Premium
Comparison of multivariate methods for robust parameter design in sheet metal spinning
Author(s) -
Auer Corinna,
Erdbrügge Martina,
Göbel Roland
Publication year - 2004
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.525
Subject(s) - spinning , multivariate statistics , sheet metal , quality (philosophy) , scope (computer science) , process (computing) , computer science , design of experiments , multivariate analysis , mathematical optimization , statistics , mathematics , mechanical engineering , engineering , machine learning , physics , quantum mechanics , programming language , operating system
Abstract Sheet metal spinning is a very complex forming process with a large number of quality characteristics. Within the scope of a joint project of the Department of Statistics and the Chair of Forming Technology the impact of process parameters (design factors) on important quality characteristics has been investigated both theoretically and experimentally. In the past, every response has been treated individually and uncontrollable disturbances (noise factors) have been neglected. Now this approach has been extended to robust multiresponse parameter design. For this, a review of common multivariate approaches for robust parameter design has been carried out, which also leads to the proposal of some new variants. In addition to the theoretical comparison, the methods were applied to data gained in the sheet metal spinning process. The obtained results were evaluated in terms of applicability, limitations and quality accuracy. Practical experiments confirmed the high degree of efficiency that the finally proposed method based on desirabilities promises. Copyright © 2004 John Wiley & Sons, Ltd.