IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-7908-2380-6_4.html
   My bibliography  Save this book chapter

Quality Control of Manufactured Surfaces

In: Frontiers in Statistical Quality Control 9

Author

Listed:
  • Bianca Maria Colosimo

    (Dipartimento di Meccanica - Politecnico di Milano)

  • Federica Mammarella

    (Dipartimento di Meccanica - Politecnico di Milano)

  • Stefano Petrò

    (Dipartimento di Meccanica - Politecnico di Milano)

Abstract

Summary Recent literature on statistical process monitoring pointed out that the quality of products and processes can be often related to profiles, where the function relating a response to one or more location variables (in time or space) is the quality characteristic of interest. An important application of profile monitoring concerns geometric specifications of mechanical components, such as straightness, roundness or free-form tolerance. This paper presents a new approach aimed at extending the method proposed for profile monitoring to surface monitoring. In this case, a geometric specification (such as cylindricity, flatness, etc.) is assumed to characterize the machined surface. The proposed method is based on combining a Spatial Autoregressive Regression (SARX) model (i.e. a regression model with spatial autoregressive errors) to multivariate and univariate control charting. In this work, the approach is applied to a case study concerning surfaces obtained by turning and subject to cylindricity tolerance.

Suggested Citation

  • Bianca Maria Colosimo & Federica Mammarella & Stefano Petrò, 2010. "Quality Control of Manufactured Surfaces," Springer Books, in: Hans-Joachim Lenz & Peter-Theodor Wilrich & Wolfgang Schmid (ed.), Frontiers in Statistical Quality Control 9, pages 55-70, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2380-6_4
    DOI: 10.1007/978-3-7908-2380-6_4
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-7908-2380-6_4. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.