Aerodynamic Drag and Noise Minimization of Rear End Parameters in a Simplified Car Model Utilizing Robust Parameter Design Method

2015 ◽  
Author(s):  
Sajjad Beigmoradi
Keyword(s):  
Aerodynamic Drag ◽  
Design Method ◽  
Parameter Design ◽  
Robust Parameter Design ◽  
Car Model ◽  
Robust Parameter

Study on Bonding Technology Parameter Optimize of MEMS Packaging Based on Robust Parameter Design

2011 ◽  
Vol 422 ◽  
pp. 370-374
Author(s):  
Jin Wei Yu
Keyword(s):  
Raw Materials ◽  
Design Method ◽  
Parameter Design ◽  
Robust Parameter Design ◽  
Packaging Technology ◽  
Mems Packaging ◽  
New Type ◽  
Robust Parameter ◽  
Bonding Technology ◽  
Economy Benefit

In order to improving reliability and economy of down-lead bonding of MEMS packaging , NiPdAu PCB is leaded in ,because palladium is joined in protecting involucra , bonding technology parameter must change . In this paper , robust parameter design method of DOE is used and optimize bonding technology parameter of new type NiPdAu involucra has been discovered , according to optimize results , mending bonding technology parameter and Ni Pd Au PCB is triumphantly used into MEMS packaging technology , not only increasing reliability of products , but also reducing cost of raw materials and obtaining well economy benefit.

A semi-parametric approach to robust parameter design

2008 ◽  
Vol 138 (1) ◽  
pp. 114-131 ◽  
Author(s):  
Stephanie M. Pickle ◽  
Timothy J. Robinson ◽  
Jeffrey B. Birch ◽  
Christine M. Anderson-Cook
Keyword(s):  
Parameter Design ◽  
Robust Parameter Design ◽  
Parametric Approach ◽  
Robust Parameter

scholarly journals A Confidence Region for Zero-Gradient Solutions for Robust Parameter Design Experiments

2011 ◽  
Vol 2011 ◽  
pp. 1-11
Author(s):  
Aili Cheng ◽  
John Peterson ◽  
Pallavi Chitturi
Keyword(s):  
Confidence Region ◽  
Control Variable ◽  
Critical Values ◽  
Parameter Design ◽  
Feasible Region ◽  
Robust Parameter Design ◽  
Control Variables ◽  
Controllable Factors ◽  
Key Issues ◽  
Robust Parameter

One of the key issues in robust parameter design is to configure the controllable factors to minimize the variance due to noise variables. However, it can sometimes happen that the number of control variables is greater than the number of noise variables. When this occurs, two important situations arise. One is that the variance due to noise variables can be brought down to zero The second is that multiple optimal control variable settings become available to the experimenter. A simultaneous confidence region for such a locus of points not only provides a region of uncertainty about such a solution, but also provides a statistical test of whether or not such points lie within the region of experimentation or a feasible region of operation. However, this situation requires a confidence region for the multiple-solution factor levels that provides proper simultaneous coverage. This requirement has not been previously recognized in the literature. In the case where the number of control variables is greater than the number of noise variables, we show how to construct critical values needed to maintain the simultaneous coverage rate. Two examples are provided as a demonstration of the practical need to adjust the critical values for simultaneous coverage.

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