Plenary Lecture

Artificial Social Systems for Workflow Chart

Associate Professor Calin I. Ciufudean
Department of Automatics and Computers
Faculty of Electrical Engineering and Computer Science
“Stefan Cel Mare” Universtity of Suceava
9, University str., RO720225, Suceava
ROMANIA
E-mail: calin@eed.usv.ro

Abstract: We focus on the control of the performance characteristics of workflows modelled with stochastic Petri nets (SPN’s). This goal is achieved using a new model for Artificial Social Systems (ASS’s) behaviours, and by introducing equivalent transfer functions for SPN’s.
ASS’s exist in practically every multi-agent system, and play a major role in the performance and effectiveness chart of the agents. This is the reason why we introduce a suggestive model for ASS’s. To model complex systems, such as flexible manufacturing ones, a class of Petri nets is adopted, and briefly introduced.
This class allows representing the flow of physical resources and control information data of the ASS’s components. In the analysis of SPN we use simulations in respect to timing parameters in a generalized semi-Markov process (GSMP). By using existing results on perturbation analysis (e.g., delays in supply with raw materials, equipment failure, etc.), and by extending them to new physical interpretations we address unbiased sensitivity estimators correlated with practical solutions in order to attenuate the perturbations.
The novelty of the approach is that the construction of large Markov chains is not required. Using a structural decomposition, the construction system is divided into cells. We can simplify the structure of the SPN using the presented approach, which is useful when we deal with complex Petri nets, and we need to simplify these structures (e.g. graphs) in order to analyze them properly. For each cell a Markov model was derived and the probability was determined of at least Ni working machines in cell i, for i = 1,2,..,n and j , where j=1, ..., m, working material handling system (MHS) at time t, where Ni and j satisfy the system production capacity requirements. An example illustrates this approach. The results reported here form the basis of several enhancements, such as conducting performance studies of complex systems with multiple part types.

Brief Biography of the Speaker:

• Honor Member of the Romanian Society of Electrical & Control Engineering - Member of the Romanian Technical Experts Corp.

• Technical Expert of the Romanian Ministry of Justice.

• President of the Romanian Society of Electrical & Control Engineering, Suceava Branch.

• Academic Positions: Assoc. Professor, Dept. of Automatics and Computers, Faculty of Electrical Engineering and Computer Science, “Stefan cel Mare” University of Suceava, Romania.

• Fields of Scientific Activities: Discrete Event Systems, Complex Measurement Systems, Reliability and Diagnosis of Control Systems, Environmental Management.

• He published 6 books and over 120 scientific papers in conference proceedings and journals.