Customer Oriented Product Design by Adaptive Clustering Analysis

Wei Hui Dai

doi:10.4028/www.scientific.net/AMM.26-28.690

Paper Titles

Development and Application of the Optimization Design of Progressive Die Based on Transfer Unit
p.671

A Fault Diagnosis Method of Rolling Bearing through Wear Particle and Vibration Analyses
p.676

Preparation and Characterization of Nanosized Barium-Strontium Titanate Immobilized on Aluminum Oxide and Its Application in Adsorption
p.682

Autonomous Intelligent System for Supply Chain Management on Mass Customization Manufacture
p.686

Customer Oriented Product Design by Adaptive Clustering Analysis
p.690

Modeling on the Ground Wafer Shape in Wafer Rotational Grinding
p.694

Green Laser Drilling Assisted with Neutral Salt Solution
p.698

An Adjustable Adaptive Subdivision Surface Modeling Based on Triangle Meshes
p.702

A Coupling Dynamic Model for Interfacial Reaction between Slag and Metal of Stainless Steelmaking by Chromium Ore Smelting Reduction in a Converter
p.706

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 26-28Customer Oriented Product Design by Adaptive...

Customer Oriented Product Design by Adaptive Clustering Analysis

Abstract:

In the face of increasing competition and diversified demand, product design must be customer oriented for modern enterprises to satisfy the variationally personalized requirements. Thereof; the exact orientation and comprehensive analysis of target customers have been the key to conduct customer oriented product design. This paper presented a new method for the orientation and analysis of target customers by adaptive clustering analysis. By this method, the distribution of customer clusters and the related characteristics of each custer as well as its included customers can be extracted dynamically and adaptively. Applied by this method, the adaptive recommendation system was illustrated for the design of LCD-TV.This paper applied the Autonomous Intelligent System(AIS) to deal with the intelligent activities intelligently and automatically, and thereof provided a new method for the Supply Chain Management(SCM) on MC manufacture. First, a new supply chain model based on E-HUB was presented according to the requirements of MC manufacture, and then the structure and operation of AIS were designed to support that SCM. Finally, the development technology of AIS was discussed.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 26-28)

Pages:

690-693

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.26-28.690

Citation:

Cite this paper

Online since:

June 2010

Authors:

Wei Hui Dai

Keywords:

Clustering, Customer Analysis, Product Design

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Q. D. Wu and L. Wang: Intelligent Ant Colony Algorithm and Application. Technology Press, Shanghai(2004).

Google Scholar

[2] Q. D. Wu and L. Wang, Intelligent Particle Swarm Optimization Algorithm Research and Application. Jiangsu Education Press, NanJing(2005).

Google Scholar

[3] M. K. Ng and Z. Huang: Information and Software Technology. Vol. 41(1999), pp.545-556.

Google Scholar

[4] S. J. Liu: Ant clustering algorithm based on swarm intelligence and its application. Fudan University, Shanghai(2008).

Google Scholar

[5] T. Mu: Research and implementation to clustering technology of browsing behavior based on swarm intelligence. Fudan University, Shanghai(2009).

Google Scholar

[6] E. Bonabeau, M. Dorigo and G. Theraulaz: Swarm Intelligence: From "atural to Artificial Systems. Oxford University Press, New York(1999).

DOI: 10.1093/oso/9780195131581.001.0001

Google Scholar

[7] J. Kennedy, R. C. Eberhart: Swarm Intelligence. Morgan Kaufmann, San Francisco(2001).

Google Scholar

[8] W. H. Dai, S. J. Liu, and S.Y. Liang: Journal of Software. Vol. 4(2009), pp.299-306.

Google Scholar