Login

 


Plenary Lecture

Discrete Mathematic Diagnosis Models of Complex Manufacturing Systems

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

Abstract: Fault detection is a crucial and challenging task in the automatic control of complex systems, e.g. in flexible manufacturing systems (FMSs) as a representative class of discrete event systems (DESs).
A discrete event system approach to the problem of failure diagnosis is presented.
We propose a systematic procedure for detection of failure events using diagnoses implemented with stochastic coloured Petri nets (SCPN). An analytical approach for the availability evaluation of cellular manufacturing systems (as basic components of FMS’s) is presented, where a FMS is considered operational as long as its production capacity requirements are satisfied.
The approach is used to evaluate transient and steady-state performance of alternative designs based on an industrial example.
The property of diagnosability is introduced in the context of the failure diagnosis problem, e.g. in the context of the availability of the DES.
We bring a DES approach to the problem of failure diagnosis of FMSs because most of them are modelled by DESs, and because continuous variable dynamic systems can often be viewed as DESs at a higher level of abstraction, respectively when their trajectories are determined by meaningful accumulations of dynamics e.g., are determined by events.
The states of the discrete event model reflect both the normal and the failed status of the system components, while the failure events form part of the event set.
We present a systematic procedure for detection and isolation of failure events using diagnosers. Therefore we model FMSs with stochastic coloured Petri nets (SCPNs).
The diagnoser is a SCPN which models the FSM. This model performs detection and isolation of failures (failure information and occurrences of failures can be detected by inspecting the states of the SCPN model), and it also permits the verification of the diagnosability properties of the system (e.g., permits the estimation of the reliability of the system). In our assumption the availability of a production cell i (i=1, 2…., n, where n is the total number of part cells in the FMS) is calculated with a Markov chain that includes the failure rates, repair rates, and coverability of the respective devices in the production cell i.
The colour domains of transition in the SCPN model which loads cell i, in the Markov chain, include colours that result in a value between 0 and 1, and the biggest value designates the cell which will transmit data further on according to the system throughput.

Brief Biography of the Speaker:
•    Academic Positions: Assoc. Professor Ph.D. Eng., 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 11 books, 12 patents and over 160 scientific papers in conference proceedings and journals.
•    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.
•    He is a member of the editorial boards of several international scientific journals and conferences of control systems and electric engineering science. He was designated chairmen at 21 international conferences.