Title :
Visualization and data mining method for inventory classification
Author_Institution :
Member, IEEE, Department of Informatics, Tallinn University of Technology, 15 Raja Street, EE-12618 Tallinn, ESTONIA. phone: +3725200552; fax: +3726202305; e-mail: innar.liiv@ttu.ee
Abstract :
Inventory classification of stock-keeping units is typically achieved with ABC analysis accompanied with a diagram describing the distribution of dollar-usage values. Unfortunately, it fails to identify the interdependencies between the products, which may lead to alienating customers by ignoring the effect of assortments of choices. To remedy this problem, we propose new visualization and product interdependency identification methods. Experimental results in real-world scenarios for two warehouse datasets are included and analyzed.
Keywords :
Assembly; Data mining; Data visualization; Group technology; History; Inventory management; Manufacturing; Pareto analysis; Profitability; Spirals; ABC classification; annual-dollar-usage ranking method; data mining; inventory management;
Conference_Titel :
Service Operations and Logistics, and Informatics, 2007. SOLI 2007. IEEE International Conference on
Conference_Location :
Philadelphia, PA, USA
Print_ISBN :
978-1-4244-1118-4
Electronic_ISBN :
978-1-4244-1118-4
DOI :
10.1109/SOLI.2007.4383909
