A comparison of two intelligent scheduling systems for flexible manufacturing systems

Abstract

Despite the existence of hardware suitable for the development of advanced automated manufacturing systems, the implementation of such systems has been hampered by the lack of appropriate software necessary for the scheduling and control of these systems. Artificial Intelligence (AI) has been suggested as a methodology suited to the development of this software. As a result, in this paper two intelligent scheduling and control systems are developed with the cooperation of an “expert” at an existing FMS in Aiken, South Carolina, USA. The literature related to scheduling FMS using AI methodologies is unclear as to whether scheduling should be done in a real-time manner similar to simple job-shop scheduling or in a predictive manner that shows detailed start times and finish times for some scheduling horizon. As such, one intelligent scheduler developed in this research utilizes a real-time scheduling methodology, while the second utilizes a predictive methodology. Both systems were developed in conjuction with a scheduling expert at the FMS. Results from a simulation model of the FMS using each of the two scheduling methodologies are compared in an effort to address the issue of which methodology is better suited for the scheduling and control of automated manufacturing systems such as FMS.