Advanced numerical prototyping methods in modern engineering applications - Optimisation for micro-electronic package reliability

Journal article (2007)

Authors

A Wymyslowski Dynamics of Micro and Nano Systems - Mechanical, Maritime and Materials Engineering
W.D. van Driel Dynamics of Micro and Nano Systems - Mechanical, Maritime and Materials Engineering
J van de Peer External organisation
N Tzannetakis External organisation
Guo Qi Zhang Dynamics of Micro and Nano Systems - Mechanical, Maritime and Materials Engineering
Research Group
Dynamics of Micro and Nano Systems (Mechanical, Maritime and Materials Engineering) (TU Delft)
More Info
expand_more

Published Date

2007

Language

Undefined/Unknown

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical, Maritime and Materials Engineering

Department

Precision and Microsystems Engineering

Research Group

Dynamics of Micro and Nano Systems

Abstract

Numerical prototyping methods based on numerical simulations and optimisation technologies are nowadays a key success factor for cost effectively and timely development and manufacturing of competitive products and processes. The typical numerical prototyping procedures are based on a sequence of numerical simulations and/or experiments done in an iterative form in order to achieve (sub-)optimal designs. The `Design Of Experiments¿ are usually selected according to the knowledge and experience of an engineer and/or defined according to certain numerical methods. The current paper describes our research and results of advanced numerical prototyping, specially focused on a novel `Design Of Experiment¿ approach and a novel `Response Surface Modelling¿ approach. These novel approaches are applied to an example in which a micro-electronic package is optimised to minimize the stress levels during processing and manufacturing of this component. It is shown that our novel approach leads to a substantial reduction of numerical experiments to obtain a certain accuracy of the response surface models. As such, the optimisation process is shortened and can be used to faster optimise the performance of products and/or process prior to major physical prototyping and manufacturing investments.