Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

데이터 마이닝 기반의 품질설계지원시스템Quality Design Support System based on Data Mining Approach

Other Titles
Quality Design Support System based on Data Mining Approach
Authors
지원철
Issue Date
2003
Publisher
한국경영과학회
Keywords
Intelligent Quality System; Data Mining; Artificial Neural Network; Case Base Reasoning; Data Screening; Quality Design Simulation; Model Management System; Intelligent Quality System; Data Mining; Artificial Neural Network; Case Base Reasoning; Data Screening; Quality Design Simulation; Model Management System
Citation
한국경영과학회지, v.28, no.3, pp.31 - 47
Journal Title
한국경영과학회지
Volume
28
Number
3
Start Page
31
End Page
47
URI
https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/26074
ISSN
1225-1119
Abstract
Quality design in practice highly depends on human designer's intuition and past experiences due to lack of formal knowledge about the relationship among IO variables. This paper represents an data mining approach for developing quality design support system that integrates Case Based Reasoning (CBR) and Artificial Neural Networks (ANN) to effectively support all the steps in quality design process. CBR stores design cases in a systematic way and retrieve them quickly and accurately. ANN predicts the resulting quality attributes of design alternatives that are generated from CBR's adaptation process. When the predicted attributes fail to meet the target values, quality design simulation starts to further adapt the alternatives to the customer's new orders. To implement the quality design simulation, this paper suggests (1) the data screening method based on ξ-δ Ball to obtain the robust ANN models from the large production data bases, (2) the procedure of quality design simulation using ANN and (3) model management system that helps users find the appropriate one from the ANN model base. The integration of CBR and ANN provides quality design engineers the way that produces consistent and reliable design solutions in the remarkably reduced time.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > Industrial and Data Engineering > Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Jhee, Won Chul photo

Jhee, Won Chul
Engineering (Industrial and Data Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE