Kamran Paynabar

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Quality control charts have proven to be very effective in detecting out-of-control states. When a signal is detected a search begins to identify and eliminate the source(s) of the signal. A critical issue that keeps the mind of the process engineer busy at this point is determining the time when the process first changed. Knowing when the process first(More)
A novel algorithm is developed for feature selection and parameter tuning in quality monitoring of manufacturing processes using cross-validation. Due to the recent development in sensing technology, many on-line signals are collected for manufacturing process monitoring and feature extraction is then performed to extract critical features related to(More)
In this expository paper we give an overview of some statistical methods for the monitoring of social networks. We discuss the advantages and limitations of various methods as well as some relevant issues. One of our primary contributions is to give the relationships between network monitoring methods and monitoring methods in engineering statistics and(More)
In modern manufacturing systems, online sensing is being increasingly used for process monitoring and fault diagnosis. In many practical situations, the output of the sensing system is represented by time-ordered data known as profiles or waveform signals. Most of the work reported in the literature has dealt with cases in which the production process is(More)
—Image and video sensors are increasingly being deployed in complex systems due to the rich process information that these sensors can capture. As a result, image data play an important role in process monitoring and control in different application domains such as manufacturing processes, food industries, medical decision-making, and structural health(More)
Placing sensors in every station of a process or every element of a system to monitor its state or performance is usually too expensive or physically impossible. Therefore, a systematic method is needed to select important sensing variables. The method should not only be capable of identifying important sensors/signals among multi-stream signals from a(More)
In recent years risk-adjusted control charts have been increasingly studied for monitoring surgical outcomes by accounting for patients' health conditions prior to surgery. However, most existing research focuses on phase II monitoring, and very little work has been done on phase I control of surgical outcomes. In this paper, a general phase I risk-adjusted(More)