Manufacturing systems: A knowledge- and optimization-based approach

Optimization approaches have traditionally been viewed as tools for solving manufacturing problems. The optimization approach is not suitable for many problems arising in modern manufacturing systems due to their complexity and involvement of qualitative factors. Expert systems appear to remedy the latter weakness of optimization approaches. The biggest disadvantage of expert systems in manufacturing environment is the slow response time. In this paper an integrand approach involving knowledge-based and optimization approaches is explored. The knowledge-and optimization-based approach is applied to solve two manufacturing problems: group technology (static problem) and scheduling (dynamic problem). The approach presented is illustrated with numerical example and computational results.The original version of this paper was presented at the 2nd International Symposium on Robotics and Manufacturing (ISRAM), Albuquerque, New Mexico 16–18 November 1988. The published proceedings of this meeting may be ordered from: CAD Laboratory for Systems/Robotics, EECE Dept, UNM, Albuquerque, NM 87131, U.S.A.