Knowledge discovery and constraint-based processing in automated manufacturing

This paper studies the application of integrated database and artificial intelligence technologies in automated manufacturing. Two interesting techniques: (1) knowledge discovery, i.e., discovery of interesting rules and regularities from data or processing history, and (2) constraint-based processing, i.e., the application of the knowledge and rules as constraints in the guidance or control of a manufacturing process, are examined in detail. The study shows that the proposed technique may extract interesting knowledge from data, guide manufacturing processes and enhance system performance. Therefore, it may have important implications to computer-integrated manufacturing systems