https://homepages.fhv.at/hgb/New-Papers/CMAME07_BS07b.pdf

Robust Optimization - A Comprehensive Survey

Robust design has been developed with the expectation that an insensitive design can be obtained. That is, a product designed by robust design should be insensitive to external noises or tolerances. An insensitive design has more probability to obtain a target value, although there are uncertain noises. Theories of robust design have been developed by adopting the theories of other fields. Based on the theories, robust design can be classified into three methods: 1) the Taguchi method, 2) robust optimization, and 3) robust design with the axiomatic approach. Each method is reviewed and investigated. The methods are examined from a theoretical viewpoint and are discussed from an application viewpoint. The advantages and drawbacks of each method are discussed, and future directions for development are proposed.

Robust Design: An Overview

Computational methods in optimization considering uncertainties – An overview

Review of uncertainty-based multidisciplinary design optimization methods for aerospace vehicles

http://michael.friswell.com/PDF_Files/J108.pdf

A review of robust optimal design and its application in dynamics

Robust optimization considering tolerances of design variables

The current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies but it may produce uncontrollable uncertainties. To increase manageability of such uncertainties, the Taguchi method, reliability-based optimization and robust optimization are commonly being used. The main functional requirement of a mechanical system is to obtain the target performance with maximum robustness. In this research, a design procedure for global robust optimization is developed using kriging and global optimization approaches. Robustness is determined by kriging model to reduce a number of real functional calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust optimum of a surrogate model. As the postprocess, the global optimum is further refined by applying the first-order second-moment approximation method. Mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

A Global Robust Optimization Using Kriging Based Approximation Model

Engineering optimization has been developed for the economic design of engineering systems. The conventional optimum is determined without considering noise factors. Thus, applications to practical problems may be limited. Within current design practice, noises tend to be allowed for by specification of closer tolerances, or the use of safety factors. However, these approaches may be economically infeasible. Thus, the inclusion of design-variable noises is required for practical design in optimization. A method is developed to find robust solutions for unconstrained optimization problems. The method is applied to problems with discrete variables. The orthogonal array based on the Taguchi concept is utilized to arrange the discrete variables. Through several examples, it is verified that the solutions from the suggested method are more insensitive to noise than the conventional optimum within the range of variations for design variables.

Robust design for unconstrained optimization problems using the Taguchi method

An optimization algorithm using orthogonal arrays in discrete design space for structures

Weight reduction for an automobile body is sought to achieve fuel efficiency and energy conservation. Recently, the UltraLight Steel Auto Body (ULSAB) concept is suggested using a few methods. ULSAB pursues a lightweight automotive with steel structure. Tailor welded blank (TWB) is one of the ULSAB methods and TWB can be utilized for an automobile door. Optimization technology is applied to the inner panel of a door which is made by TWB. A design process is appropriately defined for the inner panel. The design starts from an existing component. At first, the inner reinforcements are removed to use TWB technology. In the conceptual design stage, topology optimization is conducted to find the distribution of the variable thickness. The number of parts and the welding lines are determined from the topology design. In the detailed design process, size optimization is carried out to find thickness while the stiffness constraints are satisfied. Size optimization is performed based on the welding lines determined from topology optimization. The final parting lines are tuned by shape optimization. The results from size optimization are considered constant in shape optimization. A commercial optimization software GENESIS is utilized for the optimization processes.

Kwon-Hee Lee

Papers

Robust optimization considering tolerances of design variables

A Global Robust Optimization Using Kriging Based Approximation Model

Robust design for unconstrained optimization problems using the Taguchi method

An optimization algorithm using orthogonal arrays in discrete design space for structures

Automotive door design with the ULSAB concept. using structural optimization