ARTIFICIAL-INTELLIGENCE AND JOB-SHOP SCHE DULING SYSTEMS IN AERONAUTICAL MANUFACTURING

Scheduling problems are a class of problems hard to solve for all know n techniques. Many of research and development efforts have been condu cted in different areas, particularly Artificial Intelligence. This pa per presents the results of research on job shop scheduling in aeronau tical manufacturing through the description of the OPAL software proto type, developed at CERT. The OPAL software is dedicated to building pr ovisional schedules and belongs to the class of knowledge-based system s. Several types of knowledge are embedded in the system: theoretical knowledge about scheduling constraint analysis, experimental knowledge about priority rules used in discrete event simulation and practical knowledge from shop floor. Solving a scheduling problem is based on th e cooperation between these different types of knowledge. OPAL uses re sults from fuzzy set theory, constraint based analysis and multicriter ia aggregation techniques. The presentation is organized in two main p arts. The first part deals with generalities about manufacturing (sect ion I), scheduling (section II) and artificial intelligence (section I II). The detailed description of the OPAL system is given in the secon d part (section IV).