Online training course:

Automatic Optimization for Efficient Product and Process Development

Recognise next level design methodologies utilizing simulation results to explore the whole design space.

Some people consider that optimization is part of an engineer’s basic job. In general, no one will accept a project if they think it can be improved in any way. However, usually there are restrictions such as time and cost not to mention the number of technical restrictions.

Computers and software came to the rescue such that we now have software that cleverly controls other software to run process simulations and automatically repeat them in order to improve the design or the concept that we have defined. This requires smart algorithms that determine trends and make the best decisions to come up with an optimal design.

In this way the sequence of simulations in the design process is configured by the engineer, who then defines an optimization strategy for the computer to do the work using software algorithms. This saves time and effort, but there are issues and possibly time is wasted in some cases.

The course provides an extensive overview of process simulation and optimization methods so that engineers can enhance their working methods by defining optimization strategies be they single- or multi-objective, single- or multi-disciplinary using determinate, continuous or statistical variables and including restrictions and decision making. Generic algorithms are discussed, advice is provided and problematic issues are highlighted to guide engineers in the creation of successful, efficient optimization strategies.

Interaction is encouraged throughout the course. Questions and class participation are encouraged, as this is one of the key aspects of making this a unique and positive experience for each attendee.

Who should attend

Engineers who are interested in the next level of design methodologies utilizing simulation results to explore the whole design space and improve designs by using appropriate optimization tools and methods.

Course Program

This course combines information, examples, case-studies and time for open discussion of the concepts presented:

• Design cycles
• Optimization within a design cycle
• Simulation Process Integration
• Design windows
• Optimization
• Basics
• Single- and Multi-objective optimization
• Basic methodologies
• Topology Optimization
• Concepts, methods, and examples
• Design of Experiments (DoE)
• Concepts, uses, guidance
• Typical algorithms

• Parameter Optimization
• Concepts and guidance
• Methods (gradient, GA, evolution, others)
• Decision making tools
• Response Surface/Meta-model methods
• Methods and algorithms
• Real-life/Experimental information
• Robust design methodologies
• Sensitivity
• Examples in many sectors are distributed throughout the course