Abstract

Traditionally, cost estimation methods are used to predict costs only after a product model has been built, and not at an early design stage when there is little data and information available. The traditional cost models and systems used require a large amount of detailed data before a cost calculation can be made. This research has identified that, one of the main challenges to improve this situation in modelling cost is data identification and collection. The aim of this paper therefore is to discuss the methods of developing an extended-enterprise digital data library, data searching and data transfer mechanisms to support through-life cost estimation in the innovative product development processes. The paper begins with an introduction of relevant research in data modelling in cost estimation. This is followed by a section, which highlights problems of performing cost estimates for innovative low volume products, and subsequently the proposed solutions and example applications.

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