Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/184554
Authors: 
Relich, Marcin
Year of Publication: 
2013
Citation: 
[Journal:] Foundations of Management [ISSN:] 2300-5661 [Volume:] 5 [Year:] 2013 [Issue:] 2 [Pages:] 49-58
Abstract: 
Nowadays, more and more enterprises are using Enterprise Resource Planning (EPR) systems that can also be used to plan and control the development of new products. In order to obtain a project schedule, certain parameters (e.g. duration) have to be specified in an ERP system. These parameters can be defined by the employees according to their knowledge, or can be estimated on the basis of data from previously completed projects. This paper investigates using an ERP database to identify those variables that have a significant influence on the duration of a project phase. In the paper, a model of knowledge discovery from an ERP database is proposed. The presented method contains four stages of the knowledge discovery process such as data selection, data transformation, data mining and interpretation of patterns in the context of new product development. Among data mining techniques, a fuzzy neural system is chosen to seek relationships on the basis of data from completed projects stored in an ERP system.
Subjects: 
knowledge management
new product development
knowledge discovery in databases
data mining
ERP system
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-nc-nd/3.0
Document Type: 
Article
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