The statistical monitoring of batch manufacturing processes is considered. It is known that conventional monitoring approaches, e.g. principal component analysis (PCA), are not applicable when the normal operating conditions of the process cannot be sufficiently represented by a Gaussian distribution. To address this issue, Gaussian mixture model (GMM) has been proposed to estimate the probabil...

monitoring of road traffic noise is becoming an important issue in modern cities due to the spreading of noise pollution and the extension of monitored areas. thus, the stratified spatial sampling is frequently applied to reduce the costs and provide adequate accuracy in order to obtain reliable noise maps. the definition of the strata in the sampling may refer to the legislative classification...

multivariate process capability indices (mpci) show how well a manufacturing process can meet specifica-tion limits when quality characteristics enclose a relative correlation. process capability is an important and commonly used metric for assessing and improving the quality of a production process. when quality charac-teristics of a product are correlated then an attractive comes close to mpc...

Monitoring the reliability of products in both the manufacturing and service processes is of main concern in today’s competitive market. To this end, statistical process control has been widely used to control the reliability-related quality variables. The so-far surveillance schemes have addressed processes with independent quality characteristics. In multistage processes, however, the cascade...

The process of implementing a damage detection strategy for aerospace, civil, and mechanical engineering systems is called structural health monitoring. Vibration-based damage detection is receiving considerable attention from the research community for such monitoring. Recent research has recognized that the process of vibration-based structural health monitoring is fundamentally one of statis...

Monitoring and diagnosis of mean shifts in manufacturing processes become more challenging when involving two or more correlated variables. Unfortunately, most of the existing multivariate statistical process control schemes are only effective in rapid detection but suffers high false alarm, that is, imbalanced monitoring performance. The problem becomes more complicated when dealing with small...

In some statistical process control applications, quality of a process or product can be characterized by a relationship between a response and one or more independent variables, which is typically referred to a profile. In this paper, polynomial profiles are considered to monitor processes in which there is a first order autoregressive relation between the error terms in each profile. A remedi...

Multivariate statistical representations have been widely used in the process manufacturing industries for process performance monitoring, in particular for the detection of changes in current operation and the onset of process disturbances or faults. Applications of the technology have focused to a lesser extent on manufacturing processes where drift occurs over time as part of normal process ...

Continuous quality assurance (QA) in health care has necessitated the adoption of statistical methods developed as industrial process monitoring techniques. One such statistical technique is the cumulative summation (Cusum) methodology, which can monitor continuously a production process and detect subtle deviations from a preset defined level of achievement. The method is practical, simple to ...