scholarly journals Discrete Event System Control in Max-Plus Algebra: Application to Manufacturing Systems

2020 ◽  
Vol 53 (4) ◽  
pp. 143-150
Author(s):  
Gabriel Freitas Oliveira ◽  
Renato Markele Ferreira Candido ◽  
Vinicius Mariano Gonçalves ◽  
Carlos Andrey Maia ◽  
Bertrand Cottenceau ◽  
...  
Keyword(s):  
Manufacturing Systems ◽  
Discrete Event ◽  
Discrete Event System ◽  
System Control ◽  
Event System

Configuration space–based discrete event system specification formalism for a smart factory with real-time flexibility

2018 ◽  
Vol 26 (3) ◽  
pp. 265-275 ◽  
Author(s):  
Dae S Chang ◽  
Sang C Park
Keyword(s):  
Real Time ◽  
Configuration Space ◽  
Manufacturing Systems ◽  
Discrete Event ◽  
Discrete Event System ◽  
Smart Factory ◽  
System Specification ◽  
Discrete Event System Specification ◽  
Event System ◽  
Effective Description

A manufacturing system consists of various manufacturing devices, and each device has a set of tasks which are triggered by specific commands. Traditionally, simulation has been considered as an essential technology for the evaluation and analysis of manufacturing systems. Although discrete event system specification formalism has been a popular modeling tool for manufacturing systems, it has limitations in describing situations such as sudden cancelation of tasks. Proposed in this article is an extended discrete event system specification formalism for the effective description of a smart factory which requires the intelligence to handle turbulences in real-time production. The extended discrete event system specification formalism incorporates the configuration space concept, which is well-known in classical mechanics. While the conventional discrete event system specification formalism uses only the logical states set to represent the device states, the proposed formalism employs the combination of two sets: a logical states set (sequential states set) and a physical states set (configuration space of the device). As a result, the extended formalism enables the effective description of nondeterministic tasks which may occur frequently in a smart factory.

scholarly journals Research on Modeling and Simulating of Discrete Event System Based on Petri Net

2012 ◽  
Vol 4 ◽  
pp. 80-85 ◽  
Author(s):  
Xing Long Pan ◽  
Guo He ◽  
Chao Jie Zhang ◽  
Ting Feng Ming ◽  
Xiao Chuan Wang
Keyword(s):  
Control System ◽  
Petri Net ◽  
Discrete Event ◽  
Discrete Event System ◽  
System Model ◽  
Artificial System ◽  
Event System ◽  
Logical Control ◽  
Marine Diesel ◽  
Control System Model

A framework of modeling and simulating a typical artificial system is proposed based on discrete event system and Petri net. Firstly, the system model is constructed based on discrete event system theory. Secondly, the model is described and analyzed by using Petri net. Then, the simulation procedures on Matlab platform are presented in detail. The proposed framework is applied to modeling and simulating a logical control system of a marine diesel engine. The simulation results indicate that this logical control system model can be constructed by the given framework and the proposed method is effective in simulating and analyzing this kind of artificial system.

Production degrees of freedom as manufacturing system reconfiguration potential measures

2008 ◽  
Vol 222 (10) ◽  
pp. 1301-1314 ◽  
Author(s):  
A M Farid ◽  
D C McFarlane
Keyword(s):  
Manufacturing Systems ◽  
Degrees Of Freedom ◽  
Manufacturing System ◽  
Automated Manufacturing ◽  
Reconfigurable Manufacturing ◽  
Multi Agent Systems ◽  
Automated Manufacturing Systems ◽  
System Reconfiguration ◽  
Multi Agent ◽  
Changes Over Time

In recent years, many design approaches have been developed for automated manufacturing systems in the fields of reconfigurable manufacturing systems (RMSs), holonic manufacturing systems (HMSs), and multi-agent systems (MASs). One of the principle reasons for these developments has been to enhance the reconfigurability of a manufacturing system, allowing it to adapt readily to changes over time. However, to date, reconfigurability assessment has been limited. Hence, the efficacy of these design approaches remains inconclusive. This paper is the first of two in this issue to address reconfigurability measurement. Specifically, it seeks to address ‘reconfiguration potential’ by analogy. Mechanical degrees of freedom have been used in the field of mechanics as a means of determining the independent directions of motion of a mechanical system. By analogy, manufacturing degrees of freedom can be used to determine independent ways of production. Furthermore, manufacturing degrees of freedom can be classified into their production and product varieties. This paper specifically focuses on the former to measure the product-independent aspects of manufacturing system ‘reconfiguration potential’. This approach will be added to complementary work on the measurement of ‘reconfiguration ease’ so as to form an integrated reconfigurability measurement process described elsewhere [1—5].

scholarly journals Predictors of Transition in Smoking Stages in Iranian Adolescents: A Probabilistic Discrete Event System Model

2017 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Ahmad Khosravi ◽  
Kourosh Holakouie-Naieni ◽  
Mohammad Ali Mansournia ◽  
Mahmood Mahmoodi ◽  
Ali Akbar Pouyan
Keyword(s):  
Discrete Event ◽  
Discrete Event System ◽  
System Model ◽  
Event System
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