Optimal Product Portfolio Formulation: Merging Predictive Data Mining with Analytical Target Cascading

2006 ◽  
Author(s):  
Conrad Tucker ◽  
Harrison Kim
Keyword(s):  
Data Mining ◽  
Product Portfolio ◽  
Analytical Target Cascading ◽  
Target Cascading ◽  
Predictive Data Mining

Optimal Product Portfolio Formulation by Merging Predictive Data Mining With Multilevel Optimization

2008 ◽  
Vol 130 (4) ◽  
Author(s):  
Conrad S. Tucker ◽  
Harrison M. Kim
Keyword(s):  
Data Mining ◽  
Product Family ◽  
Product Architecture ◽  
Product Portfolio ◽  
Market Demand ◽  
Customer Preference ◽  
Data Mining Approach ◽  
Engineering Level ◽  
Initial Stage ◽  
Predictive Data Mining

This paper addresses two important fundamental areas in product family formulation that have recently begun to receive great attention. First is the incorporation of market demand that we address through a data mining approach where realistic customer preference data are translated into performance design targets. Second is product architecture reconfiguration that we model as a dynamic design entity. The dynamic approach to product architecture optimization differs from conventional static approaches in that a product architecture is not fixed at the initial stage of product design, but rather evolves with fluctuations in customer performance preferences. The benefits of direct customer input in product family design will be realized through the cell phone product family example presented in this work. An optimal family of cell phones is created with modularity decisions made analytically at the engineering level that maximize company profit.

scholarly journals An Enhanced Analytical Target Cascading and Kriging Model Combined Approach for Multidisciplinary Design Optimization

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ping Jiang ◽  
Jianzhuang Wang ◽  
Qi Zhou ◽  
Xiaolin Zhang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Kriging Model ◽  
Multidisciplinary Design ◽  
High Approximation ◽  
Engineering Systems ◽  
Analytical Target Cascading ◽  
Combined Approach ◽  
Coordination Strategy ◽  
Target Cascading

Multidisciplinary design optimization (MDO) has been applied widely in the design of complex engineering systems. To ease MDO problems, analytical target cascading (ATC) organizes MDO process into multilevels according to the components of engineering systems, which provides a promising way to deal with MDO problems. ATC adopts a coordination strategy to coordinate the couplings between two adjacent levels in the design optimization process; however, existing coordination strategies in ATC face the obstacles of complicated coordination process and heavy computation cost. In order to conquer this problem, a quadratic exterior penalty function (QEPF) based ATC (QEPF-ATC) approach is proposed, where QEPF is adopted as the coordination strategy. Moreover, approximate models are adopted widely to replace the expensive simulation models in MDO; a QEPF-ATC and Kriging model combined approach is further proposed to deal with MDO problems, owing to the comprehensive performance, high approximation accuracy, and robustness of Kriging model. Finally, the geometric programming and reducer design cases are given to validate the applicability and efficiency of the proposed approach.

scholarly journals Analytical target cascading for optimal configuration of cloud manufacturing services

2017 ◽  
Vol 151 ◽  
pp. 330-343 ◽  
Author(s):  
Yingfeng Zhang ◽  
Geng Zhang ◽  
Ting Qu ◽  
Yang Liu ◽  
Ray Y. Zhong
Keyword(s):  
Cloud Manufacturing ◽  
Optimal Configuration ◽  
Analytical Target Cascading ◽  
Target Cascading
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