Monitoring of the milling process through neural network and fuzzy techniques

S. Markos, L. Monostori, J. Nacsa, G. Szollosi

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Citations (Scopus)


Real-time nature, uncertainty handling and learning ability are essential features of knowledge representation and processing techniques to be applied at lower levels of intelligent manufacturing systems. The paper demonstrates, that artificial neural networks and fuzzy systems are possibly approaches to comply with these requirements. Their applicability for modelling and monitoring of manufacturing processes is illustrated and compared. At the end of the paper the combined use of the neural and fuzzy techniques is suggested to produce adaptive fuzzy systems, and the integration of such hybrid system in an intelligent manufacturing environment is investigated.

Original languageEnglish
Title of host publicationIFIP Transactions B
Subtitle of host publicationComputer Applications in Technology
PublisherPubl by Elsevier Science Publishers B.V.
Number of pages12
ISBN (Print)0444814841
Publication statusPublished - Dec 1 1993


ASJC Scopus subject areas

  • Engineering(all)

Cite this

Markos, S., Monostori, L., Nacsa, J., & Szollosi, G. (1993). Monitoring of the milling process through neural network and fuzzy techniques. In IFIP Transactions B: Computer Applications in Technology (B-11 ed., pp. 239-250). Publ by Elsevier Science Publishers B.V..