Fuzzy technology in advanced manufacturing systems: A fuzzy-neural approach to job remaining cycle time estimation

Tin-Chih Chen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

A self-organization map (SOM)-fuzzy back propagation network (FBPN) approach is proposed in this study for estimating the remaining cycle time of each job in a semiconductor manufacturing factory, which was seldom investigated in the past studies but is a critical task to the semiconductor manufacturing factory. The proposed methodology applies the SOM-FBPN approach to estimate both the cycle time and the step cycle time of a job, and then derives the remaining cycle time with the proportional adjustment approach. For evaluating the effectiveness of the proposed methodology, production simulation is also applied in this study to generate some test data.

Original languageEnglish
Title of host publicationProduction Engineering and Management under Fuzziness
EditorsCengiz Kahraman, Mesut Yavuz
Pages125-142
Number of pages18
DOIs
StatePublished - 31 May 2010

Publication series

NameStudies in Fuzziness and Soft Computing
Volume252
ISSN (Print)1434-9922

Fingerprint Dive into the research topics of 'Fuzzy technology in advanced manufacturing systems: A fuzzy-neural approach to job remaining cycle time estimation'. Together they form a unique fingerprint.

Cite this