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Mining Industrial Engineered Data of Apparel Industry: A Proposed Methodology

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Md Shamsur Rahim, Mashiour Rahman, Azm Ehtesham Chowdhury

Md Shamsur Rahim, Mashiour Rahman and Azm Ehtesham Chowdhury. Mining Industrial Engineered Data of Apparel Industry: A Proposed Methodology. International Journal of Computer Applications 161(7):1-7, March 2017. BibTeX

	author = {Md Shamsur Rahim and Mashiour Rahman and Azm Ehtesham Chowdhury},
	title = {Mining Industrial Engineered Data of Apparel Industry: A Proposed Methodology},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2017},
	volume = {161},
	number = {7},
	month = {Mar},
	year = {2017},
	issn = {0975-8887},
	pages = {1-7},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2017913262},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Data mining and knowledge discovery play a significant role in the field of industrial engineering as the vast amount of generated data help to reveal previously unknown interesting patterns and knowledge. Many industries have already adopted data mining techniques for better productivity by following clear and concise methodologies. But apparel industries are yet waiting to adopt data mining techniques due to the absence of a data mining methodology which meets the particular requirements and business objectives. The objective of this research is to develop such a mining methodology that will be able to fulfill the requirements of apparel industries. This research paper has proposed a methodology for mining industrial engineered manufacturing data of apparel industries. This methodology covers from analysis of apparel industrys manufacturing unit to implement and evaluate mining model. It also includes the analysis of different departments in manufacturing to identify correlation and dependencies among the departments which is absent in the existing methodologies. Furthermore, the proposed methodology provides a clear and unambiguous transitions among different steps to perform data mining.


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Apparel industry, industrial engineering, data mining, data mining methodology, manufacturing data