An artificial intelligent (AI) inspection path management for multiple tasks measurement on co-ordinate measuring machine (CMM): an application of neural network technology

Author

Lu, C.G. ; Morton, D. ; Myler, P. ; Wu, M.H.

Author_Institution

Bolton Inst. of Higher Educ., UK

fYear

1995

fDate

28-30 Jun 1995

Firstpage

353

Lastpage

357

Abstract

The use of a co-ordinate measuring machine (CMM) is widely spread throughout the manufacturing industry. In spite of this, inspection planning for a CMM, especially by using artificial intelligent (AI) techniques, is not well developed. This paper presents an approach of using an artificial neural network technique to carry out the inspection path management for a CMM, especially for multi-component inspection. This path planning system applies genetic algorithm theory to establish an optimiser; and an artificial neural network is developed to carry out the inspection task pattern recognition and the self-learning function

Keywords

automatic optical inspection; computerised instrumentation; industrial control; neurocontrollers; path planning; pattern recognition; position control; position measurement; artificial intelligence; co-ordinate measuring machine; genetic algorithm theory; inspection path management; inspection planning; inspection task pattern recognition; manufacturing industry; multi-component inspection; multiple tasks measurement; neural network technology; path planning system; self-learning function; Artificial intelligence; Coordinate measuring machines; Education; Inspection; Material storage; Neural networks; Optimization methods; Path planning; Probes; Time measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering Management Conference, 1995. Global Engineering Management: Emerging Trends in the Asia Pacific., Proceedings of 1995 IEEE Annual International

Print_ISBN

0-7803-2799-3

Type

conf

DOI

10.1109/IEMC.1995.524608

Filename

524608