Eric M. Yezdimer,†,‡ Peter T. Cummings,§,| and Ariel A. Chialvo*,|,⊥ Chemistry Department, UniVersity of Tennessee, KnoxVille, Tennessee 37996-2200, Departments of Chemical Engineering, Chemistry and Computer Science, UniVersity of Tennessee, KnoxVille, Tennessee 37996-2200, Chemical Sciences DiVision, High-Temperature Aqueous Chemistry Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee...

In this article, a novel dynamic Bayesian network based networked process monitoring approach is proposed for fault detection, propagation pathway identification and root cause diagnosis. First, process network structure is designed according to the prior process knowledge including process flow sheets and used to characterize the causal relationships among different measurement variables. Then...

Many classical multivariate statistical process monitoring (MSPM) techniques assume normal distribution of the data and independence of the samples. Very often, these assumptions do not hold for real industrial chemical processes, where multiple plant operating modes lead to multiple nominal operation regions. MSPM techniques that do not take account of this fact show increased false alarm and ...

1569-190X/$ see front matter 2012 Elsevier B.V http://dx.doi.org/10.1016/j.simpat.2012.07.010 ⇑ Corresponding author. Tel.: +386 1 477 36 84. E-mail address: [email protected] (M. Glavan). Holistic production control is a concept that introduces production optimisation by employing model-based, closed-loop control of the principal production Performance Indicators (pPIs). The concept relies on...

200 ml. of isopropenyl acetate (Tennessee Eastman Corporation) are cooled in an ice bath and then, with stirring, 25 ml. of 85 per cent syrupy phosphoric acid (35 gm. of H3P04) are added dropwise, and finally 1.0 ml. of concentrated sulfuric acid is added as catalyst. The reaction mixture is placed in a water bath at 25” and stirred constantly to prevent localized heating. After 35 minutes at t...

In this paper, a new approach for fault detection and isolation that is based on the possibilistic clustering algorithm is proposed. Fault detection and isolation (FDI) is shown here to be a pattern classification problem, which can be solved using clustering and classification techniques. A possibilistic clustering based approach is proposed here to address some of the shortcomings of the fuzz...

Compared to large process faults, the latent and small ones are difficult to be detected. However, the accumulation of these faults may even more harmful to the process. A novel fault detection and diagnosis method is proposed which is based on similarity factor and a variable moving window. The new method is based on the idea that a change of process can be reflected in the distribution of the...