• 제어로봇시스템학회논문지
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• 제6권6호
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• pp.478-485
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• 2000

A discrete event systems (DES) is a physical system that is discrete in time and state space, asynchronous (event rather than clock-driven), and in some sense generative(or nondeterministic). This paper presents the design of fifteen modular supervisors to control an experimental CIM testbed. These supervisors are nonblocking, controllable and nonconflicting. After verification of the supervisors by simulation, the supervisors for AGV system have been implemented to demonstrate their efficacy.

• 대한산업공학회지
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• 제23권2호
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• pp.249-260
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• 1997

The manufacturing environment is rife with nonlinear processes. In this context, an intelligent production controller should be able to predict the dynamic behavior of various subsystems as they react to transient environmental conditions, the varying internal condition of the manufacturing plant, and the changing demands of the production schedule. This level of adaptive capability may be achieved through a coherent methodology for a learning coordinator to predict nonlinear and stochastic processes. The system is to serve as a real time, online supervisor for routine activities as well as exceptional conditions such as damage, failure, or other anomalies. The complexity inherent in a learning coordinator can be managed by a modular architecture incorporating case based reasoning. In the interest of concreteness, the concepts are presented through a case study involving a knowledge based robotic system.