Abstract
In mass customization, data mining can be used to extract valid, previously unknown, and easily interpretable information from large product databases in order to improve and optimize engineering design and manufacturing process decisions. A product family is a group of related products based on a product platform, facilitating mass customization by providing a variety of products for different market segments cost-effectively. In this paper, we propose a method for identifying a platform along with variant and unique modules in a product family using data mining techniques. Association rule mining is applied to develop rules related to design knowledge based on product function, which can be clustered by their similarity based on functional features. Fuzzy c-means clustering is used to determine initial clusters that represent modules. The clustering result identifies the platform and its modules by a platform level membership function and classification. We apply the proposed method to determine a new platform using a case study involving a power tool family.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of 2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006 |
| State | Published - Nov 29 2006 |
| Event | 2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006 - Philadelphia, PA, United States Duration: Sep 10 2006 → Sep 13 2006 |
Publication series
| Name | Proceedings of the ASME Design Engineering Technical Conference |
|---|---|
| Volume | 2006 |
Other
| Other | 2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006 |
|---|---|
| Country | United States |
| City | Philadelphia, PA |
| Period | 9/10/06 → 9/13/06 |
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All Science Journal Classification (ASJC) codes
- Modeling and Simulation
- Mechanical Engineering
- Computer Science Applications
- Computer Graphics and Computer-Aided Design
Cite this
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Data mining and fuzzy clustering to support product family design. / Moon, Seung Ki; Tirupatikumara, Soundar Rajan; Simpson, Timothy William.
Proceedings of 2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006. 2006. (Proceedings of the ASME Design Engineering Technical Conference; Vol. 2006).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Data mining and fuzzy clustering to support product family design
AU - Moon, Seung Ki
AU - Tirupatikumara, Soundar Rajan
AU - Simpson, Timothy William
PY - 2006/11/29
Y1 - 2006/11/29
N2 - In mass customization, data mining can be used to extract valid, previously unknown, and easily interpretable information from large product databases in order to improve and optimize engineering design and manufacturing process decisions. A product family is a group of related products based on a product platform, facilitating mass customization by providing a variety of products for different market segments cost-effectively. In this paper, we propose a method for identifying a platform along with variant and unique modules in a product family using data mining techniques. Association rule mining is applied to develop rules related to design knowledge based on product function, which can be clustered by their similarity based on functional features. Fuzzy c-means clustering is used to determine initial clusters that represent modules. The clustering result identifies the platform and its modules by a platform level membership function and classification. We apply the proposed method to determine a new platform using a case study involving a power tool family.
AB - In mass customization, data mining can be used to extract valid, previously unknown, and easily interpretable information from large product databases in order to improve and optimize engineering design and manufacturing process decisions. A product family is a group of related products based on a product platform, facilitating mass customization by providing a variety of products for different market segments cost-effectively. In this paper, we propose a method for identifying a platform along with variant and unique modules in a product family using data mining techniques. Association rule mining is applied to develop rules related to design knowledge based on product function, which can be clustered by their similarity based on functional features. Fuzzy c-means clustering is used to determine initial clusters that represent modules. The clustering result identifies the platform and its modules by a platform level membership function and classification. We apply the proposed method to determine a new platform using a case study involving a power tool family.
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UR - http://www.scopus.com/inward/citedby.url?scp=33751344622&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33751344622
SN - 079183784X
SN - 9780791837849
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - Proceedings of 2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006
ER -