In order to improve the availability and reliability of manufacturing systems, the diagnosis method is primordial. The literature around the diagnosis of Discrete Event Systems (DES) have proposed different approaches and diagnosability assessment. This paper presents a local modelling of diagnoser and a diagnosability evaluation by Model-Checking. This approach avoids the combinatory explosion...

This paper reveals the experiences of the application of a software tool that combines discrete event simulation (DES), material flow analysis (MFA) and life cycle assessment (LCA) in a single simulation model. This view focuses not only on economic optimization but also on material flow analysis opening the door to sustainable production in the future. Thus, the software unifies the economic a...

Discrete event modeling and simulation reinforcement learning are two frameworks suited for cyberphysical system design, which, when combined, can give powerful tools optimization or decision making process example. This paper describes how discrete could be integrated into concepts in order to assist the realization of systems, more specially considering temporal, hierarchical, multi-agent asp...

This paper deals with the on-line control of partially observed discrete event systems (DES), The goal is to restrict the behavior of the system within a prefix-closed legal language while accounting for the presence of uncontrollable and unobservable events. In the spirit of recent work on the on-line control of partially observed DES (Heymann and Lin 1994) and on variable lookahead control of...

Failure diagnosis in large and complex systems is a critical task. A discrete event system (DES) approach to the problem of failure diagnosis is presented in this paper. A classic solution to solve DES’s diagnosis is a stochastic Petri net. The foraging behavior of ant colonies can give rise to the shortest path, which will reduce the state explosion of stochastic Petri net. Therefore, a new mo...

The determination of AGV vehicle requirements in a manufacturing system has great impact on the performance. This paper first defines requirement as general optimization problem, and secondly develops new method capable effective solving problem. features with combination discrete event simulation (DES), sensitivity analysis, fractional factorial design (FFD) response surface methodology (RSM)....

We study distributed coverage of environments with unknown extension using a team of networked miniature robots analytically and experimentally. Algorithms are analyzed by incrementally raising the abstraction level starting from physical robots, to realistic and discrete-event system (DES) simulation. The realistic simulation is calibrated using sensor and actuator noise characteristics of the...

Genetic programming (GP) and artificial neural networks (ANNs) can be used in the development of surrogate models of complex systems. The purpose of this paper is to provide a comparative analysis of GP and ANNs for metamodeling of discrete-event simulation (DES) models. Three stochastic industrial systems are empirically studied: an automated material handling system (AMHS) in semiconductor ma...

This paper addresses a decentralized supervisory control problem for an uncertain discrete event system (DES) modeled by a set of possible nondeterministic automata with unidentified internal events. For a given language specification, we present the existence condition of a robust and nonblocking decentralized supervisor that achieves this specification for any nondeterministic model in the se...