Interdisciplinary life cycle data analysis within a knowledge-based system for product cost estimation

Stefania Altavilla, Francesca Montagna, Linda Newnes

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)


Product lifecycle has become one of the most relevant cost drivers for many manufacturing companies. Companies, in fact, are forced to reduce not only the costs that directly determine the price of the product, but they must also evaluate those costs that affect the entire lifecycle since customers are now considering after-sale services in their purchasing decision. However, implementing a product lifecycle perspective is challenging for an organisation if the uncertainty related to the duration of the life cycle process as well as the collection of a large amount of data are taken into account. Data, if correctly collected, contain valuable information that can be extracted and integrated into the analysis, to improve better design decisions and enhance product quality. For this purpose, this research proposed a knowledge-based system that uses empirical data, and information available across phases of product's lifecycle, and suggests how different qualitative and quantitative analyses can be performed, to transform the results in valuable feedback for future product development, while also providing a cost estimation.

Original languageEnglish
Pages (from-to)375-384
Number of pages10
JournalProceedings of the International Conference on Engineering Design (ICED 2017)
Issue numberDS87-5
Publication statusPublished - Aug 2017
EventInternational Conference on Engineering Design ICED 2017 - University of British Columbia, Vancouver, Canada
Duration: 21 Aug 201725 Aug 2017


  • Conceptual design
  • Design costing
  • Design for X (DfX)
  • Knowledge management

ASJC Scopus subject areas

  • Engineering (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Modelling and Simulation


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