Case Example 7: Monitoring and predicting surface roughness and bore tolerance in end-milling

  • A. Chukwujekwu Okafor
Part of the Manufacturing Systems Engineering Series book series (MSES, volume 5)


The work described in this chapter is a result of a series of research conducted in the Laboratory for Industrial Automation and Flexible Manufacturing at the Department of Mechanical and Aerospace Engineering and Engineering Mechanics, University of Missouri-Rolla. The main objectives of the research effort, which is still in progress, are to develop and implement an on-line (real-time) intelligent machining monitoring and diagnostic system for predicting and assuring the quality characteristics of machined parts, in the form of surface roughness and bore tolerance, based on the integration of multi-sensors using neural networks and expert systems.


Acoustic Emission Tool Wear Processing Element Hide Node Training Cycle 
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© Springer Science+Business Media Dordrecht 1999

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  • A. Chukwujekwu Okafor

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