Alternatives of Taguchi's Approach for Dynamic Robust Design Problems

Author(s):  
Kwok-Leung Tsui

Robust Design is an important method for improving product quality, manufacturability, and reliability at low cost. Most research in robust design has been focused on problems with static responses. This paper deals with the robust design problems with dynamic responses. The objective of the paper is to investigate and compare three modeling approaches: the loss model, the response function model, and the response model approaches. Taguchi16 proposes the loss model approach which models the loss measures as functions of the control factor effects. Miller and Wu10 propose the response function model approach which models the loss measures as functions of the effects of both control and noise factors. Tsui18 proposes the response model approach which directly models the response as a function of the effects of control, noise, and signal factors. In this paper, we identify and derive the relationships between the effect estimates of the three approaches and show that the loss model approach creates unnecessary biases for the factorial effect estimates and may lead to non-optimal solutions. The three modeling approaches are compared in a real example.

2009 ◽  
Vol 23 (03) ◽  
pp. 477-480 ◽  
Author(s):  
ZHILI TANG

The Taguchi robust design concept is combined with the multi-objective deterministic optimization method to overcome single point design problems in Aerodynamics. Starting from a statistical definition of stability, the method finds, Nash equilibrium solutions for performance and its stability simultaneously.


Author(s):  
Nestor F. Michelena ◽  
Alice M. Agogino

Abstract The Taguchi method of product design is a statistical experimental technique aimed at reducing the variance of a product performance characteristic due to uncontrollable factors. The goal of this paper is to provide a monotonicity analysis based methodology to facilitate the solution of N-type parameter design problems. The obtained design is robust, i.e., the least sensitive to variations on uncontrollable factors (noise). The performance characteristic is unbiased in the sense that its expected value equals a target or specification. The proposed loss function is based on the absolute deviation of the characteristic with respect to the target, instead of the common square error approach. Conditions, like those imposed by monotonicity analysis, on the monotonic characteristics of the performance function are proven, despite the objective function is not monotonic and contains stochastic parameters. These conditions allow the qualitative analysis of the problem to identify the activity of some constraints. Identification of active sets of constraints allows a problem reduction strategy to be employed, where the solution to the original problem is obtained by solving a set of problems with fewer degrees of freedom. Results for the case of one uncontrollable factor are independent of the probability measure on the factor. However, conclusions for the multi-parametric case must take into account the characteristics of the probability space on which the random parameters are defined.


2013 ◽  
Vol 24 (1) ◽  
pp. 64-81 ◽  
Author(s):  
Thomas Quirante ◽  
Patrick Sebastian ◽  
Yann Ledoux

Author(s):  
PS Suresh ◽  
Niranjan K Sura ◽  
K Shankar

The dynamic responses simulation of aircraft as rigid body considering heave, pitch, and roll motions, coupled onto a tricycle landing gear arrangement is presented. Equation of motion for each landing gear consists of un-sprung mass vertical and longitudinal motions considering strut nonlinear stiffness and damping combined with strut bending flexibility. Initially, the nonlinear dynamic response model is subjected to an input of riding over staggered bump and the responses are compared with linear landing gear model. It is observed that aircraft dynamics and important landing gear events such as vertical, spin-up and spring-back are truly represented with nonlinear stiffness and damping model considering strut bending flexibility. Later, landing response analysis is performed, with the input from nonlinear flight mechanics model for several vertical descent rate cases. The aircraft and landing gear dynamic responses such as displacement, velocity, acceleration, and reaction forces are obtained. The vertical and longitudinal drag forces from the nonlinear dynamic response model is compared with “Book-case method” outlined in landing gear design technical specifications. From the reaction force ratio calculation, it is shown that for lower vertical descent rate case the predicted loads are lesser using nonlinear dynamic response model. The same model for higher vertical descent rate cases predicts higher ratios on vertical reaction for main landing gear and longitudinal reaction for nose landing gear, respectively. The scope for increase in fatigue life for low vertical descent rate landing covering major design spectrum and the concern for static strength and structural integrity consideration for higher vertical descent rate cases are discussed in the context of event monitoring on aircraft in services.


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