MULTIDISCIPLINARY ANALYSIS AND OPTIMIZATION

Design Optimization 

Multidisciplinary Analysis and Optimization (MDO), often referred to as Multidisciplinary Design Analysis and Optimization (MDAO), is an engineering methodology that is used to solve complex engineering design issues.

Through the use of new algorithms available for optimization and metamodel creation within an MDO framework, design engineers can tackle large-scale coupled engineering problems. MDO involves a complex engineering system being decomposed into a series of smaller coupled subsystems each of which is analyzed concurrently using a different discipline.

Amongst the disciplines most commonly used in a multidisciplinary analysis and optimization model we can distinguish:

Statistics and design of experiments

Design of Experiments (DoE) provides a systematic approach both for real and virtual experimentation of campaign designs. This approach has obsoleted the more traditional approach of changing one factor  ...

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Multi-objective optimization

The prevalence of complex engineered systems has resulted in multi-objective optimization playing a very significant role in engineering. A multi-objective approach to optimization allows solutions to be found to real-world problems ...

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Metamodels and calibration

The use of mathematical and statistical tools to approximate, calibrate and simulate complex real world systems is widely applied in many fields. Interpolation and regression methodologies are now commonly used  ...

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Process integration

Process integration can be described as a set of methods and tools for the effective management of the entire design process, often, but not necessarily, orienting it to the optimum solution. This approach is  ...

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Uncertainty quantification

The importance of controlling variability is well recognized in disciplines such as financial risk management. Recently, robust optimization techniques have started to gain attention within the engineering and scientific communities ...

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Business analytics

The advent of mass data storage systems and increased computing power has allowed companies to embrace data-driven decision making through business analytics, which provides an insight into a   ...

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Interest in the integration of these disciplines is rapidly growing within industries that need to employ a systematic and robust approach to product design. In particular, multidisciplinary design optimization has been growing steadily in these past few years fuelled mainly by a quantum leap in the accuracy of the numerical algorithms used and by the continuous increase in distributed computing power needed for large scale simultaneous numerical simulation. Also, new visualization tools provide a simple method for selecting the best design options in a coherent and efficient way, giving engineers the ultimate set of tools to help them achieve a truly integrated design process through the entire production chain.