Title :
Evaluation model of adaptability to dynamic production environments for manufacturing system
Author_Institution :
Coll. of Inf. & Control Eng., Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
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;
Conference_Titel :
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-7957-3
DOI :
10.1109/CMCE.2010.5609861
