Product Design Optimization Method Considering the Integrated Satisfaction Level

2012 ◽  
Author(s):  
Masataka Yoshimura ◽  
Masaki Satou ◽  
Tomoyuki Miyashita ◽  
Hiroshi Yamakawa
Keyword(s):  
Design Optimization ◽  
Product Design ◽  
Optimization Method ◽  
Satisfaction Level

PRODUCT DESIGN OPTIMIZATION METHOD CONSIDERING THE INTEGRATED SATISFACTION LEVEL

2013 ◽  
Vol 41 (3) ◽  
Author(s):  
Masataka Yoshimura ◽  
Masaki Sato ◽  
Tomoyuki Miyashita ◽  
Hiroshi Yamakawa
Keyword(s):  
Design Optimization ◽  
Product Design ◽  
Optimization Method ◽  
Satisfaction Level

Hierarchical Arrangement of Characteristics in Product Design Optimization Problems for Deeper Insight Into Optimized Results

2004 ◽  
Author(s):  
Masataka Yoshimura ◽  
Masahiko Taniguchi ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki
Keyword(s):  
Design Optimization ◽  
Product Design ◽  
Optimum Design ◽  
Design Problem ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Optimization Method ◽  
Hierarchical Level ◽  
Hierarchical Arrangement ◽  
Insight Into

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.

Robust Product Design Optimization Method Using Hierarchical Representations of Characteristics

2007 ◽  
Author(s):  
Masataka Yoshimura ◽  
Koichi Sasaki ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki
Keyword(s):  
Design Optimization ◽  
Product Design ◽  
Optimum Design ◽  
Process Variations ◽  
Optimization Method ◽  
Performance Characteristics ◽  
Design Solutions ◽  
Hierarchical Representations ◽  
Robust Product Design

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.

Concurrent Optimization of Product Design and Manufacturing Coping With Demand Variability

1993 ◽  
Author(s):  
Masataka Yoshimura ◽  
Atsushi Takeuchi
Keyword(s):  
Decision Making ◽  
Design Optimization ◽  
Product Design ◽  
Integrated Design ◽  
Industrial Robots ◽  
Design Decision ◽  
Satisfaction Level ◽  
Market Demand ◽  
Decision Variables ◽  
Practical Design

Abstract A user-oriented product design methodology for integrating design, manufacturing and marketing is proposed and the practical design optimization procedures are constructed and presented. First, market demand analyses are conducted by dividing users into groups based on similarities of users’ needs. The product satisfaction level of each group is formulated using the users’ satisfaction levels for product attributes. Next, in order to obtain optimum design solutions effectively in the integrated decision making processes of design, manufacturing and marketing (which include an enormous number of decision variables), multiphase procedures of design optimization are constructed according to simplicity levels of shape modelings with structural characteristics and manufacturing costs which can be evaluated. Then, practical design decision making procedures from the extraction of design alternatives through the determination of detailed decision variables are described corresponding to multiphase modeling starting with simplified models and advancing to detailed models. Here, the objective function of decision making is to maximize the satisfaction level of product user. Finally, the proposed integrated design optimization method is applied to industrial robots for demonstrating the effectiveness of the method.

Hierarchical Arrangement of Characteristics in Product Design Optimization

2005 ◽  
Vol 128 (4) ◽  
pp. 701-709 ◽  
Author(s):  
Masataka Yoshimura ◽  
Masahiko Taniguchi ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki
Keyword(s):  
Design Optimization ◽  
Product Design ◽  
Optimization Problems ◽  
Optimization Method ◽  
Hierarchical Level ◽  
Specific Design ◽  
Design Problems ◽  
Hierarchical Arrangement ◽  
Optimum Solution ◽  
Insight Into

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.

Study on Mix-Variable Collaborative Design Optimization

2012 ◽  
Vol 215-216 ◽  
pp. 592-596
Author(s):  
Li Gao ◽  
Rong Rong Wang
Keyword(s):  
Design Optimization ◽  
Product Design ◽  
Optimization Algorithm ◽  
Collaborative Design ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Collaborative Optimization ◽  
Continuous Variables ◽  
Complex Product ◽  
Divide And Rule

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.

Shape-design optimization of hull structures considering thermal deformation

2013 ◽  
Vol 228 (13) ◽  
pp. 2266-2277
Author(s):  
Myung-Jin Choi ◽  
Min-Geun Kim ◽  
Seonho Cho
Keyword(s):  
Optimal Design ◽  
Design Optimization ◽  
Thermal Deformation ◽  
Parametric Design ◽  
Optimization Method ◽  
Optimization Process ◽  
Design Parameters ◽  
Shape Design ◽  
Shape Design Optimization ◽  
Modified Method

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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