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 situations.

Bu using advanced algorithms available for optimization and metamodel creation within an MDO framework, engineers can address large-scale combined engineering problems. MDO concerns a complete engineering system being broken down into a series of coupled subsystems each of which is analyzed concurrently using a different discipline.

The disciplines most commonly used in a multidisciplinary analysis and optimization model are:

Statistics and design of experiments

Design of Experiments (DoE) is a systematic approach both for real and virtual experimentation of designs. This approach has revolutionized the older traditional approach of altering one factor  ...

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Multi-objective optimization

The increase of complex engineered systems has resulted in multi-objective optimization having a significant role in engineering. A multi-objective approach to optimization enables solutions to be found to real-world problems ...

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Metamodels and calibration

Mathematical and statistical tools can be used to approximate, calibrate and simulate complex real world systems and is widely applicable to 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.