Enhancement of adaptable product development by computerised comparison of requirement lists
by Jörg Feldhusen; Eliseo Milonia; Arun Nagarajah; Jan Neis; Sebastian Schubert
International Journal of Product Lifecycle Management (IJPLM), Vol. 6, No. 1, 2012

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.

Online publication date: Sat, 16-Aug-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Product Lifecycle Management (IJPLM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com