@article{(Open Science Index):https://publications.waset.org/pdf/13143,
	  title     = {Reducing Variation of Dyeing Process in Textile Manufacturing Industry},
	  author    = {M. Zeydan and  G. Toğa},
	  country	= {},
	  institution	= {},
	  abstract     = {This study deals with a multi-criteria optimization
problem which has been transformed into a single objective
optimization problem using Response Surface Methodology (RSM),
Artificial Neural Network (ANN) and Grey Relational Analyses
(GRA) approach. Grey-RSM and Grey-ANN are hybrid techniques
which can be used for solving multi-criteria optimization problem.
There have been two main purposes of this research as follows.
1. To determine optimum and robust fiber dyeing process
conditions by using RSM and ANN based on GRA,
2. To obtain the best suitable model by comparing models
developed by different methodologies.
The design variables for fiber dyeing process in textile are
temperature, time, softener, anti-static, material quantity, pH,
retarder, and dispergator. The quality characteristics to be evaluated
are nominal color consistency of fiber, maximum strength of fiber,
minimum color of dyeing solution. GRA-RSM with exact level
value, GRA-RSM with interval level value and GRA-ANN models
were compared based on GRA output value and MSE (Mean Square
Error) performance measurement of outputs with each other. As a
result, GRA-ANN with interval value model seems to be suitable
reducing the variation of dyeing process for GRA output value of the
model.},
	    journal   = {International Journal of Materials and Textile Engineering},
	  volume    = {5},
	  number    = {11},
	  year      = {2011},
	  pages     = {2272 - 2280},
	  ee        = {https://publications.waset.org/pdf/13143},
	  url   	= {https://publications.waset.org/vol/59},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 59, 2011},
	}