Abstract Proper integration of scheduling and control in Flexible Manufacturing Systems will make available the required level of decision-making capacity to provide a flexibly-automated, efficient, and quality manufacturing process. To achieve this level of integration, the developments in computer technology and sophisticated techniques of artificial intelligence (AI) should be applied to such FMS functions as scheduling. In this paper, we present an Intelligent Scheduling System for FMS under development that makes use of the integration of two AI technologies. These two AI technologies — Neural Networks and Expert Systems — provide the intelligence that the scheduling function requires in order to generate goodschedules within the restrictions imposed by real-time problems. Because the system has the ability to plan ahead and learn, it has a higher probability of success than conventional approaches. The adaptive behavior that will be achieved contribute to the integration of scheduling and control in FMS.
[1]
R. Hecht-Nielsen,et al.
Neurocomputing: picking the human brain
,
1988,
IEEE Spectrum.
[2]
James L. McClelland,et al.
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
,
1986
.
[3]
James Raymond Gross.
Intelligent feedback control for flexible manufacturing systems
,
1987
.
[4]
James J. Solberg,et al.
Dynamic control in automated manufacturing: a knowledge integrated approach†
,
1988
.
[5]
J. Diebold.
Automation
,
1955,
Industry, Innovation and Infrastructure.
[6]
Peter O'Grady,et al.
An intelligent cell control system for automated manufacturing
,
1988
.
[7]
Wolfgang Meyer,et al.
Knowledge-based factory supervision — The CIM shell
,
1988
.