IDEAS home Printed from https://ideas.repec.org/a/ids/ijpqma/v7y2011i1p22-43.html
   My bibliography  Save this article

Prediction of dimensional accuracy in fused deposition modelling: a fuzzy logic approach

Author

Listed:
  • Asif Equbal
  • Anoop Kumar Sood
  • S.S. Mahapatra

Abstract

In the present work, effect of five factors viz., layer thickness, part build orientation, raster angle, raster to raster gap (air gap) and raster width each at three levels together with their interactions is studied on dimensional accuracy of fused deposition modelling (FDM) build part. Four performance characteristics i.e. percentage change in length, width, thickness and diameter considered in this study are converted into an equivalent response known as grey relational grade. Optimum factor levels are determined for maximisation of grey relational grade using grey-based Taguchi method. A fuzzy inference system (FIS) is proposed for prediction of overall dimensional accuracy using Taguchi's orthogonal array for developing inference engine. The results of FIS are compared with prediction values obtained through artificial neural network. It has been demonstrated that fuzzy model is able to predict overall dimensional accuracy at all operating condition to a high degree of accuracy.

Suggested Citation

  • Asif Equbal & Anoop Kumar Sood & S.S. Mahapatra, 2011. "Prediction of dimensional accuracy in fused deposition modelling: a fuzzy logic approach," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 7(1), pages 22-43.
    • Handle: RePEc:ids:ijpqma:v:7:y:2011:i:1:p:22-43
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=37730
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Felix W. Baumann & Julian R. Eichhoff & Dieter Roller, 2017. "Scanned Image Data from 3D-Printed Specimens Using Fused Deposition Modeling," Data, MDPI, vol. 2(1), pages 1-24, January.

    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:ids:ijpqma:v:7:y:2011:i:1:p:22-43. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=177 .

    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.