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

Research output: Contribution to journalArticle

98 Citations (Scopus)

Abstract

The application of pattern recognition techniques, expert systems, artificial neural networks, fuzzy systems and nowadays hybrid artificial intelligence (AI) techniques in manufacturing can be regarded as consecutive elements of a process started two decades ago. 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 approaches. 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)277-291
Number of pages15
JournalEngineering Applications of Artificial Intelligence
Volume16
Issue number4
DOIs
Publication statusPublished - Jun 1 2003

Keywords

  • Artificial intelligence
  • Intelligent manufacturing systems
  • Machine learning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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