Lukasz Dowhan

Parametric Approach to Numerical Design for Optimization of Stacked Packages

The main aim for development of smaller packages is mainly due to ongoing development of portable communications devices. Thin silicon die improves device performance and reliability. Novel technological processes allow for the thinning of wafers to 2 mils without residual damage to the backside silicon or topside circuitry. Stacked packages reduce packaging cost and cycle-times. Wafers are stacked to form 3D multi-chip packages. On the other hand the electronic market requires novel and efficient designing tools as numerical design for optimization. The goal of the work was to design a reliable numerical model of the stacked package and afterwards perform numerical design for optimization in reference to a number of variables, which influence the package reliability. The numerical model of the analyzed stacked package was elaborated in ABAQUS with an embedded Python script language. The design for optimization was done by two alternative approaches: direct and indirect design for optimization. The direct approach was based on genetic algorithms while indirect approach was achieved by combination of design of experiments (DOE) with response surface modeling (RSM) methods

Simulated annealing as a global optimization algorithm used in numerical prototyping of electronic packaging

There are many optimization algorithms, which can be used to find the extremum of a function. However, in optimizing the function, which is obtained from the numerical calculations, it is necessary to apply the proper global optimization algorithm. It is caused by the high nonlinearity of the numerical functions response. The nonlinear function with not known analytical form may have many local extrema and only one global extremum. Such problems occur in numerical prototyping, when the finite element method is used, for example in numerical optimization in electronic packaging in order to inmprove the components reliability.

An approach of numerical multi-objective optimization in stacked packaging

The main aim for the development of small electronic packages is supported by an ongoing development of portable communication devices. Thin silicon dies are believed to improve the device performance as well as its reliability. Additionally, novel packaging techniques such as stacked packaging reduce packaging cost and size, and improve the functionality and reliability. In the case of the stacked packages, wafers are stacked to form a 3D multi-chip package. On the other hand, the electronic market requires novel and efficient numerical designing tools to deal properly with the optimization. The goal of the current work was to design a reliable numerical model of the stacked package and afterwards perform numerical multi-objective optimization in reference to a number of variables, which influence the stacked package reliability.

Application of numerical optimization algorithms used to investigation of thin films in nanoindentation test

Current developments and trends in microelectronics are focused on thin layers and novel materials. This leads to application of different test and measurement methods, which are capable to measure basic mechanical properties of such materials on micro-scale and nano-scale. This paper focuses on application of the nanoindentation technique. It is one of the most common method for investigating the mechanical material properties (especially thin layers). In order to extract the basic elastic and elasto-plastic mechanical properties the numerical optimization algorithms were used as a support for the tests in combination with the FE-model of the nanoindentation process.

Numerical approach to extraction of elasto-plastic material models and corresponding properties of thin layers through nanoindentation technique

Current developments and trends in microelectronics are focused on thin layers and novel materials. This leads to application of different test and measurement methods, which are capable to measure basic mechanical properties of such materials on micro-scale and nano-scale. The presented project focuses on application of the nanoindentation technique in order to extract the basic elastic and elasto-plastic mechanical properties of aluminium through analytical and numerical approaches. The results allowed to select the most appropriate elastoplastic material model that would be capable of fitting the experimental and numerical results. According to the performed analysis it was concluded that Ramberg-Osgood model fulfil the above criteria and can be used to predict the nanoindentation results in case of very thin aluminium layers.

Multi-objective Parametric Approach to Numerical Optimization of Stacked Packages

The main aim for development of small electronic packages is supported by an ongoing development of portable communications devices. Thin silicon dies are believed to improve as device performance as its reliability. Additionally, novel packaging techniques as stacked packaging reduce packaging cost, size, improve functionality and reliability. In case of the stacked packages, wafers are stacked to form 3D multi-chip package. On the other hand, the electronic market requires novel and efficient numerical designing tools to deal properly with the optimization. The goal of the current work was to design a reliable numerical model of the stacked package and afterwards perform numerical multi-objective optimization in reference to a number of variables, which influence the stacked package reliability.

Investigation of thin films by nanoindentation with doe and numerical methods

Nanoindentation is one of the most known method for investigating the properties of thin films. The materials can be assessed by means of elastic mechanical properties (hardness and Youngs modulus). However, the authors research works show that it is possible to obtain the elastic as well as the plastic material behavior of the investigated thin layer. It can be done by using the nanoindentation experiment and the numerical simulations. This paper focuses then on investigation of thin metal layers by nanoindentation with a support of numerical methods, such as finite element method and numerical optimization processes. Additionally, the 3-level, full factorial design of experiment (DOE) process was applied. In order to carry out such experiment 27 samples were prepared and taken into account: 3 different materials with 3 different thicknesss values sputtered on 3 different substrates. The results were then processed by the numerical methods in order to achieve more information about the materials — mainly the plastic behaviour.

Application of genetic algorithm in numerical multi-objective optimization of ceramic capacitors

Passive electronic elements such as capacitors and resistors are the most numerous parts used in electronics. In this paper, the ceramic capacitors were taken in the consideration. The purpose was to improve the reliability of such elements by carrying out the numerical multiobjective optimization process. In such components the reliability is strictly related to thermal-mechanical integrity. The key factor in such structures is the residual stress which occurs due to the differences of thermal expansion coefficients between the layers. To minimize the risk of failure (i.e. cracking, delamination) the 3D numerical parametric model of CC structure was elaborated using the finite element method. Afterwards, in order to minimize the failure risk in the crucial areas of the capacitor, the multi-objective optimization process was designed and carried out. To obtain the global extrema, as a result of the multi- objective optimization process, the classic genetic algorithm was applied. The idea of these algorithms is taken from the biology. They base on the natural evolution process in which the best suited individuals are taken for creating the next population. As a result, the best individuals survive and represent the optimizations solutions. In the investigation the self-made optimization tool was used. The tool was made in Python scripting language and it has implemented the multi-objective algorithms and methods that allow to apply and to optimize the numerical models (i.e. made in Ansys or Abaqus).

Characterization Of Deformation Properties Of Metals In 3D ICs

The properties of the materials involved in the set‐up of 3D ICs need to be known, when the occurring mechanical stresses are to be modeled. Especially elastic‐plastic properties are relevant for the metal layers, which form redistribution layers and the through silicon vias. These can be characterized by the nanoindentation experiment, which is an established technique for the determination of Hardness and Young’s modulus of thin films. But this standard data set is not sufficient to be used as input to finite element simulations, because stress strain curves are required for the analysis of reliability of metal layers. These stress‐strain curves can be obtained by fitting the force displacement curves of the experiment with a finite‐element model. This approach enables additionally a solution for the so called substrate effect, because the stiffness of the substrate can be considered in the fitting model. This known approach is being applied and tested on thin (300 nm) gold layers deposited on silicon. ...

Application of multi-criteria optimization algorithms to numerical material extraction of thin layers through nanoindentaion technique

Current developments and trends in microelectronics are focused on thin layers and novel materials. This leads to application of different test and measurement methods, which are capable to measure basic mechanical properties of such materials on micro-scale and nano-scale. The presented paper focuses on application of the nanoindentation technique in order to extract the basic elastic and elasto-plastic mechanical properties through numerical approaches. In order to extract the elasto-plastic material data of the investigated thin layers the numerical process was designed. First of all, the nanoindentation process was elaborated in FEM Abaqus software. Then, the results were compared to the measurements and processed by the numerical optimization algorithms.