IDEAS home Printed from
MyIDEAS: Login to save this article or follow this journal

Rapid cost estimation of metallic components for the aerospace industry

  • de Cos, Javier
  • Sanchez, Fernando
  • Ortega, Francisco
  • Montequin, Vicente
Registered author(s):

    This paper illustrates and compares the results of the application of two different approaches--non-parametric and artificial neural network techniques--for the rapid cost estimation of turbine components. This technique is a simple and automatic way for the estimation of the cost of a piece with no expert intervention. Three methods of estimation are compared: the projection pursuit method (PPR), the local polynomial approach (LOESS) and adaptive neural networks (ANNs). This comparative analysis serves to enhance current work that seeks to choose the optimum predictor model. The results confirm the validity of the neural network theory in this field of application, but not a clear superiority as compared with the non-parametric approach. The present research provides a new tool to avoid inadequate piece budgeting strategies. The use of these methods contributes to the minimisation of errors in the budgeting of new items.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Elsevier in its journal International Journal of Production Economics.

    Volume (Year): 112 (2008)
    Issue (Month): 1 (March)
    Pages: 470-482

    in new window

    Handle: RePEc:eee:proeco:v:112:y:2008:i:1:p:470-482
    Contact details of provider: Web page:

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    1. H'mida, Fehmi & Martin, Patrick & Vernadat, Francois, 2006. "Cost estimation in mechanical production: The Cost Entity approach applied to integrated product engineering," International Journal of Production Economics, Elsevier, vol. 103(1), pages 17-35, September.
    2. Kearns, P., 1993. "Volatility and the Pricing of Interest Rate Derivative Claims," Papers 47, Rochester, Business - Ph.D.,.
    3. Barria, J A & Hall, Stephen G, 2002. "A Non-parametric Approach to Pricing and Hedging Derivative Securities: With an Application to LIFFE Data," Computational Economics, Society for Computational Economics, vol. 19(3), pages 303-22, June.
    4. James M. Hutchinson & Andrew W. Lo & Tomaso Poggio, 1994. "A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks," NBER Working Papers 4718, National Bureau of Economic Research, Inc.
    5. Araz, Ceyhun & Ozkarahan, Irem, 2007. "Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure," International Journal of Production Economics, Elsevier, vol. 106(2), pages 585-606, April.
    6. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:112:y:2008:i:1:p:470-482. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.