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.

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.

Hybrid and Adaptive Metamodel Based Global Optimization

2009 ◽  
Author(s):  
J. Gu ◽  
G. Y. Li ◽  
Z. Dong
Keyword(s):  
Global Optimization ◽  
Design Optimization ◽  
Optimization Problems ◽  
Optimization Method ◽  
Global Optimum ◽  
Superior Performance ◽  
Automatic Identification ◽  
Design Problems ◽  
Sample Data ◽  
Data Points

Metamodeling techniques are increasingly used in solving computation intensive design optimization problems today. In this work, the issue of automatic identification of appropriate metamodeling techniques in global optimization is addressed. A generic, new hybrid metamodel based global optimization method, particularly suitable for design problems involving computation intensive, black-box analyses and simulations, is introduced. The method employs three representative metamodels concurrently in the search process and selects sample data points adaptively according to the values calculated using the three metamodels to improve the accuracy of modeling. The global optimum is identified when the metamodels become reasonably accurate. The new method is tested using various benchmark global optimization problems and applied to a real industrial design optimization problem involving vehicle crash simulation, to demonstrate the superior performance of the new algorithm over existing search methods. Present limitations of the proposed method are also discussed.

Fundamental Concepts for Product Designs Based on Pareto Optimum Solutions

2011 ◽  
Author(s):  
Masataka Yoshimura
Keyword(s):  
Design Optimization ◽  
Product Design ◽  
Optimal Designs ◽  
Pareto Optimum ◽  
Design Problems ◽  
Solution Sets ◽  
Pareto Optimum Solution ◽  
Design Solutions ◽  
Articulated Robots ◽  
Optimum Solution

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.

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.

scholarly journals FEM Based Preliminary Design Optimization in Case of Large Power Transformers

2019 ◽  
Author(s):  
Tamás Orosz ◽  
David Pánek ◽  
Pavel Karban
Keyword(s):  
Design Optimization ◽  
Design Process ◽  
Optimization Problems ◽  
Optimization Method ◽  
Power Transformers ◽  
Design Stage ◽  
Preliminary Design ◽  
Large Power ◽  
Custom Made ◽  
Transformer Design

Since large power transformers are custom-made, and their design process is a labor-intensive task, their design process is split into different parts. In tendering, the price calculation is based on the preliminary design of the transformer. Due to the complexity of this task, it belongs to the most general branch of discrete, non-linear mathematical optimization problems. Most of the published algorithms are using a copper filling factor based winding model to calculate the main dimensions of the transformer during this first, preliminary design step. Therefore, these cost optimization methods are not considering the detailed winding layout and the conductor dimensions. However, the knowledge of the exact conductor dimensions is essential to calculate the thermal behaviour of the windings and make a more accurate stray loss calculation. The paper presents a novel, evolutionary algorithm-based transformer optimization method which can determine the optimal conductor shape for the windings during this examined preliminary design stage. The accuracy of the presented FEM method was tested on an existing transformer design. Then the results of the proposed optimization method have been compared with a validated transformer design optimization algorithm.

scholarly journals Application of evolutionary algorithms to optimize cooling channels

2019 ◽  
Vol 10 ◽  
pp. A4 ◽  
Author(s):  
Narasimha R. Nagaiah ◽  
Christopher D. Geiger
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Simulation Method ◽  
Optimization Method ◽  
Composite Function ◽  
Cooling Channels ◽  
Design Variables ◽  
Evolutionary Simulation ◽  
Conventional Methods ◽  
Cooling Passage

The design and development is a complex, repetitive, and more often difficult task, as design tasks comprising of restraining and conflicting relationships among design variables with more than one design objectives. Conventional methods for solving more than one objective optimization problems is to build one composite function by scalarizing the multiple objective functions into a single objective function with one solution. But, the disadvantages of conventional methods inspired scientists and engineers to look for different methods that result in more than one design solutions, also known as Pareto optimal solutions instead of one single solution. Furthermore, these methods not only involved in the optimization of more than one objectives concurrently but also optimize the objectives which are conflicting in nature, where optimizing one or more objective affects the outcome of other objectives negatively. This study demonstrates a nature-based and bio-inspired evolutionary simulation method that addresses the disadvantages of current methods in the application of design optimization. As an example, in this research, we chose to optimize the periodic segment of the cooling passage of an industrial gas turbine blade comprising of ribs (also known as turbulators) to enhance the cooling effectiveness. The outlined design optimization method provides a set of tradeoff designs to pick from depending on designer requirements.

Genetic Algorithms for Optimization of Building Envelopes and the Design and Control of HVAC Systems

2003 ◽  
Vol 125 (3) ◽  
pp. 343-351 ◽  
Author(s):  
L. G. Caldas ◽  
L. K. Norford
Keyword(s):  
Genetic Algorithms ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimization Method ◽  
Hvac Systems ◽  
Design Problems ◽  
Building Walls ◽  
Building Form ◽  
And Control ◽  
Future Work

Many design problems related to buildings involve minimizing capital and operating costs while providing acceptable service. Genetic algorithms (GAs) are an optimization method that has been applied to these problems. GAs are easily configured, an advantage that often compensates for a sacrifice in performance relative to optimization methods selected specifically for a given problem, and have been shown to give solutions where other methods cannot. This paper reviews the basics of GAs, emphasizing multi-objective optimization problems. It then presents several applications, including determining the size and placement of windows and the composition of building walls, the generation of building form, and the design and operation of HVAC systems. Future work is identified, notably interfaces between a GA and both simulation and CAD programs.

scholarly journals New multiobjective optimization algorithm using NBI-SASP approaches for mechanical structural problems

2022 ◽  
Vol 13 ◽  
pp. 4
Author(s):  
Samira El Moumen ◽  
Siham Ouhimmou
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Pareto Frontier ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Design Problems ◽  
Multi Objective ◽  
Structural Problems ◽  
Engineering Design Problems ◽  
Set Of Points

Various engineering design problems are formulated as constrained multi-objective optimization problems. One of the relevant and popular methods that deals with these problems is the weighted method. However, the major inconvenience with its application is that it does not yield a well distributed set. In this study, the use of the Normal Boundary Intersection approach (NBI) is proposed, which is effective in obtaining an evenly distributed set of points in the Pareto set. Given an evenly distributed set of weights, it can be strictly shown that this approach is absolutely independent of the relative scales of the functions. Moreover, in order to ensure the convergence to the Global Pareto frontier, NBI approach has to be aligned with a global optimization method. Thus, the following paper suggests NBI-Simulated Annealing Simultaneous Perturbation method (NBI-SASP) as a new method for multiobjective optimization problems. The study shall test also the applicability of the NBI-SASP approach using different engineering multi-objective optimization problems and the findings shall be compared to a method of reference (NSGA). Results clearly demonstrate that the suggested method is more efficient when it comes to search ability and it provides a well distributed global Pareto Front.

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.

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
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