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Operations Research, Systems Engineering and Industrial Engineering Commons

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Series

Mechanical Engineering

1990

Articles 1 - 3 of 3

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Synergy Of Artificial Neural Networks And Knowledge-Based Expert Systems For Intelligent Fms Scheduling, Luis Carlos Rabelo, Sema E. Alptekin, Ali S. Kiran Jun 1990

Synergy Of Artificial Neural Networks And Knowledge-Based Expert Systems For Intelligent Fms Scheduling, Luis Carlos Rabelo, Sema E. Alptekin, Ali S. Kiran

Industrial and Manufacturing Engineering

In this paper we describe a hybrid architecture that integrates artificial neural networks and knowledge-based expert systems to generate solutions for the real time scheduling of flexible manufacturing systems. The artificial neural networks perform pattern recognition and, due to their inherent characteristics, support the implementation of automated knowledge acquisition and refinement schemes through a feedback mechanism. The artificial neural network structures enable the system to recognize patterns in the tasks to be solved in order to select the best scheduling rule according to different demands. The knowledge-based expert systems are the higher order elements which drive the inference strategy and ...


A Suggested Model Program For Cim Education, Sema E. Alptekin May 1990

A Suggested Model Program For Cim Education, Sema E. Alptekin

Industrial and Manufacturing Engineering

No abstract provided.


Adaptive Scheduling And Control Using Artificial Neural Networks And Expert Systems For A Hierarchical/Distributed Fms Architecture, Luis Carlos Rabelo, Sema E. Alptekin May 1990

Adaptive Scheduling And Control Using Artificial Neural Networks And Expert Systems For A Hierarchical/Distributed Fms Architecture, Luis Carlos Rabelo, Sema E. Alptekin

Industrial and Manufacturing Engineering

An adaptive expert scheduler was developed that learns by itself and adapts to the dynamic FMS environment. This hybrid system uses a symbiotic architecture composed of expert systems (ESs) and artificial neural networks (ANNs) and provides a learning scheme guided by past experience. The artificial neural networks recognize patterns in the tasks to be solved in order to select the best scheduling rule according to different criteria. The expert systems, on the other hand, drive the inference strategy and interpret the constraints and restrictions imposed by the upper levels of the control hierarchy of the flexible manufacturing system. The level ...