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Easy Design
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EasyDesign provide design solution from simulation and test results to answer the question ¡°how to make best product?¡± or ¡°will it pass the test?¡± before you even have prototype.

EasyDesign is an efficient design optimization tool, which integrates advanced DOE, progressive meta-model and numerical optimization in the context of automated design optimization process. It requires nearly minimum sampling points for constructing the initial meta-models and improves the fidelity of meta-models by adding new design sequentially. Also, in order to elevate the convergence, meta-model methods are switched automatically during optimization process. Thus, the proposed approach is called as the progressive meta-model method to be distinguished from the conventional meta-model techniques.

EasyDesign can overcome the numerical singularity for insufficient data when constructing meta-model. Also, Even though the analysis is failed during optimization process, it can overcome the failure by automatic compensation. Furthermore, somewhat difficult selection of optimization techniques is automatically tuned. Thus, the user just defines one's design problem such as objective and constraints.

MODULES
Design Optimization
DFSS/Robust Design Optimization
Design Study
KEY FEATURES
  • Progressive Meta-Model methods
Progressive Meta-Model methods add only one point that is the estimated optimum in the previous iteration. In order to guarantee the accuracy of meta-model, it changes the meta-model type automatically and employs the numerical techniques to overcome the numerical singularity due to lack of fits. Also, in order to elevate the convergence of optimization process, it tunes move limit and optimization strategy automatically. Hence, suppose that the number of sample points is 'm' and the iteration of optimization process is 'k'. Then, EasyDesign requires 'k+m' number of analyses. more detail
  • Adaptive Six-Sigma Optimization
EasyDesign can solve the robust design optimization problem with 6-sigma inequality constraints. When the 6-sigma terms are added to the inequality constraints, the feasible region will shrink. Hence, the possibility of violation is nearly '0' when the design satisfies 6-sigma constraints. Most of engineering design problems, however, is very tough design problems. Thus, the added 6-sigma terms can make non-feasible region, which occurs very often. EasyDesign checks the feasibility before every solving 6-sigma optimization problems. Then, it automatically relaxes only the critical 6-sigma terms as possible as. It is called as 'Adaptive 6-Sigma Optimization¡¯, of which concept is explained graphically in below figure.
< Relaxed effect by using adaptive k-sigma optimization >
INDUSTRY USES
  • Aerospace & Defense: Wing and fuselage structures, Landing gears, Helicopter blade design, Doors, Satellite solar panels, Barrel, Ammunition
  • Automotive: Vehicle and component weight reduction, Vibration modes separation, Maximized energy absorption for crash safety, Optimized bushing rates for multiple handling maneuvers and ride profiles, Suspension design optimization
  • Consumer Products: Sporting goods, Packaging, Bicycle frames
  • Energy: Wind turbine blades, Offshore structures like thick-walled tubular, subsea pipes, tanks
  • Government / Civil: Concrete structures, Bridges, Barriers
  • Medical: Stents, Hospital equipment (e.g. bed, wheel chairs), Surgical devices
Contact the EasyDesign Sales Team and get a quote
Kindly contact EasyDesign sales team if you would like to find out more about what we can offer you. Feel free to pose any technical or commercial questions or make any inquiry.
ido@idopt.co.kr, 82-31-622-3690