Aziz; Xiukang Wang; Ghulam Murtaza; Ambreen Ashar; Sarfraz Hussain; Muhammad Abid; Behzad Murtaza; Muhammad Hamzah Saleem; Sajid Fiaz; Shafaqat Ali. Evaluation of Compost and Biochar to Mitigate Chlorpyrifos Pollution in Soil and Their Effect on Soil Enzyme Dynamics. Sustainability 2021, 13, 9695 .
AMA StyleHumera Aziz, Xiukang Wang, Ghulam Murtaza, Ambreen Ashar, Sarfraz Hussain, Muhammad Abid, Behzad Murtaza, Muhammad Hamzah Saleem, Sajid Fiaz, Shafaqat Ali. Evaluation of Compost and Biochar to Mitigate Chlorpyrifos Pollution in Soil and Their Effect on Soil Enzyme Dynamics. Sustainability. 2021; 13 (17):9695.
Chicago/Turabian StyleHumera Aziz; Xiukang Wang; Ghulam Murtaza; Ambreen Ashar; Sarfraz Hussain; Muhammad Abid; Behzad Murtaza; Muhammad Hamzah Saleem; Sajid Fiaz; Shafaqat Ali. 2021. "Evaluation of Compost and Biochar to Mitigate Chlorpyrifos Pollution in Soil and Their Effect on Soil Enzyme Dynamics." Sustainability 13, no. 17: 9695.
In this study, we model a heterogeneous population assuming the three-component mixture of the Pareto distributions assuming type I censored data. In particular, we study some statistical properties (such as various entropies, different inequality indices, and order statistics) of the three-component mixture distribution. The ML estimation and the Bayesian estimation of the mixture parameters have been performed in this study. For the ML estimation, we used the Newton Raphson method. To derive the posterior distributions, different noninformative priors are assumed to derive the Bayes estimators. Furthermore, we also discussed the Bayesian predictive intervals. We presented a detailed simulation study to compare the ML estimates and Bayes estimates. Moreover, we evaluated the performance of different estimates assuming various sample sizes, mixing weights and test termination times (a fixed point of time after which all other tests are dismissed). The real-life data application is also a part of this study.
Muhammad Tahir; Ibrahim M. Almanjahie; Muhammad Abid; Ishfaq Ahmad. On Estimation of Three-Component Mixture of Distributions via Bayesian and Classical Approaches. Mathematical Problems in Engineering 2021, 2021, 1 -19.
AMA StyleMuhammad Tahir, Ibrahim M. Almanjahie, Muhammad Abid, Ishfaq Ahmad. On Estimation of Three-Component Mixture of Distributions via Bayesian and Classical Approaches. Mathematical Problems in Engineering. 2021; 2021 ():1-19.
Chicago/Turabian StyleMuhammad Tahir; Ibrahim M. Almanjahie; Muhammad Abid; Ishfaq Ahmad. 2021. "On Estimation of Three-Component Mixture of Distributions via Bayesian and Classical Approaches." Mathematical Problems in Engineering 2021, no. : 1-19.
A control chart has become a choice of quality practitioners for monitoring the output of industrial and production processes. It is a common practice to develop control charts under normality assumption or known distribution of the quality characteristic(s). These control charts are known as parametric charts. These charts may provide misleading results when the normality assumption of the process distribution is doubtful or unknown. In such situations, the nonparametric (NP) charts serve as an effective alternative for efficient monitoring of the process parameter(s). In this study, we have proposed a new NP double progressive mean chart based on sign statistic for detecting small shifts in the process location. The run-length (RL) properties of the proposed chart have been computed and compared with the existing competitor charts. We have used the most popular performance measure namely average RL (ARL) as an evaluation criterion. The comparisons revealed that the proposed chart performs better than its existing competitor’s charts. We have also considered a real-life data set related to a piston ring manufacturing process for the practical implementation of the proposed and existing charts.
Zameer Abbas; Hafiz Zafar Nazir; Muhammad Riaz; Muhammad Abid; Noureen Akhtar. An efficient nonparametric double progressive mean chart for monitoring of the process location. Communications in Statistics - Simulation and Computation 2021, 1 -14.
AMA StyleZameer Abbas, Hafiz Zafar Nazir, Muhammad Riaz, Muhammad Abid, Noureen Akhtar. An efficient nonparametric double progressive mean chart for monitoring of the process location. Communications in Statistics - Simulation and Computation. 2021; ():1-14.
Chicago/Turabian StyleZameer Abbas; Hafiz Zafar Nazir; Muhammad Riaz; Muhammad Abid; Noureen Akhtar. 2021. "An efficient nonparametric double progressive mean chart for monitoring of the process location." Communications in Statistics - Simulation and Computation , no. : 1-14.
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.
Muhammad Riaz; Zameer Abbas; Hafiz Nazir; Muhammad Abid. On the Development of Triple Homogeneously Weighted Moving Average Control Chart. Symmetry 2021, 13, 360 .
AMA StyleMuhammad Riaz, Zameer Abbas, Hafiz Nazir, Muhammad Abid. On the Development of Triple Homogeneously Weighted Moving Average Control Chart. Symmetry. 2021; 13 (2):360.
Chicago/Turabian StyleMuhammad Riaz; Zameer Abbas; Hafiz Nazir; Muhammad Abid. 2021. "On the Development of Triple Homogeneously Weighted Moving Average Control Chart." Symmetry 13, no. 2: 360.
Muhammad Abid; Sun Mei; Hafiz Zafar Nazir; Muhammad Riaz; Shahid Hussain; Zameer Abbas. A mixed cumulative sum homogeneously weighted moving average control chart for monitoring process mean. Quality and Reliability Engineering International 2020, 1 .
AMA StyleMuhammad Abid, Sun Mei, Hafiz Zafar Nazir, Muhammad Riaz, Shahid Hussain, Zameer Abbas. A mixed cumulative sum homogeneously weighted moving average control chart for monitoring process mean. Quality and Reliability Engineering International. 2020; ():1.
Chicago/Turabian StyleMuhammad Abid; Sun Mei; Hafiz Zafar Nazir; Muhammad Riaz; Shahid Hussain; Zameer Abbas. 2020. "A mixed cumulative sum homogeneously weighted moving average control chart for monitoring process mean." Quality and Reliability Engineering International , no. : 1.
In practical situations, the underlying process distribution sometimes deviates from normality and their distribution is partially or completely unknown. In that instance, rather than staying with/depending on the conventional parametric control charts, we consider non‐parametric control charts due to their exceptional performance. In this paper, a new non‐parametric double homogeneously weighted moving average sign control chart is proposed with the least assumptions. This chart is based on a sign test statistic for catching the smaller deviations in the process location. Run‐length (RL) properties of the proposed chart are studied with the help of Monte Carlo simulations. Both in‐control and out‐of‐control RL properties show that the proposed chart is a better contender as compared to some existing charts from the literature. A real‐life application for practical consideration of the proposed chart is also provided.
Muhammad Riaz; Muhammad Abid; Aroosa Shabbir; Hafiz Zafar Nazir; Zameer Abbas; Saddam Akber Abbasi. A non‐parametric double homogeneously weighted moving average control chart under sign statistic. Quality and Reliability Engineering International 2020, 37, 1544 -1560.
AMA StyleMuhammad Riaz, Muhammad Abid, Aroosa Shabbir, Hafiz Zafar Nazir, Zameer Abbas, Saddam Akber Abbasi. A non‐parametric double homogeneously weighted moving average control chart under sign statistic. Quality and Reliability Engineering International. 2020; 37 (4):1544-1560.
Chicago/Turabian StyleMuhammad Riaz; Muhammad Abid; Aroosa Shabbir; Hafiz Zafar Nazir; Zameer Abbas; Saddam Akber Abbasi. 2020. "A non‐parametric double homogeneously weighted moving average control chart under sign statistic." Quality and Reliability Engineering International 37, no. 4: 1544-1560.
Recently, a homogeneously weighted moving average (HWMA) chart has been suggested for the efficient detection of small shifts in the process mean. In this study, we have proposed a new one-sided HWMA chart to effectively detect small changes in the process dispersion. The run-length (RL) profiles like the average RL, the standard deviation RL, and the median RL are used as the performance measures. The RL profile comparisons indicate that the proposed chart has a better performance than its existing counterpart’s charts for detecting small shifts in the process dispersion. An application related to the Dhahran wind farm data is also part of this study.
Muhammad Riaz; Saddam Akber Abbasi; Muhammad Abid; Abdulhammed K. Hamzat. A New HWMA Dispersion Control Chart with an Application to Wind Farm Data. Mathematics 2020, 8, 2136 .
AMA StyleMuhammad Riaz, Saddam Akber Abbasi, Muhammad Abid, Abdulhammed K. Hamzat. A New HWMA Dispersion Control Chart with an Application to Wind Farm Data. Mathematics. 2020; 8 (12):2136.
Chicago/Turabian StyleMuhammad Riaz; Saddam Akber Abbasi; Muhammad Abid; Abdulhammed K. Hamzat. 2020. "A New HWMA Dispersion Control Chart with an Application to Wind Farm Data." Mathematics 8, no. 12: 2136.
In the statistical process control, the most useful tool to monitor the manufacturing processes in the industries is the control chart. Quality practitioners always desire the charting structure that identifies sustainable changes in the monitoring processes. The sensitivity of the control chart is improved when additional correlated auxiliary information about the study variable is introduced. The regression estimate in the form of auxiliary and supporting variables presents an unbiased and efficient statistic of the mean of the process variable. In this study, auxiliary information‐based moving average (AB‐MA) control chart is designed for efficient monitoring of shifts in the process location parameter. The performance of the AB‐MA control chart is evaluated and compared with existing charts using average run length and other run length characteristics. The comparison reveals that the AB‐MA control chart outperforms the competitors in detecting the small and medium changes in the process location parameter. The application of the proposal is also provided to implement it in real situation.
Muhammad Wasim Amir; Zeeshan Raza; Zameer Abbas; Hafiz Zafar Nazir; Noureen Akhtar; Muhammad Riaz; Muhammad Abid. On increasing the sensitivity of moving average control chart using auxiliary variable. Quality and Reliability Engineering International 2020, 37, 1198 -1209.
AMA StyleMuhammad Wasim Amir, Zeeshan Raza, Zameer Abbas, Hafiz Zafar Nazir, Noureen Akhtar, Muhammad Riaz, Muhammad Abid. On increasing the sensitivity of moving average control chart using auxiliary variable. Quality and Reliability Engineering International. 2020; 37 (3):1198-1209.
Chicago/Turabian StyleMuhammad Wasim Amir; Zeeshan Raza; Zameer Abbas; Hafiz Zafar Nazir; Noureen Akhtar; Muhammad Riaz; Muhammad Abid. 2020. "On increasing the sensitivity of moving average control chart using auxiliary variable." Quality and Reliability Engineering International 37, no. 3: 1198-1209.
Memory‐type control charts play a significant role to identify slight changes in the parameters of the production process. In this article, we have proposed a new cumulative sum chart that utilizes the statistic of the homogeneously weighted moving average chart. The performance of the proposed chart is studied using Monte Carlo simulations. The proposed chart is compared with some existing charts under different run length profiles. The run length profile comparisons reveal that the proposed chart performs superior as compared to the existing control charts. A real‐life application using a manufacturing process dataset is also part of this study.
Muhammad Abid; Sun Mei; Hafiz Zafar Nazir; Muhammad Riaz; Shahid Hussain. A mixed HWMA‐CUSUM mean chart with an application to manufacturing process. Quality and Reliability Engineering International 2020, 37, 618 -631.
AMA StyleMuhammad Abid, Sun Mei, Hafiz Zafar Nazir, Muhammad Riaz, Shahid Hussain. A mixed HWMA‐CUSUM mean chart with an application to manufacturing process. Quality and Reliability Engineering International. 2020; 37 (2):618-631.
Chicago/Turabian StyleMuhammad Abid; Sun Mei; Hafiz Zafar Nazir; Muhammad Riaz; Shahid Hussain. 2020. "A mixed HWMA‐CUSUM mean chart with an application to manufacturing process." Quality and Reliability Engineering International 37, no. 2: 618-631.
Recently, a new double progressive mean (DPM) control chart has been proposed in the literature of statistical process control. In the said proposal, an important term is missing in the variance expression of the DPM statistic that affects the detection ability of the proposed chart. In this study, we have derived and provided the correct version of the said variance along with its corresponding control limits. The run length profiles of the DPM chart are investigated, and the results are updated for the new version of the limits. Moreover, a sensitivity analysis between DPM and progressive mean charts based on the different choices of the design parameter is also included in this study. It is revealed that the revised version offers even more efficient outcomes than the previous ones. In addition, a real dataset application is also presented for practical considerations of the refined version.
Muhammad Riaz; Muhammad Abid; Zameer Abbas; Hafiz Zafar Nazir. An enhanced approach for the progressive mean control charts: A discussion and comparative analysis. Quality and Reliability Engineering International 2020, 37, 1 -9.
AMA StyleMuhammad Riaz, Muhammad Abid, Zameer Abbas, Hafiz Zafar Nazir. An enhanced approach for the progressive mean control charts: A discussion and comparative analysis. Quality and Reliability Engineering International. 2020; 37 (1):1-9.
Chicago/Turabian StyleMuhammad Riaz; Muhammad Abid; Zameer Abbas; Hafiz Zafar Nazir. 2020. "An enhanced approach for the progressive mean control charts: A discussion and comparative analysis." Quality and Reliability Engineering International 37, no. 1: 1-9.
The exponentially weighted moving average (EWMA) control chart is a memory chart that is widely used in process monitoring to spot small and persistent disturbances in the process parameter(s). This chart requires normality of the quality characteristic(s) of interest and a smaller choice of smoothing parameter. Any deviations from these conditions affect its performance in terms of efficiency and robustness. For the said two concerns, this study develops a new mixed EWMA chart under progressive setup (mixed EWMA–progressive mean [MEP] chart). The proposed MEP chart combines the advantages of robustness (under nonnormal scenarios) and high sensitivity to small and persistent shifts in the process mean. The performance of the proposed MEP control chart is evaluated in terms of average run length and some other characteristics of run length distribution. The assessment of the proposed chart is made under standard normal, student's t , gamma, Laplace, logistic, exponential, contaminated normal and lognormal distributions. The performance of the proposed MEP chart is also compared with some existing competitors including the classical EWMA, the classical cumulative sum (CUSUM), the homogenously weighted moving average, the mixed EWMA–CUSUM, the mixed CUSUM–EWMA and the double EWMA charts. The analysis reveals that the proposal of this study offers a superior design structure relative to its competing counterparts. An application from substrates manufacturing process (in which flow width of the resist is the key quality characteristic) is also provided in the study.
Zameer Abbas; Hafiz Zafar Nazir; Noureen Akhtar; Muhammad Riaz; Muhammad Abid. On developing an exponentially weighted moving average chart under progressive setup: An efficient approach to manufacturing processes. Quality and Reliability Engineering International 2020, 36, 2569 -2591.
AMA StyleZameer Abbas, Hafiz Zafar Nazir, Noureen Akhtar, Muhammad Riaz, Muhammad Abid. On developing an exponentially weighted moving average chart under progressive setup: An efficient approach to manufacturing processes. Quality and Reliability Engineering International. 2020; 36 (7):2569-2591.
Chicago/Turabian StyleZameer Abbas; Hafiz Zafar Nazir; Noureen Akhtar; Muhammad Riaz; Muhammad Abid. 2020. "On developing an exponentially weighted moving average chart under progressive setup: An efficient approach to manufacturing processes." Quality and Reliability Engineering International 36, no. 7: 2569-2591.
Control chart is a well‐known tool for monitoring the performance of an ongoing process. The variability of a process is an important parameter that may deteriorate the process performance if it is not taken care on time. In this study, we have proposed some new auxiliary information‐based exponentially weighted moving average (EWMA) charts for improved monitoring of process variability. We employed auxiliary information in some useful forms including ratio, regression, power ratio, ratio exponential, ratio regression, power ratio regression, and ratio exponential regression estimators. The performance of the newly developed charts is evaluated and compared with some existing charts (viz., the NEWMA, the Improved R, the Synthetic R, and the classical R charts), using some useful measures such as average run length (ARL), extra quadratic loss, and relative ARL. The comparative analysis revealed that the proposed charts outperform their counterparts, especially when there is a strong relationship between the study and the auxiliary variables. Finally, an illustrative example is provided for the monitoring of air quality data.
Saddam Akber Abbasi; Muhammad Riaz; Shabbir Ahmad; Ridwan A. Sanusi; Muhammad Abid. New efficient exponentially weighted moving average variability charts based on auxiliary information. Quality and Reliability Engineering International 2020, 36, 2203 -2224.
AMA StyleSaddam Akber Abbasi, Muhammad Riaz, Shabbir Ahmad, Ridwan A. Sanusi, Muhammad Abid. New efficient exponentially weighted moving average variability charts based on auxiliary information. Quality and Reliability Engineering International. 2020; 36 (7):2203-2224.
Chicago/Turabian StyleSaddam Akber Abbasi; Muhammad Riaz; Shabbir Ahmad; Ridwan A. Sanusi; Muhammad Abid. 2020. "New efficient exponentially weighted moving average variability charts based on auxiliary information." Quality and Reliability Engineering International 36, no. 7: 2203-2224.
Most of the research work on ratio, product, and regression estimators are usually based on conventional measures such as mean, quartiles, semi-interquartile range, semi-interquartile average, coefficient of skewness, coefficient of kurtosis, etc. The efficiency of these conventional measures is doubtful in the presence of extreme values in the data. In this paper, we propose an enhanced family of estimators for estimating the population variance using unconventional location measures such as tri-mean, Hodges-Lehmann, and decile mean of an auxiliary variable. The performance of the proposed family of estimators is compared with the existing estimators using a simulation study and two real populations. Also, the robustness of the proposed estimators was examined using an environment protection data with extreme values. The results showed that the proposed family performs better than its competitors not only in simple conditions but is also robust in the presence of extreme values.
Muhammad Awais Gulzar; Muhammad Abid; Hafiz Zafar Nazir; Faisal Maqbool Zahid; Muhammad Riaz. On enhanced estimation of population variance using unconventional measures of an auxiliary variable. Journal of Statistical Computation and Simulation 2020, 90, 2180 -2197.
AMA StyleMuhammad Awais Gulzar, Muhammad Abid, Hafiz Zafar Nazir, Faisal Maqbool Zahid, Muhammad Riaz. On enhanced estimation of population variance using unconventional measures of an auxiliary variable. Journal of Statistical Computation and Simulation. 2020; 90 (12):2180-2197.
Chicago/Turabian StyleMuhammad Awais Gulzar; Muhammad Abid; Hafiz Zafar Nazir; Faisal Maqbool Zahid; Muhammad Riaz. 2020. "On enhanced estimation of population variance using unconventional measures of an auxiliary variable." Journal of Statistical Computation and Simulation 90, no. 12: 2180-2197.
Control charts are commonly used tools that deal with monitoring of process parameters in an efficient manner. Multivariate control charts are more practical and are of greater importance for timely detection of assignable causes in multiple quality characteristics. This study deals with multivariate memory control charts to address smaller shifts in process mean vector. By adopting a new homogeneous weighting scheme, we have designed an efficient structure for multivariate process monitoring. We have also investigated the effect of an estimated variance covariance matrix on the proposed chart by considering different numbers and sizes of subgroups. We have evaluated the performance of the newly proposed multivariate chart under different numbers of quality characteristics and varying sample sizes. The performance measures used in this study include average run length, standard deviation run length, extra quadratic loss, and relative average run length. The performance analysis revealed that the proposed control chart outperforms the usual scheme under both known and estimated parameters. An application of the study proposal is also presented using a data set related to Olympic archery, for the monitoring of the location of arrows over the concentric rings on the archery board.
Nasir Abbas; Muhammad Riaz; Shabbir Ahmad; Muhammad Abid; Babar Zaman. On the Efficient Monitoring of Multivariate Processes with Unknown Parameters. Mathematics 2020, 8, 823 .
AMA StyleNasir Abbas, Muhammad Riaz, Shabbir Ahmad, Muhammad Abid, Babar Zaman. On the Efficient Monitoring of Multivariate Processes with Unknown Parameters. Mathematics. 2020; 8 (5):823.
Chicago/Turabian StyleNasir Abbas; Muhammad Riaz; Shabbir Ahmad; Muhammad Abid; Babar Zaman. 2020. "On the Efficient Monitoring of Multivariate Processes with Unknown Parameters." Mathematics 8, no. 5: 823.
Variation is an important phenomenon of the output of every manufacturing and production process. To deal with the natural and special cause variations in the process, quality practitioners mostly apply control charts. There have been regular advancements over time in the design structures of these charts such as runs rules, fast initial response, sampling mechanisms among many others. In this article, auxiliary‐information‐based progressive mean (AIB‐PM) control chart has been proposed, in which study variable is found correlated with another auxiliary variable. The development of the proposed AIB‐PM structure utilises both the study and auxiliary variables. It is based on the regression estimator to introduce an unbiased and efficient estimate of the location parameter of the study variable. The performance assessment is carried out using average run length as a metric under zero‐state and steady‐state modes. The proposed AIB‐PM chart is compared with some existing competitors and found that it performs uniformly superior than the existing competitors at small and persistent shifts in the process mean. An illustrative example using a real data set is presented to show the implementation of the proposed method.
Zameer Abbas; Hafiz Zafar Nazir; Noureen Akhtar; Muhammad Riaz; Muhammad Abid. On designing a progressive mean chart for efficient monitoring of process location. Quality and Reliability Engineering International 2020, 36, 1716 -1730.
AMA StyleZameer Abbas, Hafiz Zafar Nazir, Noureen Akhtar, Muhammad Riaz, Muhammad Abid. On designing a progressive mean chart for efficient monitoring of process location. Quality and Reliability Engineering International. 2020; 36 (5):1716-1730.
Chicago/Turabian StyleZameer Abbas; Hafiz Zafar Nazir; Noureen Akhtar; Muhammad Riaz; Muhammad Abid. 2020. "On designing a progressive mean chart for efficient monitoring of process location." Quality and Reliability Engineering International 36, no. 5: 1716-1730.
In the service and manufacturing industry, memory‐type control charts are extensively applied for monitoring the production process. These types of charts have the ability to efficiently detect disturbances, especially of smaller amount, in the process mean and/or dispersion. Recently, a new homogeneously weighted moving average (HWMA) chart has been proposed for efficient monitoring of smaller shifts. In this study, we have proposed a new double HWMA (DHWMA) chart to monitor the changes in the process mean. The run length profile of the proposed DHWMA chart is evaluated and compared with some existing control charts. The outcomes reveal that the DHWMA chart shows better performance over its competitor charts. The effect of non‐normality (in terms of robustness) and the estimation of the unknown parameters on the performance of the DHWMA chart are also investigated as a part of this study. Finally, a real‐life industrial application is offered to demonstrate the proposal for practical considerations.
Muhammad Abid; Aroosa Shabbir; Hafiz Zafar Nazir; Rehan Ahmed Khan Sherwani; Muhammad Riaz. A double homogeneously weighted moving average control chart for monitoring of the process mean. Quality and Reliability Engineering International 2020, 36, 1513 -1527.
AMA StyleMuhammad Abid, Aroosa Shabbir, Hafiz Zafar Nazir, Rehan Ahmed Khan Sherwani, Muhammad Riaz. A double homogeneously weighted moving average control chart for monitoring of the process mean. Quality and Reliability Engineering International. 2020; 36 (5):1513-1527.
Chicago/Turabian StyleMuhammad Abid; Aroosa Shabbir; Hafiz Zafar Nazir; Rehan Ahmed Khan Sherwani; Muhammad Riaz. 2020. "A double homogeneously weighted moving average control chart for monitoring of the process mean." Quality and Reliability Engineering International 36, no. 5: 1513-1527.
The moving average (MA), exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts are popular control charts to detect small shifts quickly in process parameters. In this study, we evaluate the performance of the EWMA chart for monitoring exponentially distributed quality characteristics based on moving average statistics. The average run length and some other associated characteristics are used as performance measures of the chart. The concept of using the probability of detection for the performance assessment of this chart has been criticized in this study. A real-life application is also provided for practical consideration.
Saddam Akber Abbasi; Muhammad Abid; Muhammad Riaz; Hafiz Zafar Nazir. Performance evaluation of moving average-based EWMA chart for exponentially distributed process. Journal of the Chinese Institute of Engineers 2020, 43, 365 -372.
AMA StyleSaddam Akber Abbasi, Muhammad Abid, Muhammad Riaz, Hafiz Zafar Nazir. Performance evaluation of moving average-based EWMA chart for exponentially distributed process. Journal of the Chinese Institute of Engineers. 2020; 43 (4):365-372.
Chicago/Turabian StyleSaddam Akber Abbasi; Muhammad Abid; Muhammad Riaz; Hafiz Zafar Nazir. 2020. "Performance evaluation of moving average-based EWMA chart for exponentially distributed process." Journal of the Chinese Institute of Engineers 43, no. 4: 365-372.
The use of auxiliary information in survey sampling to enhance the efficiency of the estimators of population parameters is a common phenomenon. Generally, the ratio and regression estimators are developed by using the known information on conventional parameters of the auxiliary variables, such as variance, coefficient of variation, coefficient of skewness, coefficient of kurtosis, or correlation between the study and auxiliary variable. The efficiency of these estimators is dubious in the presence of outliers in the data and a nonsymmetrical population. This study presents improved variance estimators under simple random sampling without replacement with the assumption that the information on some nonconventional dispersion measures of the auxiliary variable is readily available. These auxiliary variables can be the inter-decile range, sample inter-quartile range, probability-weighted moment estimator, Gini mean difference estimator, Downton’s estimator, median absolute deviation from the median, and so forth. The algebraic expressions for the bias and mean square error of the proposed estimators are obtained and the efficiency conditions are derived to compare with the existing estimators. The percentage relative efficiencies are used to numerically compare the results of the proposed estimators with the existing estimators by using real datasets, indicating the supremacy of the suggested estimators.
Farah Naz; Tahir Nawaz; Tianxiao Pang; Muhammad Abid. Use of Nonconventional Dispersion Measures to Improve the Efficiency of Ratio-Type Estimators of Variance in the Presence of Outliers. Symmetry 2019, 12, 16 .
AMA StyleFarah Naz, Tahir Nawaz, Tianxiao Pang, Muhammad Abid. Use of Nonconventional Dispersion Measures to Improve the Efficiency of Ratio-Type Estimators of Variance in the Presence of Outliers. Symmetry. 2019; 12 (1):16.
Chicago/Turabian StyleFarah Naz; Tahir Nawaz; Tianxiao Pang; Muhammad Abid. 2019. "Use of Nonconventional Dispersion Measures to Improve the Efficiency of Ratio-Type Estimators of Variance in the Presence of Outliers." Symmetry 12, no. 1: 16.
Process control measures are mostly applied in production and manufacturing industries. The most important tool used in these disciplines is control chart. In manufacturing and production processes, when the quality characteristic of interest cannot be directly measured, it becomes essential to apply attribute control charts. To monitor fraction nonconforming of the output, quality practitioners mostly prefer p‐chart. In this article, a new progressive mean (PM) control chart is being proposed for monitoring drift in proportion of nonconforming products. The design evaluations of the proposed chart are made and compared through different properties of run length distribution, such as average run length (ARL), standard deviation of run length (SDRL), and some percentile points. The performance of the proposed chart is assessed under zero‐state and steady‐state scenarios. The proposed PM chart is compared with p‐chart, moving average (MA) chart, optimal CUSUM chart, modified exponentially weighted moving average (EWMA) chart, and runs rules p‐charts for monitoring fraction nonconforming. The proposed chart spots efficiently sustained disturbances in the process as compared with their existing counterparts. Two illustrative examples are also provided; one from real‐life application of nonconforming bearing and seal assemblies data and the other from simulated data for the implementation of PM chart.
Zameer Abbas; Hafiz Zafar Nazir; Noureen Akhtar; Muhammad Abid; Muhammad Riaz. On designing an efficient control chart to monitor fraction nonconforming. Quality and Reliability Engineering International 2019, 36, 547 -564.
AMA StyleZameer Abbas, Hafiz Zafar Nazir, Noureen Akhtar, Muhammad Abid, Muhammad Riaz. On designing an efficient control chart to monitor fraction nonconforming. Quality and Reliability Engineering International. 2019; 36 (2):547-564.
Chicago/Turabian StyleZameer Abbas; Hafiz Zafar Nazir; Noureen Akhtar; Muhammad Abid; Muhammad Riaz. 2019. "On designing an efficient control chart to monitor fraction nonconforming." Quality and Reliability Engineering International 36, no. 2: 547-564.
Statistical process control (SPC) has its own importance in the field of quality control. In SPC, control charts are significant tools to monitor process parameters, and exponentially weighted moving average (EWMA) control chart is one such tool. It is a memory-type chart, which is used to target mainly the smaller shifts in the process parameters. Adaptive EWMA (AEWMA) scheme is used to identify small as well as large shifts. EWMA and AEWMA are based on the assumption of normality, which is quite hard to find in practice, and there are many situations where outliers are occasionally present. In the current study, we have proposed four robust adaptive EWMA schemes for monitoring process location parameter. We have investigated their performance under uncontaminated normal and contaminated normal environments. We have carried out comparisons amongst different competing charts based on average run length (ARL), standard deviation of run length (SDRL) and different percentiles of run length distribution. Two examples related to manufacturing processes are also provided for practical implementation of the proposed schemes.
Hafiz Zafar Nazir; Tahir Hussain; Noureen Akhtar; Muhammad Abid; Muhammad Riaz. Robust adaptive exponentially weighted moving average control charts with applications of manufacturing processes. The International Journal of Advanced Manufacturing Technology 2019, 105, 733 -748.
AMA StyleHafiz Zafar Nazir, Tahir Hussain, Noureen Akhtar, Muhammad Abid, Muhammad Riaz. Robust adaptive exponentially weighted moving average control charts with applications of manufacturing processes. The International Journal of Advanced Manufacturing Technology. 2019; 105 (1-4):733-748.
Chicago/Turabian StyleHafiz Zafar Nazir; Tahir Hussain; Noureen Akhtar; Muhammad Abid; Muhammad Riaz. 2019. "Robust adaptive exponentially weighted moving average control charts with applications of manufacturing processes." The International Journal of Advanced Manufacturing Technology 105, no. 1-4: 733-748.