Optimal product portfolio formulation: Merging predictive data mining with analytical target cascading

Conrad S. Tucker, Harrison M. Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 survey data is translated into performance design targets. Second is platform architecture design that we model as a dynamic entity. The dynamic approach to product architecture optimization differs from conventional static approaches in that a predefined architecture is not present 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 our cell phone product family example presented in this work. An optimal family of cell phones is created with modularity decisions made analytically at the enterprise level that maximize company profit.

Original languageEnglish (US)
Title of host publicationCollection of Technical Papers - 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
Pages768-781
Number of pages14
ISBN (Print)1563478234, 9781563478239
DOIs
StatePublished - Jan 1 2006
Event11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference - Portsmouth, VA, United States
Duration: Sep 6 2006Sep 8 2006

Publication series

NameCollection of Technical Papers - 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference
Volume2

Other

Other11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference
Country/TerritoryUnited States
CityPortsmouth, VA
Period9/6/069/8/06

ASJC Scopus subject areas

  • Engineering(all)

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