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Computational Intelligence In Manufacturing Handbook P2

Introduction Modeling and Design of Manufacturing Systems Modeling, Planning, and Scheduling of Manufacturing Processes Monitoring and Control of Manufacturing Processes Quality Control, Quality Assurance, and Fault Diagnosis Concluding Remarks Abstract In recent years, artificial neural networks have been applied to solve a variety of problems in numerous areas of manufacturing at both system and process levels. The manufacturing applications of neural networks comprise the design of manufacturing systems (including part-family and machine-cell formation for. | Wang Jun et al Applications in Intelligent Manufacturing An Updated Survey Computational Intelligence in Manufacturing Handbook Edited by Jun Wang et al Boca Raton CRC Press LLC 2001 2 Neural Network Applications in Intelligent Manufacturing An Updated Survey Jun Wang The Chinese University of Hong Kong Wai Sum Tang The Chinese University of Hong Kong Catherine Roze IBM Global Services 2.1 Introduction 2.2 Modeling and Design of Manufacturing Systems 2.3 Modeling Planning and Scheduling of Manufacturing Processes 2.4 Monitoring and Control of Manufacturing Processes 2.5 Quality Control Quality Assurance and Fault Diagnosis 2.6 Concluding Remarks Abstract In recent years artificial neural networks have been applied to solve a variety of problems in numerous areas of manufacturing at both system and process levels. The manufacturing applications of neural networks comprise the design of manufacturing systems including part-family and machine-cell formation for cellular manufacturing systems modeling planning and scheduling of manufacturing processes monitoring and control of manufacturing processes quality control quality assurance and fault diagnosis. This paper presents a survey of existing neural network applications to intelligent manufacturing. Covering the whole spectrum of neural network applications to manufacturing this chapter provides a comprehensive review of the state of the art in recent literature. 2.1 Introduction Neural networks are composed of many massively connected simple neurons. Resembling more or less their biological counterparts in structure artificial neural networks are representational and computational models processing information in a parallel distributed fashion. Feedforward neural networks and recurrent neural networks are two major classes of artificial neural networks. Feedforward neural networks 2001 CRC Press LLC such as the popular multilayer perceptron are usually used as representational models trained using a learning rule .