A performance-based framework to prioritise underutilised historical buildings for adaptive reuse interventions in New Zealand

Measurement error is a usually met distortion factor in real-world applications that influences the outcome of a process. The performance of the control charts can be affected in the presence of measurement error which also leads to erroneous conclusions regarding the average run length. In this paper, we proposed regression estimator-based mixed exponentially weighted moving average-cumulative sum (MxEMCUS) control chart to monitor the process mean and investigate the effect of measurement error on shift detection ability of the proposed control chart. The performance of MxEMCUS control chart is evaluated in the cases of mean shift with and without measurement error. The linear covariate model is used to evaluate the control chart in the presence of measurement error. The case of multiple measurements and linear increasing variance is also investigated in the presence of measurement error. The average run length and standard deviation of run length are used as the performance measuring tool. Based on simulation results, it is concluded that in the presence of measurement error, proposed chart has better performance as compared to other existing charts. An example with real data set is given to demonstrate the implementation of MxEMCUS control chart.

Auxiliary Information Based Mixed EWMA–CUSUM Mean Control Chart with Measurement Error

Attribute inspection control charts for the joint monitoring of mean and variance

The coefficient of variation is a variability measure used in manufacturing industries when the process mean fluctuates with time and process standard deviation is a linear function of process mean. In this paper, we proposed an exponential weighted moving coefficient of variation control chart by using three parametric log-normal transformations under ranked set sampling with different sample sizes. The average run length and standard deviation of run lengths are computed with an extensive Monte Carlo simulation study to measure the performance of the proposed chart. The comparison of the proposed control chart is made with considered CV control charts and concluded that the proposed control chart is efficient as compared to considered CV control charts to detect the small or moderate shifts in the process CV. An example is presented to demonstrate the implementation of the proposed control chart on the real data set.

EWMA Control Chart for Coefficient of Variation Using Log-Normal Transformation Under Ranked Set Sampling

The exponentially weighted moving average (EWMA) control chart is good enough to capture a small/moderate shift in the process-mean as it has the ability to provide good detection of a said shift b...

Enhancing the performance of exponential weighted moving average control chart using paired double ranked set sampling

In this paper, a joint monitoring control chart for process mean and variance is proposed under pair ranked set sampling (PRSS) procedures using generalized likelihood ratio (GLR) test statistic discussed by Zhang et al. (Qual Reliab Eng Int 26(1):63–73, 2010) and Ghashghaei et al. (Qual Reliab Eng Int 32(8):3035–3050, 2016). The results revealed that using PRSS method can increase the performance of the monitoring structure in identifying mean shifts, variance shifts as well as joint shifts even the PRSS will cut down the number of units to be sampled from the population to half of what is needed in RSS competitors. The practical implication of our proposed method is explained by using a real data set.

Joint Monitoring of Mean and Variance Using Likelihood Ratio Test Statistic Under Pair Ranked Set Sampling Scheme

This paper explores the effect of measurement errors on a joint monitoring control chart by using three different techniques (i) covariate method (ii) multiple measurements (iii) linear increasing 

Joint monitoring of mean and variance using likelihood ratio test statistic with measurement error

Quality control charts are widely used as a process monitoring tool. In this article, an attempt is made to develop a new control chart that integrates the exponentially weighted moving average pro...

Joint monitoring of mean and variance under double ranked set sampling using likelihood ratio test statistic

This study is focused on ranked set sampling theory which is constructive and cost efficient. Estimation for population mean for different sample sizes based on new ranked set sampling (NRS...

A new scheme using the ranked sets

In this paper, a modified extreme ranked set sampling (MERSS) scheme is presented. The ratio estimator under the modified scheme is discussed, and expression of mean square error is derived. The performance of the ratio estimator under MERSS is compared with simple random sampling (SRS), ranked set sampling (RSS), median ranked set sampling (MRSS), quartile ranked set sampling (QRSS) and extreme ranked set sampling (ERSS). A simulation study is conducted, and the results showed that MERSS provides the efficient results as compared to SRS, RSS, MRSS, QRSS and ERSS.

Farah Arif

Papers

Joint Monitoring of Mean and Variance Using Likelihood Ratio Test Statistic Under Pair Ranked Set Sampling Scheme

Joint monitoring of mean and variance using likelihood ratio test statistic with measurement error

Joint monitoring of mean and variance under double ranked set sampling using likelihood ratio test statistic

A new scheme using the ranked sets

Modified Extreme Ranked Sets Sampling with Auxiliary Variable