The issue of how to improve product quality and product yield in a brief period of time
becomes more critical in many industries. Even though industrial processes are totally …

Multivariate monitoring and control schemes based on latent variable methods have been
receiving increasing attention by industrial practitioners in the last 15 years. Several …

Early and accurate fault detection and diagnosis for modern manufacturing processes can
minimise downtime, increase the safety of plant operations, and reduce costs. Such process …

Process monitoring and fault diagnosis are crucial for efficient and optimal operation of a
chemical plant. This paper proposes a reconstruction-based fault identification approach …

This study has developed three Logistic Regression Models to determine and analyze the
factors that could affect knowledge, attitude and behavior of the urban poor concerning solid …

This article describes principal component analysis (PCA) of the power spectra of data from
chemical processes. Spectral PCA can be applied to the measurements from a whole unit or …

This paper proposes a hierarchical artificial neural network (HANN) for isolating the faults of
the Tennessee–Eastman process (TEP). The TEP process is the simulation of a chemical …

A novel inferential strategy for controlling end-product quality properties by adjusting the
complete trajectories of the manipulated variables is presented. Control through complete …

Process Control Performance Assessment is a practical guide to the application of control
benchmarking to real, complex, industrial processes. It presents commercial solutions as …

Early detection of process disturbances and prediction of malfunctions in process equipment
improve the safety of the process, minimize the time and resources needed for maintenance …