15th Triennial World Congress of the International Federation of Automatic Control
  Barcelona, 21–26 July 2002 
AI AND MACHINE LEARNING TECHNIQUES FOR MANAGING COMPLEXITY, CHANGES AND UNCERTAINTIES IN MANUFACTURING
László Monostori
Computer and Automation Research Institute, Hungarian Academy of Sciences
Kende u. 13-17, Budapest, POB 63, H-1518, Hungary
Phone: (36 1) 2096-990, Fax: (361) 4667-503, e-mail: laszlo.monostori@sztaki.hu

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.
Keywords: Artificial intelligence, machine learning, intelligent manufacturing systems
Session slot T-Fr-A20: Intelligent Manufacturing Control/Area code 1a : Advanced Manufacturing Technology