DOIONLINE

DOIONLINE NO - IJAECS-IRAJ-DOIONLINE-3543

Publish In
International Journal of Advances in Electronics and Computer Science-IJAECS
Journal Home
Volume Issue
Issue
Volume-2,Issue-12  ( Dec, 2015 )
Paper Title
Development Of Statistical Simulation And Robust Parameter Design Optimization For A D-Grade Explosion-Proof Junction Box
Author Name
Gyuhyo Choi, Tuan-Ho Le, Sungmin Park, Moo-Yeon Lee, Yonghee Lee, Sittichai Kaewkuekool, Sangmunshin
Affilition
Department of Industrial & Management Systems Engineering, Dong-A University, Busan, 604-714, Republic of Korea Department of Mechanical Engineering, Dong-A University, Busan 604-714, Republic of Korea Co-won Co. Ltd, Busan 600-814, Republic of Korea Department of Production Technology Education, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand
Pages
138-142
Abstract
The D-grade explosion-proof junction box is designed to withstand the pressure of explosion. Most of companies have focused on the development of high-value explosion-proof junction to improve the safety by considering the relationship between different explosion prevention components and safety of D-grade explosion-proof junction box. As the thickness of junction box increases, the safety will be improved. However, the manufacturing costs of junction box will increase numerously. Therefore, the primary objective of this paper is to identify the optimal settings for D-grade explosion-proof junction box structure with the high safety and low manufacturing costs. First of all, the information of sizes and the related stress and mass of junction box is conducted based on the proposed structure interpreting simulation and design of experiment (DoE). Then, the response surface methodology (RSM) is used to estimate the functional relationship between input factors and associated output responses. Finally, the optimal settings of sizes of junction box are obtained by using the weighted sum model for multi-objective optimization problem. Index Terms- D-grade explosion-proof junction box, robust parameter design, structure interpreting simulation, design of experiment, estimation, optimization.
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