Performance Distribution Analysis and Robust Design

2000 ◽  
Vol 123 (1) ◽  
pp. 11-17 ◽  
Author(s):  
Jianmin Zhu ◽  
Kwun-Lon Ting
Keyword(s):  
Robust Design ◽  
Robust Parameter Design ◽  
Distribution Analysis ◽  
Performance Space ◽  
Sensitivity Distribution ◽  
Performance Sensitivity ◽  
Design Variables ◽  
Robust Parameter ◽  
Performance Distribution ◽  
Feasible Space

The paper presents the theory of performance sensitivity distribution and a novel robust parameter design technique. In the theory, a Jacobian matrix describes the effect of the component tolerance to the system performance, and the performance distribution is characterized in the variation space by a set of eigenvalues and eigenvectors. Thus, the feasible performance space is depicted as an ellipsoid. The size, shape, and orientation of the ellipsoid describe the quantity as well as quality of the feasible space and, therefore, the performance sensitivity distribution against the tolerance variation. The robustness of a design is evaluated by comparing the fitness between the ellipsoid feasible space and the tolerance space, which is a block, through a set of quantitative and qualitative indexes. The robust design can then be determined. The design approach is demonstrated in a mechanism design problem. Because of the generality of the analysis theory, the method can be used in any design situation as long as the relationship between the performance and design variables can be expressed analytically.

Performance Distribution Analysis and Robust Design

2000 ◽  
Author(s):  
Jianmin Zhu ◽  
Kwun-Lon Ting
Keyword(s):  
Robust Design ◽  
Robust Parameter Design ◽  
Distribution Analysis ◽  
Performance Space ◽  
Sensitivity Distribution ◽  
Performance Sensitivity ◽  
Design Variables ◽  
Robust Parameter ◽  
Performance Distribution ◽  
Feasible Space

Abstract The paper presents the theory of performance sensitivity distribution and a novel robust parameter design technique. In the theory, a Jacobian matrix describes the effect of the component tolerance to the system performance, and the performance distribution is characterized in the variation space by a set of eigenvalues and eigenvectors. Thus, the feasible performance space is depicted as an ellipsoid. The size, shape, and orientation of the ellipsoid describe the quantity as well as quality of the feasible space and, therefore, the performance sensitivity distribution against the tolerance variation. The robustness of a design is evaluated by comparing the fitness between the ellipsoid feasible space and the tolerance space, which is a block, through a set of quantitative and qualitative indexes. The robust design can then be determined. The design approach is demonstrated in a mechanism design problem. Because of the generality of the analysis theory, the method can be used in any design situation as long as the relationship between the performance and design variables can be expressed analytically.

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 The Sensitivity Analysis for Life Estimation of Turbine Blades

1997 ◽  
Author(s):  
O. Repetski ◽  
K. Zainchkovski
Keyword(s):  
Vibration Analysis ◽  
Dynamic Stress ◽  
Natural Frequencies ◽  
Turbine Blades ◽  
Stress Sensitivity ◽  
Life Estimation ◽  
Sensitivity Coefficients ◽  
Sensitivity Distribution ◽  
Design Variables ◽  
Forced Vibration Analysis

The proposed algorithm permits one to determine the sensitivity coefficients of natural frequencies and dynamic displacements and stresses in the free- and forced vibration analysis. This algorithm is presented in a computer program with the help of finite element method (FEM). The design variables is the thickness of the blades. Usually a maximum resonance accounts more than half the damage and deterioration of machine components. The analysis of dynamic stress sensitivity distribution for this resonance permits us to control for both the endurance of machines and their components based on the thickness. In this study the sensitivity coefficients for both free vibration, dynamic resonances are investigated by acceleration and braking the regimes.

A time-varying reliability-based robust design method considering overall efficiency of axial piston pump

2021 ◽  
pp. 1748006X2110661
Author(s):  
Zunling Du ◽  
Yimin Zhang
Keyword(s):  
Energy Conversion ◽  
Robust Design ◽  
Design Method ◽  
Design Stage ◽  
Structure Parameters ◽  
Time Varying ◽  
Design Variables ◽  
Reliability Method ◽  
Overall Efficiency ◽  
Axial Piston

Axial piston pumps (APPs) are the core energy conversion components in a hydraulic transmission system. Energy conversion efficiency is critically important for the performance and energy-saving of the pumps. In this paper, a time-varying reliability design method for the overall efficiency of APPs was established. The theoretical and practical instantaneous torque and flow rate of the whole APP were derived through comprehensive analysis of a single piston-slipper group. Moreover, as a case study, the developed model for the instantaneous overall efficiency was verified with a PPV103-10 pump from HYDAC. The time-variation of reliability for the pump was revealed by a fourth-order moment technique considering the randomness of working conditions and structure parameters, and the proposed reliability method was validated by Monte Carlo simulation. The effects of the mean values and variance sensitivity of random variables on the overall efficiency reliability were analyzed. Furthermore, the optimized time point and design variables were selected. The optimal structure parameters were obtained to meet the reliability requirement and the sensitivity of design variables was significantly reduced through the reliability-based robust design. The proposed method provides a theoretical basis for designers to improve the overall efficiency of APPs in the design stage.

Robust Parameter Design of the Precision Injection Molding Process

1994 ◽  
Author(s):  
Sornkrit Leartcheongchowasak ◽  
Merwan Mehta ◽  
Hamid Al-Kadi ◽  
Keith Sequeira ◽  
Brian Snow ◽  
...  
Keyword(s):  
Injection Molding ◽  
Taguchi Methods ◽  
Injection Molding Process ◽  
Robust Parameter Design ◽  
Molding Process ◽  
Product Lines ◽  
Molded Parts ◽  
Robust Parameter ◽  
Independent Process ◽  
The Right

Abstract The most important problem, causing defective parts, in the injection molding process, is nonuniform shrinkage of molded parts. This leads to an iterative trial-and-error cycles of modification of mold cavity and core to arrive at the right dimensional size required which can occasionally to complete retooling. For this process, there are many factors that can be thrown out of control. Using the traditional scientific approach, engineers have longed to understand the mechanics of the process to control it, with limited success. In this paper, a design of experiments setup, using the Taguchi Methods, was done to reduce the nonuniform shrinkage. The company where the experiment was carried out is a precision parts molder for their own product lines. By using the internal experts from the company, a list of independent process parameters with no interactions which were thought the most responsible for dimensional size were listed. As there were 13 such parameters, it was decided to use the L27 orthogonal array. The optimum value that the company experts thought would produce the right part were used as the settings for the initial experiment. The 27 experiments were then performed, allowing sufficient time to let the machine stabilized between the experiments. The S/N ratio calculation for 27 experiments was explained. Next the calculations for the percentage that each parameter contributes to the dimension was determined. Finally, a confirmation experiment was performed to verify the results.

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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