Approaches to coupling connectionist and expert systems in intelligent manufacturing

Dieter Barschdorff, L. Monostori, Gerd W. Wöstenkühler, Csaba Egresits, B. Kádár

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Artificial neural networks are successfully applied in different fields of manufacturing, mostly where multisensor integration, robustness, real-timeness, and learning abilities are needed. Since the higher levels of the control and the monitoring hierarchy require symbolic knowledge representation and processing techniques, the integrated use of the symbolic and subsymbolic approaches is straightforward. The paper describes two hybrid artificial intelligence systems for control and monitoring of manufacturing processes on different hardware and software bases. The first experiences gained by their usage are outlined. Finally, further possible applications of these hybrid solutions in an intelligent manufacturing environment are enumerated.

Original languageEnglish
Pages (from-to)5-15
Number of pages11
JournalComputers in Industry
Volume33
Issue number1
Publication statusPublished - Aug 1997

Fingerprint

Expert systems
Monitoring
Knowledge representation
Artificial intelligence
Neural networks
Hardware
Processing
Manufacturing
Expert system
Integrated
Software
Artificial neural network
Manufacturing process
Robustness

Keywords

  • Artificial intelligence
  • Artificial neural networks
  • Control and monitoring of manufacturing processes
  • Expert systems
  • Hybrid AI systems

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

Cite this

Approaches to coupling connectionist and expert systems in intelligent manufacturing. / Barschdorff, Dieter; Monostori, L.; Wöstenkühler, Gerd W.; Egresits, Csaba; Kádár, B.

In: Computers in Industry, Vol. 33, No. 1, 08.1997, p. 5-15.

Research output: Contribution to journalArticle

Barschdorff, Dieter ; Monostori, L. ; Wöstenkühler, Gerd W. ; Egresits, Csaba ; Kádár, B. / Approaches to coupling connectionist and expert systems in intelligent manufacturing. In: Computers in Industry. 1997 ; Vol. 33, No. 1. pp. 5-15.
@article{687c3cf4e2e64b0dac27859c578b95d5,
title = "Approaches to coupling connectionist and expert systems in intelligent manufacturing",
abstract = "Artificial neural networks are successfully applied in different fields of manufacturing, mostly where multisensor integration, robustness, real-timeness, and learning abilities are needed. Since the higher levels of the control and the monitoring hierarchy require symbolic knowledge representation and processing techniques, the integrated use of the symbolic and subsymbolic approaches is straightforward. The paper describes two hybrid artificial intelligence systems for control and monitoring of manufacturing processes on different hardware and software bases. The first experiences gained by their usage are outlined. Finally, further possible applications of these hybrid solutions in an intelligent manufacturing environment are enumerated.",
keywords = "Artificial intelligence, Artificial neural networks, Control and monitoring of manufacturing processes, Expert systems, Hybrid AI systems",
author = "Dieter Barschdorff and L. Monostori and W{\"o}stenk{\"u}hler, {Gerd W.} and Csaba Egresits and B. K{\'a}d{\'a}r",
year = "1997",
month = "8",
language = "English",
volume = "33",
pages = "5--15",
journal = "Computers in Industry",
issn = "0166-3615",
publisher = "Elsevier",
number = "1",

}

TY - JOUR

T1 - Approaches to coupling connectionist and expert systems in intelligent manufacturing

AU - Barschdorff, Dieter

AU - Monostori, L.

AU - Wöstenkühler, Gerd W.

AU - Egresits, Csaba

AU - Kádár, B.

PY - 1997/8

Y1 - 1997/8

N2 - Artificial neural networks are successfully applied in different fields of manufacturing, mostly where multisensor integration, robustness, real-timeness, and learning abilities are needed. Since the higher levels of the control and the monitoring hierarchy require symbolic knowledge representation and processing techniques, the integrated use of the symbolic and subsymbolic approaches is straightforward. The paper describes two hybrid artificial intelligence systems for control and monitoring of manufacturing processes on different hardware and software bases. The first experiences gained by their usage are outlined. Finally, further possible applications of these hybrid solutions in an intelligent manufacturing environment are enumerated.

AB - Artificial neural networks are successfully applied in different fields of manufacturing, mostly where multisensor integration, robustness, real-timeness, and learning abilities are needed. Since the higher levels of the control and the monitoring hierarchy require symbolic knowledge representation and processing techniques, the integrated use of the symbolic and subsymbolic approaches is straightforward. The paper describes two hybrid artificial intelligence systems for control and monitoring of manufacturing processes on different hardware and software bases. The first experiences gained by their usage are outlined. Finally, further possible applications of these hybrid solutions in an intelligent manufacturing environment are enumerated.

KW - Artificial intelligence

KW - Artificial neural networks

KW - Control and monitoring of manufacturing processes

KW - Expert systems

KW - Hybrid AI systems

UR - http://www.scopus.com/inward/record.url?scp=0031197959&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031197959&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0031197959

VL - 33

SP - 5

EP - 15

JO - Computers in Industry

JF - Computers in Industry

SN - 0166-3615

IS - 1

ER -