Search

Fault monitoring is an essential requirement for safety and reliability of industrial systems. The paper presents a novel event-based online monitoring technique for automated manufacturing systems, ensuring timely and accurate detection of system failures. The monitor model is based on first-order hybrid Petri nets, ie, Petri nets that make use of first-order fluid approximation. The proposed fault analysis technique relies on a modular framework, so that elementary monitors can be connected with other monitors to check more complex systems while avoiding the state—space explosion problem. In addition, the presented monitor detects system faults as soon as possible, before the maximum execution time assigned to each task. Several examples and an application to an automated manufacturing system proposed in the related literature enlighten the simplicity and modularity of the technique. [ABSTRACT FROM PUBLISHER]

Worldwide competition originated the development of integrated e-supply chains (IESC) that are distributed manufacturing systems integrating international logistics and information technologies with production. This work builds upon an IESC network design methodology previously proposed to select partners in the different IESC stages and the links connecting them. In order to rank the Pareto optimal solutions obtained by such a method, the paper proposes a second level IESC optimization performed using fuzzy logic. Indeed, fuzzy multi-criteria optimization is particularly suitable for choosing, on the basis of the subjective and qualitative knowledge provided by the decision makers, the IESC configuration from the set of Pareto optimal alternatives. Two fuzzification techniques and two different multi-criteria methods are considered. Moreover, a discussion on the different advantages and limitations of the proposed techniques is provided. Finally, the effectiveness of the methodology is illustrated by way of a case study. [ABSTRACT FROM AUTHOR]