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     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2012(Vol.4, Issue:17)
Article Information:

The Study of an Exponential Parametric Model for Evaluating Parallelism Deviation of Aerospace Alloys during Turning

Nosratollah Solhjoei, Amir Vafaei, Forood Khalilzadeh and Keyvan Vafaei
Corresponding Author:  Nosratollah Solhjoei 
Submitted: January 03, 2012
Accepted: January 25, 2012
Published: September 01, 2012
Abstract:
Aeronautical industrial sector applies currently aluminium alloys in a wide range of its products. Aerospace precision requirements are highly restricted. Thus, dimensional precision is commonly studied in the manufacturing processes of aerospace alloys, such aluminium. As a consequence of this, quality finish of machined aluminium alloys for aeronautical use is deeply analysed, although mainly in terms of dimensional accuracy. Geometrical precision is usually studied from roughness analysis, which only has into account microgeometrical aspects. However, macrogeometrical precision is commonly far of the objectives in some of those analyses. In this work, Parallelism Deviations (PD) of dry turned UNS A92024 (Al-Cu) and UNS A97050 (Al-Zn) samples have been evaluated for different machining conditions (cutting speeds and feeds). A parametric model for the parallelism deviation as a function of those cutting parameters has been established from the mathematical treatment of the results obtained. In parallel, a prediction surface PD (f, v) has been constructed from the 3D interpolation of the set of (f, v, PD) points. This surface allows determining marginal PD (f) and PD (v) curves for specific v and f values, respectively.

Key words:  Dry turning, parallelism deviation, UNS A92024, UNS A97050, , ,
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Cite this Reference:
Nosratollah Solhjoei, Amir Vafaei, Forood Khalilzadeh and Keyvan Vafaei, . The Study of an Exponential Parametric Model for Evaluating Parallelism Deviation of Aerospace Alloys during Turning. Research Journal of Applied Sciences, Engineering and Technology, (17): 3027-3030.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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