Title: Enhancement of adaptable product development by computerised comparison of requirement lists

Authors: Jörg Feldhusen; Eliseo Milonia; Arun Nagarajah; Jan Neis; Sebastian Schubert

Addresses: Chair and Institute for Engineering Design, RWTH Aachen University, Steinbachstrasse 54B, 52074 Aachen, Germany. ' Info-key GmbH and Co. KG, Wuppertal, Heinz-Fangman-Strasse, 42287 Wuppertal, Germany. ' Chair and Institute for Engineering Design, RWTH Aachen University, Steinbachstrasse 54B, 52074 Aachen, Germany. ' Chair and Institute for Engineering Design, RWTH Aachen University, Steinbachstrasse 54B, 52074 Aachen, Germany. ' Chair and Institute for Engineering Design, RWTH Aachen University, Steinbachstrasse 54B, 52074 Aachen, Germany

Abstract: This paper shows how the data mining method known as self-organising maps (SOM) can be applied to optimise the selection of a product variant designated as the starting point for adaptive product development. SOM is a clustering technique in which the similarity of specifications is measured and visualised to assist selection of the optimum product variant. An initial step involves preparing the requirements in the specifications so that they can be applied to SOM. Emphasis is placed on linguistic formalisation in order to detect identical requirements and on quantification of the requirements, which is mandatory. The final part of the paper describes the SOM approach.

Keywords: adaptive product development; engineering design; self organising maps; SOM; data mining; product variants; requirements.

DOI: 10.1504/IJPLM.2012.046428

International Journal of Product Lifecycle Management, 2012 Vol.6 No.1, pp.20 - 32

Accepted: 06 May 2011
Published online: 08 Apr 2012 *

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