Evaluation model of adaptability to dynamic production environments for manufacturing system

Author

Yufang, Wang

Author_Institution

Coll. of Inf. & Control Eng., Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China

Volume

6

fYear

2010

fDate

24-26 Aug. 2010

Firstpage

232

Lastpage

235

Abstract

In this paper, a fuzzy neural network model is presented to evaluate the adaptability of the existing manufacturing mode to the dynamic production environments. The dynamic production environments are generalized firstly and regarded as linguistic variable inputs of the fuzzy neural network model. A modified momentum factor B-P algorithm consists of information feed-forward process and the error back-propagation process is used. The proposed fuzzy neural network model is employed to evaluate the adaptability of a switching production manufacturing mode to the hypothetical production environment schemes consist of five experiments. Experiment results show the proposed model is effective.

Keywords

backpropagation; feedforward neural nets; fuzzy neural nets; manufacturing systems; production engineering computing; adaptability evaluation; dynamic production environment; error back-propagation process; fuzzy neural network model; hypothetical production environment scheme; information feed-forward process; manufacturing system; momentum factor B-P algorithm; production manufacturing mode; Adaptation model; IP networks; Impedance matching; Adaptability; Fuzzy neural network; Manufacturing system; dynamic environments; evaluation model;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on

Conference_Location

Changchun

Print_ISBN

978-1-4244-7957-3

Type

conf

DOI

10.1109/CMCE.2010.5609861

Filename

5609861