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...

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...

This paper presents a new vulnerability assessment model based on timing attacks. In particular, it examines the problem where an adversary has access to a certain sensor reading or a controller output signal in real time, but can only cause denial of service (DoS). Jamming the communications to a device can cause the system to work with stale data that, in turn, could interfere with the contro...

In this paper, we will report on the experience of building a successful industrial application using the LDL++ deductive database as part of the technology transfer process to our sponsor company, Eastman Chemical Company. We will describe the nature of the problems faced by Eastman Chemical Company and show how the LDL++ deductive database technology helps to build an Intelligent Information ...

This paper presents the prototype of an advanced platform for production analysis and optimization, referred to as ProOpter. The platform was developed to support the recently derived concept of holistic production control (HPC), which relies on model-based control. The prototype is comprised of a set of offline and on-line modules. The off-line modules support the definition of key performance...

Principal component analysis (PCA) is largely adopted for chemical process monitoring and numerous PCAbased systems have been developed to solve various fault detection and diagnosis problems. Since PCA-based methods assume that the monitored process is linear, nonlinear PCA models, such as autoencoder models and kernel principal component analysis (KPCA), has been proposed and applied to nonli...

An appropriately designed sensor network is crucial for the success of any fault diagnostic strategy. In previous works (Bhushan and Rengaswamy, 2002a,b) strategies for optimally locating sensors based on criteria of reliability maximization and cost minimization have been devised. These opposing objectives were treated in a lexicographic (a special type of multiobjective optimization) manner. ...