A new economic approach to process capability assessment is presented, which differs from the commonly used engineering metrics. The proposed metric consists of two economic capability measures – the expected profit and the variation in profit of the process. This dual economic metric offers a number of significant advantages over other engineering or economic metrics used in process capability...

The process capability analysis is a crucial activity to evaluate if the process outcome meets the design specifications. Classically, such analysis is performed by verifying the in-control condition of the process and evaluating suitable capability indices, by assuming the process in-control steady-state condition. However, the in-control period of the process characterizes only a part of the ...

Process safety and environment pollution demands are continuously increasing in the process industry. Apart from that, requirements regarding final product quality and production efficiency are higher and higher [1]. This can be achieved by applying advanced process monitoring and control techniques. Process control is heavily dependent on the quality of the data, so it is crucial to measure as...

In contrast to the conventional minimum mean squared error (MMSE) training criterion for nonlinear spectral mapping based on deep neural networks (DNNs), we propose a probabilistic learning framework to estimate the DNN parameters for singlechannel speech separation. A statistical analysis of the prediction error vector at the DNN output reveals that it follows a unimodal density for each log p...

When monitoring a process which has multivariate normal variables, the Shewhart-type control chart (Hotelling (1947)) traditionally used for monitoring the process mean vector is effective for detecting large shifts, but for detecting small shifts it is more effective to use the multivariate exponentially weighted moving average (MEWMA) control chart proposed by Lowry et al. (1992). It has been...

Multivariate Laplace distribution is an important stochastic model that accounts for asymmetry and heavier than Gaussian tails, while still ensuring the existence of the second moments. A Lévy process based on this multivariate infinitely divisible distribution is known as Laplace motion, and its marginal distributions are multivariate generalized Laplace laws. We review their basic properties ...