AI and machine learning techniques for managing complexity, changes and uncertainties in manufacturing

Research output: Contribution to journalConference article

14 Citations (Scopus)

Abstract

The application of pattern recognition (PR) techniques, expert systems (ESs), artificial neural networks (ANNs), fuzzy systems (FSs) and nowadays hybrid artificial intelligence (AI) techniques in manufacturing can be regarded as consecutive elements of a process started two decades ago. On the one hand, the paper outlines the most important steps of this process and introduces some new results with special emphasis on hybrid AI and multistrategy machine learning (ML) approaches. On the other hand, agent-based (holonic) systems are highlighted as promising tools for managing complexity, changes and disturbances in production systems. Further integration of approaches is predicted.

Original languageEnglish
Pages (from-to)119-130
Number of pages12
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume15
Issue number1
Publication statusPublished - Jan 1 2002
Event15th World Congress of the International Federation of Automatic Control, 2002 - Barcelona, Spain
Duration: Jul 21 2002Jul 26 2002

Keywords

  • Artificial intelligence
  • Intelligent manufacturing systems
  • Machine learning

ASJC Scopus subject areas

  • Control and Systems Engineering

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