one of the most important problems of the designs proposed by traditional economic-statistical approaches of control charts is inefficiency in the face of uncertainty. uncertainty in the parameters of economic-statistical models may lead to failure in rapidly detecting changes in processes and impose greater costs to the organization. monitoring the machining process in an automotive industry e...

in statistical quality control a very widely used measure is average run length (arl) which may be worked out by different methods like integral equation, approximations, and monte carlo simulations. the arl measure and the other related measures are of major significance in every type of production process. an omission in its computation (and hence its related measures such as extra quadratic ...

in many statistical process control applications, the quality of a process is characterized by a profile. a profile is a function in terms of one or more explanatory variables. in profile monitoring, one is interested to monitor the performance of a process or product using this functional relationship. control charts for monitoring nonparametric profiles are useful when the relationship is too...

usually, in monitoring schemes the nominal value of the process parameter is assumed known. however, this assumption is violated owing to costly sampling and lack of data particularly in healthcare systems. on the other hand, applying a fixed control limit for the risk-adjusted bernoulli chart causes to a variable in-control average run length performance for patient populations with dissimilar...

Some of the most widely-investigated control charting techniques for autocorrelated data are based on time series residuals. If the mean shift in the autocorrelated process is a sudden step shift, the resulting mean shift in the residuals is time varying and has been referred to as the fault signature. Traditional residual based charts, such as a Shewhart, CUSUM, or EWMA on the residuals, do no...

Statistical process control ($SPC$), an internationally recognized technique for improving product quality and productivity, has been widely employed in various industries. $SPC$ relies on the use of control charts to monitor a manufacturing process for identifying causes of process variation and signaling the necessity of corrective action for the process. Fuzzy data exist ubiquitously in the ...

The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences su...