Implementation of Association Rule Mining in the domain of Dyeing Unit and Related Issues

Saravanan .M.S, Rama Sree .R.J

Abstract


In the past two decade the textile industry has grown in high to export the fabrics to other countries. To export high quality fabrics, particularly cotton cloths, the colouring process plays major role in the dyeing domain. The dyeing is a dynamic, complex and involved various discipline. The dyeing process is difficult to automate processes, because of their interdisciplinary and dynamic in nature. Moreover, it is also critical to keep a check on the automated processes to produce the expected results in the form of quality and timely dyeing processes. Delivering high quality colours are very difficult due to lot of constraints, such as poor dye mix powders, bad processing methods, etc. Hence, the dyeing organizations were requiring quality dyeing process methods to produce perfect shade. Therefore, first time the process mining algorithms were used in the previous my research paper. But in this paper the alternative process model that is association rule mining approach was used in the domain of dyeing unit to produce better understanding dyeing process model in the form of association rules to overcome the difficulties and limitations of process mining algorithms. The benefit of association rule mining is very easy to understand the dyer to process the colour with little difficulties. Hence, these systems can reduce the cost, improved operational efficiencies, pH test error reduction, improved shade quality, etc. Therefore, the main focus of this paper is to implement the association rule mining approach in the dyeing unit and discussed the related issues.

 

 


Keywords: Textiles, Fabrics, Dyeing, Automate, Association rule mining, Shades


Full Text:

PDF


DOI: https://doi.org/10.26483/ijarcs.v2i4.676

Refbacks

  • There are currently no refbacks.




Copyright (c) 2016 International Journal of Advanced Research in Computer Science