Robust Design by Matching the Design With Manufacturing Variation Patterns

1994 ◽  
Author(s):  
Jyh-Cheng Yu ◽  
Kosuke Ishii
Keyword(s):  
Robust Optimization ◽  
Robust Design ◽  
Optimization Procedure ◽  
Theoretical Development ◽  
Future Application ◽  
Design Variables ◽  
Performance Variation ◽  
Heat Treated ◽  
Variation Patterns ◽  
Manufacturing Variation

Abstract This paper deals with robust design problems in which variations on design variables have significant correlation. Manufacturing errors often affect design variables with characteristic patterns, that is, the variations are coupled. Robust optimization seeks designs with optimal and robust performance. Designers should match the design to the Manufacturing Variation Patterns (MVP) in the constrained robust optimization procedure. This study focuses on matching the variation patterns found in typical manufacturing processes. It uses quadrature experimental design to approximate the performance variation within the patterns. We redefine the robust constraint activity for designs using MVP and propose our procedure to search for the robust feasible designs. Theoretical development of manufacturing variation matching leads to our case study of heat treated shaft design with minimum dimensional distortion. The paper also outlines our future application in injection molding gear design and challenge in the identification of nonlinear correlated MVP.

Design for Robustness Based on Manufacturing Variation Patterns

1998 ◽  
Vol 120 (2) ◽  
pp. 196-202 ◽  
Author(s):  
Jyh-Cheng Yu ◽  
Kosuke Ishii
Keyword(s):  
Design Optimization ◽  
Transmission Error ◽  
Variation Pattern ◽  
Design Variables ◽  
Performance Variation ◽  
Variation Patterns ◽  
Manufacturing Errors ◽  
Dimensional Errors ◽  
Manufacturing Variation

This paper addresses interacting manufacturing errors and their impact on the design robustness and constraint activity. Manufacturing errors often affect design variables with characteristic patterns. This paper defines the Manufacturing Variation Pattern (MVP) to represent this characteristic and investigates its effects. The application of the concept of MVP to design optimization leads to an improved robust optimum. The design of molded gears with minimum transmission error illustrates the proposed scheme’s effectiveness. Our model readily accommodates correlation among dimensional errors and significantly reduces performance variation.

The Effect of Different Optimization Methods on Robustness for Robust Optimization Design

2014 ◽  
Vol 721 ◽  
pp. 464-467
Author(s):  
Tao Fu ◽  
Qin Zhong Gong ◽  
Da Zhen Wang
Keyword(s):  
Robust Optimization ◽  
Objective Function ◽  
Robust Design ◽  
Optimization Design ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Parameters ◽  
Hybrid Particle Swarm Optimization ◽  
Design Variables ◽  
Robust Optimization Design

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.

Multi-Objective Robust Design Optimization and Knowledge Mining of a Centrifugal Fan That Takes Dimensional Uncertainty Into Account

2008 ◽  
Author(s):  
Kazuyuki Sugimura ◽  
Shinkyu Jeong ◽  
Shigeru Obayashi ◽  
Takeshi Kimura
Keyword(s):  
Data Mining ◽  
Robust Optimization ◽  
Robust Design ◽  
Rough Set Theory ◽  
Optimization Techniques ◽  
Robust Design Optimization ◽  
Centrifugal Fan ◽  
Data Mining Techniques ◽  
Multi Objective ◽  
Design Variables

A new design approach named MORDE (multi-objective robust design exploration), in which multi-objective robust optimization techniques and data mining techniques are combined, is proposed in this paper. We first developed a widely applicable design framework for multi-objective robust optimization. In this framework, probabilistic representation of design variables are introduced and Kriging models are used to approximate relations between design variables with uncertainty and multiple design objectives. A multi-objective genetic algorithm optimizes the mean and standard deviation of the responses. We then applied the framework to the real-world design problem of a centrifugal fan used in a washer-dryer. Taking dimensional uncertainty into account, we optimized the means and standard deviations of the resulting distributions of fan efficiency and turbulent noise level. Steady Reynolds-averaged Navier Stokes simulations were used to build Kriging models that approximate these objective functions. With the obtained non-dominated solutions, we demonstrated how to analyze features of solutions and select design candidates. We also attempted to acquire design knowledge by applying several data mining techniques. Self-organizing map was used to visualize and reuse the high dimensional design data. Decision tree analysis and rough set theory were used to extract design rules to improve the product’s performance. We also discussed differences in types of rules, which were extracted by both methods.

Practical Robust Design Optimization Using Evolutionary Algorithms

2011 ◽  
Vol 133 (10) ◽  
Author(s):  
Amit Saha ◽  
Tapabrata Ray
Keyword(s):  
Evolutionary Algorithms ◽  
Robust Optimization ◽  
Design Optimization ◽  
Robust Design ◽  
Optimal Solution ◽  
Optimization Procedure ◽  
Computational Design ◽  
Robust Design Optimization ◽  
Function Evaluation ◽  
Engineering Design Problems

Robust design optimization (RDO) seeks to find optimal designs which are less sensitive to the uncontrollable variations that are often inherent to the design process. Studies using Evolutionary Algorithms (EAs) for RDO are not too many. In this work, we propose enhancements to an EA based robust optimization procedure with explicit function evaluation saving strategies. The proposed algorithm, IDEAR, takes into account a specified expected uncertainty in the design variables and then imposes the desired robustness criteria during the optimization process to converge to robust optimal solution(s). We pick up a number of Bi-objective engineering design problems from the standard literature and study them in the proposed robust optimization framework to demonstrate the enhanced performance. A cross-validation study is performed to analyze whether the solutions obtained are truly robust and also make some observations on how robust optimal solutions differ from the performance maximizing solutions in the design space. We perform a rigorous analysis of the key features of IDEAR to illustrate its functioning. The proposed function evaluation saving strategies are generic and their applications are worth exploring in other areas of computational design optimization.

A ROBUST OPTIMIZATION PROCEDURE WITH VARIATIONS ON DESIGN VARIABLES AND CONSTRAINTS

1995 ◽  
Vol 24 (2) ◽  
pp. 101-117 ◽  
Author(s):  
SIVAKUMAR SUNDARESAN ◽  
KOSUKE ISHII ◽  
DONALD R. HOUSER
Keyword(s):  
Robust Optimization ◽  
Optimization Procedure ◽  
Design Variables

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.

Structural Optimization of Composite Panel with Lamination Parameters and Equivalent Stiffness Laminate Method

2014 ◽  
Vol 496-500 ◽  
pp. 429-435
Author(s):  
Xiao Ping Zhong ◽  
Peng Jin
Keyword(s):  
Genetic Algorithm ◽  
Structural Optimization ◽  
Composite Structure ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Composite Panel ◽  
Analysis Tool ◽  
Equivalent Stiffness ◽  
Lamination Parameters ◽  
Design Variables

Firstly, a two-level optimization procedure for composite structure is investigated with lamination parameters as design variables and MSC.Nastran as analysis tool. The details using lamination parameters as MSC.Nastran input parameters are presented. Secondly, with a proper equivalent stiffness laminate built to substitute for the lamination parameters, a two-level optimization method based on the equivalent stiffness laminate is proposed. Compared with the lamination parameters-based method, the layer thicknesses of the equivalent stiffness laminate are adopted as continuous design variables at the first level. The corresponding lamination parameters are calculated from the optimal layer thicknesses. At the second level, genetic algorithm (GA) is applied to identify an optimal laminate configuration to target the lamination parameters obtained. The numerical example shows that the proposed method without considering constraints of lamination parameters can obtain better optimal results.

Structural Shape Optimization Wth Error Control

1994 ◽  
Author(s):  
Pierre Duysinx ◽  
WeiHong Zhang ◽  
HaiGuang Zhong ◽  
Pierre Beckers ◽  
Claude Fleury
Keyword(s):  
Shape Optimization ◽  
Computer Aided Design ◽  
Adaptive Mesh Refinement ◽  
Error Control ◽  
Optimization Procedure ◽  
Adaptive Mesh ◽  
Structural Shape ◽  
Structural Shape Optimization ◽  
Design Variables ◽  
Recent Developments

Abstract A robust and automatic shape optimization procedure is presented in this paper, which incorporates recent developments in the field of computer-aided design (CAD) of mechanical structures, such as geometric modelling, automatic selection of independent design variables, sensitivity analysis using reliable mesh perturbation schemes, error estimation and adaptive mesh refinement. A numerical example is given to show the efficiency of the procedure.

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.

scholarly journals Thermal-Structural Design of Actively-Cooled Panels Reinforced by Light-Weight Truss Cores

2013 ◽  
Author(s):  
Hongwei Song ◽  
Mingjun Li ◽  
Chenguang Huang ◽  
Xi Wang
Keyword(s):  
Heat Transfer ◽  
Structural Analysis ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Thermal Environment ◽  
Numerical Models ◽  
Lightweight Design ◽  
Optimization Procedure ◽  
Combustion Gas ◽  
Design Variables

This paper focuses on thermal-structural analysis and lightweight design of actively-cooled panels reinforced by low density lattice-framed material (LFM) truss cores. Numerical models for actively-cooled panels are built up with parametric codes to perform the coupled thermal-structural analysis, considering the internal thermal environment of convective heat transfer in the combustor and convective heat transfer in the cooling channel, and internal pressures from the combustion gas and the coolant. A preliminary comparison of the LFM truss reinforced actively-cooled panel and the non-reinforced panel demonstrates that the thermal-structural behavior is significantly improved. Then, an optimization procedure is carried out to find the lightest design while satisfying thermal deformation and plastic strain constraints, with thicknesses of face sheets and topology parameters of LFM truss as design variables. The optimization result demonstrates that, compared with the non-reinforced actively-cooled panels, weight reduction for the panel reinforced by LFM truss may reach 19.6%. We have also fabricated this type of actively-cooled panel in the laboratory level, and the specimen shows good mechanical behaviors.

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