Robust Product Design Optimization Method Using Hierarchical Representations of Characteristics

Author(s):  
Masataka Yoshimura ◽  
Koichi Sasaki ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki

Product design optimizations usually require the optimization of not only all performance characteristics, but also the robustness of certain performance characteristics. Obtaining optimum design solutions is far from easy, since this requires evaluations of numerous related characteristics that usually have complicated and conflicting interrelationships. Some of these characteristics can include variations of one type or another, such as manufacturing process variations, variations pertaining to the environments where the product is used, variations in how long-term use affects certain product characteristics, and so on. The difficulty of obtaining optimum design solutions is thus compounded by the need to carry out specific optimizations that provide sufficient robustness to safely accommodate anticipated ranges of variations. This paper expands the hierarchical multiobjective optimization method based on simplification and decomposition of characteristics so that optimizations can be concurrently conducted for both performance characteristics and maximization of robustness against characteristic variances. A principal cause of variations in performance characteristics is variations in the contact conditions of joints, and the utility of the proposed robust product design optimization method is demonstrated by applying it to machine-tool models that include joints.

Author(s):  
Masataka Yoshimura ◽  
Masahiko Taniguchi ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki

This paper proposes a design optimization method for machine products that is based on the decomposition of performance characteristics, or alternatively, extraction of simpler characteristics, to accommodate the specific features or difficulties of a particular design problem. The optimization problem is expressed using hierarchical constructions of the decomposed and extracted characteristics and the optimizations are sequentially repeated, starting with groups of characteristics having conflicting characteristics at the lowest hierarchical level and proceeding to higher levels. The proposed method not only effectively enables achieving optimum design solutions, but also facilitates deeper insight into the design optimization results, and aids obtaining ideas for breakthroughs in the optimum solutions. An applied example is given to demonstrate the effectiveness of the proposed method.


2013 ◽  
Vol 41 (3) ◽  
Author(s):  
Masataka Yoshimura ◽  
Masaki Sato ◽  
Tomoyuki Miyashita ◽  
Hiroshi Yamakawa

2005 ◽  
Vol 128 (4) ◽  
pp. 701-709 ◽  
Author(s):  
Masataka Yoshimura ◽  
Masahiko Taniguchi ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki

This paper proposes a machine product design optimization method based on the decomposition of performance characteristics, or alternatively, extraction of simpler characteristics, that is especially responsive to the detailed features or difficulties presented by specific design problems. The optimization problems examined here are expressed using hierarchical constructions of the decomposed and extracted characteristics and the optimizations are sequentially repeated, starting with groups of characteristics having conflicting characteristics at the lowest hierarchical level and proceeding to higher levels. The proposed method not only effectively provides optimum design solutions, but also facilitates deeper insight into the design optimization results, so that ideas for optimum solution breakthroughs are more easily obtained. An applied example is given to demonstrate the effectiveness of the proposed method.


Author(s):  
Masataka Yoshimura ◽  
Masaki Satou ◽  
Tomoyuki Miyashita ◽  
Hiroshi Yamakawa

Author(s):  
Masataka Yoshimura

This paper proposes fundamental concepts for goal-defined product designs, and practical methodologies for achieving optimal designs based these concepts. Also emphasized are the functions and significance of Pareto optimum solution sets in multi-objective optimizations during the execution of the proposed methodologies. Three main concepts for product design optimization are presented. First, the goal of the product design optimization is specified to obtain the best harmony of related (and often conflicting) characteristics, where Pareto optimum solution sets represent this harmony and more preferable degrees of harmony cause an increase in social profit. Second, to obtain design solutions that maximize the desired harmony, deeper level characteristics in the design optimization problem are derived based on simplification or decomposition of the usual surface level characteristics, and optimizations are initiated from these deeper levels where the most important and influential aspects of the design problems are easiest to recognize. The third concept entails the use of collaboration with specialist experts concerning the product characteristics, focusing on Pareto optimum solution sets obtained in deeper level optimizations, so that these experts can facilitate the development of more preferable results based on their own ideas and knowledge. The interrelationships between the second and third concepts are described and used to obtain globally optimal design solutions that have the highest degree of harmony for the required product design objectives. The proposed concepts and methodologies for product design optimizations are demonstrated using certain designs for articulated robots.


2012 ◽  
Vol 215-216 ◽  
pp. 592-596
Author(s):  
Li Gao ◽  
Rong Rong Wang

In order to deal with complex product design optimization problems with both discrete and continuous variables, mix-variable collaborative design optimization algorithm is put forward based on collaborative optimization, which is an efficient way to solve mix-variable design optimization problems. On the rule of “divide and rule”, the algorithm decouples the problem into some relatively simple subsystems. Then by using collaborative mechanism, the optimal solution is obtained. Finally, the result of a case shows the feasibility and effectiveness of the new algorithm.


Author(s):  
Myung-Jin Choi ◽  
Min-Geun Kim ◽  
Seonho Cho

We developed a shape-design optimization method for the thermo-elastoplasticity problems that are applicable to the welding or thermal deformation of hull structures. The point is to determine the shape-design parameters such that the deformed shape after welding fits very well to a desired design. The geometric parameters of curved surfaces are selected as the design parameters. The shell finite elements, forward finite difference sensitivity, modified method of feasible direction algorithm and a programming language ANSYS Parametric Design Language in the established code ANSYS are employed in the shape optimization. The objective function is the weighted summation of differences between the deformed and the target geometries. The proposed method is effective even though new design variables are added to the design space during the optimization process since the multiple steps of design optimization are used during the whole optimization process. To obtain the better optimal design, the weights are determined for the next design optimization, based on the previous optimal results. Numerical examples demonstrate that the localized severe deviations from the target design are effectively prevented in the optimal design.


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