Hierarchical Arrangement of Characteristics in Product Design Optimization

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.

[1]  Panos Y. Papalambros,et al.  A Hypergraph Framework for Optimal Model-Based Decomposition of Design Problems , 1997, Comput. Optim. Appl..

[2]  Christina Bloebaum,et al.  A genetic tool for optimal design sequencing in complex engineering systems , 1996 .

[3]  John E. Renaud,et al.  Multiobjective Collaborative Optimization , 1997 .

[4]  Masataka Yoshimura,et al.  Smart Optimization of Machine Systems Using Hierarchical Genotype Representations , 2002 .

[5]  Ilan Kroo,et al.  Collaborative Approach to Launch Vehicle Design , 1997 .

[6]  D. V. Steward,et al.  The design structure system: A method for managing the design of complex systems , 1981, IEEE Transactions on Engineering Management.

[7]  Kazuhiro Saitou,et al.  Decomposition-based assembly synthesis for in-process dimensional adjustability , 2003 .

[8]  A. Kusiak,et al.  Efficient solving of the group technology problem , 1987 .

[9]  JiGuan G. Lin.  Analysis and Enhancement of Collaborative Optimization for Multidisciplinary Design , 2004 .

[10]  Christina Bloebaum,et al.  Ordering design tasks based on coupling strengths , 1994 .

[11]  J. Sobieszczanski-Sobieski,et al.  A linear decomposition method for large optimization problems. Blueprint for development , 1982 .

[12]  Masataka Yoshimura,et al.  Design Optimization of Machine-Tool Structures Considering Manufacturing Cost, Accuracy, and Productivity , 1984 .

[13]  Juhani Koski,et al.  Multicriteria Design Optimization , 1990 .

[14]  Panos Y. Papalambros,et al.  Analytical Target Cascading in Automotive Vehicle Design , 2001 .

[15]  Jaroslaw Sobieszczanski-Sobieski,et al.  Bilevel Integrated System Synthesis with Response Surfaces , 2000 .

[16]  Sobieszczanski Jaroslaw,et al.  Bi-Level Integrated System Synthesis (BLISS) , 1998 .

[17]  W. Stadler.  Multicriteria Optimization in Engineering and in the Sciences , 1988 .

[18]  Tao Jiang,et al.  Target Cascading in Optimal System Design , 2003, DAC 2000.

[19]  K. Izui,et al.  Hierarchical Parallel Processes of Genetic Algorithms for Design Optimization of Large-Scale Products , 2004 .

[20]  Masataka Yoshimura,et al.  Optimization of Machine System Designs Using Hierarchical Decomposition Based on Criteria Influence , 2002, DAC 2002.

[21]  J. Sobieszczanski-Sobieski,et al.  Bilevel Integrated System Synthesis for Concurrent and Distributed Processing , 2002 .

[22]  Andrew Kusiak,et al.  Decomposition of the Design Process , 1993 .

[23]  Kazuhiro Saitou,et al.  Decomposition-based assembly synthesis for maximum structural strength and modularity , 2004 .

[24]  Xiaoyu Gu,et al.  Decision-Based Collaborative Optimization , 2002 .

[25]  Kazuhiro Saitou,et al.  Decomposition-Based Assembly Synthesis for Structural Stiffness , 2003 .

[26]  G. Zoutendijk,et al.  Methods of Feasible Directions , 1962, The Mathematical Gazette.

[27]  Natalia Alexandrov,et al.  Analytical and Computational Aspects of Collaborative Optimization for Multidisciplinary Design , 2002 .