Adaptive Optimization Design of Machining Center Tool Changing Manipulator

2015 ◽  
Vol 743 ◽  
pp. 43-48
Author(s):  
K.Z. Sun ◽  
J.Y. Zhou
Keyword(s):  
Optimization Design ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Evaluation Index ◽  
Adaptive Optimization ◽  
Machining Center ◽  
Integrative Evaluation ◽  
Product Function ◽  
Comprehensive Evaluation Model ◽  
Primary Evaluation

Analysis has been made on the adaptive optimization design of machining center tool changing manipulator by the application of the quantitative analysis tools. Thus adaptive comprehensive evaluation index is proposed and the adaptive comprehensive evaluation model of product is established. On the basis of primary evaluation on various indicators such as Product function adaptability with methods of Multilevel Fuzzy Integrative Evaluation, then, the secondary comprehensive evaluation will be continued and comprehensive adaptability evaluation level of FV-1100A machining center tool changing manipulator will be gained, thus providing guides and evidence for further improvement of product design. Through presenting adaptive measuring values of all proposals in schematic design phase and the quantitate evaluation on the complexity of modifying the design.

Improved Vector Error Diffusion for Reduction of Smear Artifact in the Boundary Regions

2003 ◽  
Author(s):  
Soon-Chang Lee ◽  
Yun-Tae Kim ◽  
Yang-Ho Cho ◽  
Yeong-Ho Ha
Keyword(s):  
Error Diffusion ◽  
Vector Error

Semi-vector error diffusion for color images

1998 ◽  
Author(s):  
Zhigang Fan ◽  
Steven J. Harrington
Keyword(s):  
Color Images ◽  
Error Diffusion ◽  
Vector Error

scholarly journals An Entropy Weight-Based Lower Confidence Bounding Optimization Approach for Engineering Product Design

2020 ◽  
Vol 10 (10) ◽  
pp. 3554 ◽  
Author(s):  
Jiachang Qian ◽  
Jiaxiang Yi ◽  
Jinlan Zhang ◽  
Yuansheng Cheng ◽  
Jun Liu
Keyword(s):  
Optimization Design ◽  
Optimal Solution ◽  
Kriging Model ◽  
Optimization Approach ◽  
Adaptive Optimization ◽  
Entropy Weight ◽  
Engineering Product ◽  
Lower Confidence ◽  
Different Dimensions ◽  
Adaptive Kriging

The optimization design of engineering products involving computationally expensive simulation is usually a time-consuming or even prohibitive process. As a promising way to relieve computational burden, adaptive Kriging-based design optimization (AKBDO) methods have been widely adopted due to their excellent ability for global optimization under limited computational resource. In this paper, an entropy weight-based lower confidence bounding approach (EW-LCB) is developed to objectively make a trade-off between the global exploration and the local exploitation in the adaptive optimization process. In EW-LCB, entropy theory is used to measure the degree of the variation of the predicted value and variance of the Kriging model, respectively. Then, an entropy weight function is proposed to allocate the weights of exploration and exploitation objectively and adaptively based on the values of information entropy. Besides, an index factor is defined to avoid the sequential process falling into the local regions, which is associated with the frequencies of the current optimal solution. To demonstrate the effectiveness of the proposed EW- LCB method, several numerical examples with different dimensions and complexities and the lightweight optimization design problem of an underwater vehicle base are utilized. Results show that the proposed approach is competitive compared with state-of-the-art AKBDO methods considering accuracy, efficiency, and robustness.

Sign in / Sign up

Export Citation Format

Share Document