Robust and Reliability Based Optimization using VisualDOC-VeroSOLVE Interface Dipankar Ghosh, Ph.D. Vladimir Balabanov, Ph.D. Vanderplaats Research & Development, Inc. 1767 S. 8th Street Colorado Springs, CO 80906 Ph. (719) 473-4611 Copyright VR&D 2003 www. vrand.com

Outline Business Challenges What is VisualDOC? What is VeroSOLVE? Robust Design/Reliability based optimization What is VisualDOC? Main features What is VeroSOLVE? What is VisualDOC-VeroSOLVE Interface? Performing robust design/Reliability based optimization Example Conclusion / Questions

Business Challenges How to be Successful, and stay successful over the long run Two important strategies Product quality Increased productivity How to implement these strategies Use innovative design methods/tools during the whole product cycle management (PLM) Address key design requirements early in the lifecycle Use Robust design/Reliability based optimization to improve quality

Robust Design Numerical Optimization Probabilistic Design allows us to make best usage of the resources while satisfying certain deterministic targets; uncertainties are not addressed Probabilistic Design Addresses uncertainties through the usage of random variables Robust Design Approach Numerical optimization and probabilistic design methods should be combined to best utilize the available resources while addressing the uncertainty issues, and thus create quality (robust) designs.

Robust Design Robust design is an extension of deterministic numerical optimization Noise factors - uncontrollable factors The environmental parameters such as humidity levels, operating temperatures, raw materials, product aging, etc. Control factors geometric parameters, materials, design configurations, manufacturing process etc. Find the appropriate levels of the controlled parameters such that the final design is insensitive (or robust) to changes in a set of noise factors.

What is VisualDOC? Graphics Based Design Optimization Software General Optimization (Gradient & Non-Gradient) Design Of Experiments Response Surface Optimization Allows User to Interface Optimization Tools with Almost Any Analysis (or Physical Experiment) Modules Available as APIs For Easy Integration with other Control Programs

VisualDOC

VisualScript

Probabilistic analysis software What is VeroSOLVE? Probabilistic analysis software Probability/Reliability analysis Inverse probability analysis PDF/CDF analysis A number of probability methods Graphically link VeroSOLVE with external analysis program Synthetic functions (like in VisualDOC)

What is VeroSOLVE?

VisualDOC-VeroSOLVE Interface Use VeroSOLVE software as analysis tool inside the VisualDOC software It allows to access the majority of VeroSOLVE probabilistic analysis capabilities Input Parameters VisualDOC Probabilistic Code Analysis Code(s) Output Parameters VisualScript

VisualDOC-VeroSOLVE Interface What can we do with this interface? Reliability based optimization System probability of failure and probability of failure for responses are used as objective and constraints Robust Design To reduce the standard deviation of certain responses Combination of reliability and robust design

VisualDOC-VeroSOLVE Interface Design Variables (Control Factors): i=1,n Random Variables (Noise Factors): j=1,m VeroSOLVE Optimization loop Probabilistic loop VisualDOC qDirect Optimization qResponse Surface Optimization Determine: μ and σ for responses of interest. MaxMin

VisualDOC-VeroSOLVE Interface VeroSOLVE users: Can automatically export data into VisualDOC Setting up optimization parameters in VisualDOC is an intuitive process VisualDOC users: Will find that defining variables, responses, and probability analysis parameters in VeroSOLVE is an easy task

VisualDOC-VeroSOLVE Interface Steps Setup a probability analysis problem in VeroSOLVE Import the problem definition from VeroSOLVE into VisualDOC Setup optimization parameters in VisualDOC Specify VeroSOLVE as an analysis for VisualDOC Run optimization

VisualDOC-VeroSOLVE Interface Functionality All VisualDOC functionality is available gradient-based optimization methods response surface optimization non-gradient optimization design of experiments Some restrictions apply to VeroSOLVE problem aspects that can be exported into VisualDOC e.g., probability analysis only

Example: Hydraulic Piston Design Design Variables: Piston position: X1, X2, X3 Piston diameter: D All variables have constant standard deviations

Example: Hydraulic Piston Design Constraints: Maximum bending moment of lifting beam Force equilibrium Pivot position Support position

Example: Hydraulic Piston Design Deterministic Optimization: Minimize the volume of oil required to lift a specified load from 0 to 45 degrees Robust Optimization: Minimize the standard deviation of the oil volume Additional constraint on the maximum volume of oil required to lift a specified load from 0 to 45 degrees

Example: Hydraulic Piston Design Results initial deterministic robust design optimum optimum X1 50.0 48.5 59.4 X2 25.0 29.1 37.8 X3 25.0 60.1 60.0 D 5.0 6.3 6.0 V (volume of oil) 355.3 1087.7 1099.1 standard deviation of V 18.9 47.6 41.6 Initial design had a severe violation of constraints Robust optimum vs. deterministic optimum: 12.6 % reduction in the standard deviation of objective 1 % increase in the value of the objective function

Summary/Conclusions Powerful VisualDOC/VeroSOLVE easy-to-use interface is created Interface expands the functionality of both software systems Allows solving reliability and robust optimization problems

Thank you!