Fatigue Focused Optimization of Treatment Parameters – A Case Study about Deep Cryogenic Treatment

Abstract:

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The problem of treatment parameter optimization focused on the fatigue resistance is analysed through a case study about Deep Cryogenic Treatment (DCT) of AISI 302 steel. In particular, the possibility to integrate fatigue data fittings through the Maximum Likelihood Estimation (MLE) method in the optimization process is evaluated. Two levels of two parameters (soaking time and temperature) are considered and then expanded to three by proper scaling of their values in order to include the untreated case as a “zero” level. Fatigue focused optimization is then achieved by standard Response Surface Method (RSM) and by MLE with two models for comparison purposes.

Info:

Periodical:

Key Engineering Materials (Volumes 488-489)

Edited by:

Z. Tonković and M.H. Aliabadi

Pages:

498-501

DOI:

10.4028/www.scientific.net/KEM.488-489.498

Citation:

P. Baldissera and C. Delprete, "Fatigue Focused Optimization of Treatment Parameters – A Case Study about Deep Cryogenic Treatment", Key Engineering Materials, Vols. 488-489, pp. 498-501, 2012

Online since:

September 2011

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Price:

$35.00

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