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Various outcome-based education (OBE) performance measurement approaches demonstrate students' attainment of a set of Graduate Attributes (GA) in the engineering programme. This paper presents four measurement models, namely the indicative, explicit, GA assessment, and culminating models, to measure GA attainment. The indicative model uses the total assessment mark as an indicator for GA attainment, whereas the explicit model utilises a specific mark from an assessment. The GA assessment and culminating models utilise the explicit approach from assessments that fulfil the GA requirement. The culminating model only consists of assessments from advanced and capstone courses. This research aims to determine whether the indicative model that uses an indicator approach can significantly represent GA attainment. This research also explores assessment selection differences in GA attainment. Statistical analysis was used to determine if the models were significantly different through the paired two-sample means t-test. The indicative model could not represent the GA attainment as it differed substantially from the explicit model. Both GA assessment and culminating models can be used to represent the attainment of students' GA. GA assessment model provides monitoring of students' progress in GA attainment, while the culminating models enable measurement at capstones and in advanced years. [ABSTRACT FROM AUTHOR]

A synthetic mean square error (MSE) control chart is presented in this study for monitoring the changes in the mean and standard deviation of a normally distributed process. The synthetic MSE control chart is a combination of the standard MSE control chart and the conforming run length (CRL) control chart. From the numerical comparisons, the synthetic MSE control chart is always more efficient than the standard MSE control chart in detecting shifts in the process mean and standard deviation. The synthetic MSE chart also performs better than the exponentially weighted moving average-semicircle (EWMA-SC) chart, except for some cases where the process mean shifts are small. [ABSTRACT FROM PUBLISHER]

This study investigates the statistical properties of the adaptive Hotelling 's T2 charts with run rules in which the sample size and sampling interval are allowed to vary according on the current and past sampling points. The adaptive charts include variable sample size (VSS), variable sampling interval (VSI), and variable sample size and sampling interval (VSSI) charts. The adaptive Hotelling's T2 charts with run rules are compared with the fixed sampling rate Hotelling's T2 chart with run rules. The numerical results show that the VSS, VSI, and VSSI features improve the performance of the Hotelling's T2 chart with run rules. [ABSTRACT FROM AUTHOR]

A multivariate synthetic exponentially weighted moving average (MSEWMA) control chart is presented in this study. The MSEWMA control chart consists of a multivariate exponentially weighted moving average (MEWMA) control chart and a conforming run length control chart. The average run length of the MSEWMA control chart is obtained using a Markov chain approach. From the numerical comparisons, it is shown that the MSEWMA control chart is more efficient than the multivariate synthetic T2 control chart and the MEWMA control chart for detecting shifts in the process mean vector. [ABSTRACT FROM AUTHOR]