Comprehensive Material Characterization and ...

Comprehensive Material Characterization and Method of its Validation by Means of FEM Simulation 1

P. Gromala1, J. Duerr1, M. Dressler2, K. M. B. Jansen3, M. Hawryluk4, J. de Vreugd5 Robert Bosch GmbH, Automotive Electronics, Tuebinger Str 123, 72762 Reutlingen, Germany 2 Robert Bosch GmbH, Corporate Research, Waiblingen 3 Delft University of Technology, Faculty of Mechanical, Maritime and Materials Engineering 4 Cracow University of Technology, Faculty of Mechanical Engineering 5 TNO Email: przemyslawjakub.gromala@de.bosch.com

Abstract Numerical simulation plays an important role in product design. Its accuracy relays on a detailed description of geometry, material models, load and boundary conditions. This paper focuses on a new approach of FEM material modeling of three commercially available molding compounds. Curing shrinkage, modulus of elasticity and coefficient of thermal expansion were measured and implemented into commercially available FEM code Ansys. Fringe pattern technique has been used to measure warpage of bimaterial strips. Then FEM simulation of bimaterial strips were done and compared with experimental results. Curing shrinkage has been modeled in an effective way. Its accuracy has been checked on one of the materials by creating bimaterial strips with three different geometrical dimensions, that is varied thickness of mold and copper substrate. Introduction Due to different material properties of different layers in electronic components temperature cycles leads to warpage. Correct prediction of the warpage and stresses by means of FEM simulation allows a shortening of the design cycling time as well as more reliable product is provided. However, reliable modeling can be achieved only if a detailed material characterization and its proper implementation into FEM code is available. Molding of electronic packages is made in few steps. Schematically it is shown in Fig. 1Fig. 1. First, a substrate with an integrated circuit is placed into the molding cavity and preheated for about one minute. Parts can reach temperature up to 130°C. Then the tool closes up to 1 mm below the final clamping position and the air is evacuated from the cavity. After this the tool is clamped completely with a defined pressure. During that time the substrate and circuitry rapidly heat up to a temperature of 160 to 170°C. Resin pellets which are stored in a plunger cavity are melted. After 5 to 10 seconds, the transfer of the molding compound starts. The temperature of the molding compound is in the range of 145 to 165°C. Time that is needed to fill the cavity is about 15 to 20 seconds. In a next step of the process the molding compound is cured. Here the part is kept at 175-180°C for 120sec. During that time the molding compound shrinks. This shrinkage is compensated by movement of the

tool which is controlled by applying constant pressure. During that time the conversion level of the molding compound can reach up to 80-90%. After 2 minutes the machine opens and the part can be removed. Already at that moment the part is warped. The amount it is warped depends on the conversion level. During cooling of the part to room temperature, the warpage changes, depending on the CTE mismatch. During post mold cure (PMC) the part is stored at a temperature of about 175°C for 4 hours. Here the remaining process of curing happens. After cooling down to room temperature the part again deviates from flatness, which is the sum of chemical shrinkage after molding and PMC, and the CTE mismatch between materials. Theoretically after PMC, molding compound should not exhibit reactivity anymore.

Heating up 25170°C

Transfer molding 145170°C

Curing 175180°C

Cooling down 18025°C

Post mold cure 2518025°C

Formatted: French (France) Field Code Changed Formatted: French (France) Formatted: French (France)

Ansys using Prony series by means of eq. 1. Master curve has been constructed using a look up table.

Material characterization Polymer materials such as epoxy molding compounds require detailed characterization [3]. The reason is, that they behave visco-elastically, that means that their properties are time and temperature dependent. In addition, chemical shrinkage that occurs during the polymerization process has to be taken into account. In currently available FEM code, an implementation of the chemical shrinkage is not straight forward available. Typically the implementation is made by an effective strain at transfer molding temperature or a change of the reference temperature of the material. In Ansys, a physical description of shrinkage that occurs during the molding process can be realized only by means of a user defined material macro. In the present study, three commercially available molding compounds were selected. They are codednamed as molding compounds A, B and E. Table 1Table 1 presents theirs properties that can be found in a data sheets provided by suppliers. Table 1 Data sheet properties of studied molding compounds MC A MC B MC E Modulus of elasticity 23544 20601 24500 @RT [MPa] CTE below Tg [ppm/K]

7

9

9

CTE above Tg [ppm/K]

31

37

38

Tg [°C]

135

135

125

Curing shrinkage [%]

0.02

0.15

Not specified

Filler content [%wt]

89

87

88

The values that are presented in data sheets quite often deviate from those which can be measured. This is caused by the complexity of the molding compound itself. Additionally, material properties depend on the method used for measurements. Last but not least they strongly depend on the process conditions. Because of those reasons a detailed characterization, using always the same method, is needed in order to achieve reliable FEM simulation results. Viscoelastic properties were characterized using a TA Instruments DMA Q800 apparatus. Material properties were determined by a multifrequency sweep in a range of temperature 25°C up to 250°C. Implementation of modulus of elasticity is done in

nG  t G  G   Gi exp  G i 1  i

   

 t K  K    K i exp  K i 1  i

  

(1) nK

During the polymerization process, the molding compound is changing its volume as well as its material properties. At first, the glass transition temperature is shifted to a higher regime. Also rubbery modulus of elasticity increases. In addition, chemical shrinkage occurs. This causes stresses which have to be taken into account in order to achieve a quantitative modeling of the molding process. For measuring shrinkage that occurs during polymerization process, a PVT experiment was conducted. Measurements were done using GNOMIX PVT apparatus. These measurements were conducted at constant pressure at 100°C. Higher temperatures can lead to too fast polymerization. In that case the material would react almost completely before reaching a constant temperature. Fig. 2Fig. 2 schematically presents the change of volume of the molding compound sample during the PVT experiment. At the beginning, the volume of a molding compound inside is equal to volume at point 1. Point 2 is the glass transition temperature Tg1 of the not reacted material. Then sample is heated up until point 3 is reached, where it is stored for 480 minutes. Change in the volume between points 3 to 4 is caused by curing shrinkage. After that the material is cooled down to room temperature (point 6). Deflection of the curve at point 5 is the glass transition temperature Tg2 of the fully cured material. The slope of the curve is proportional to the coefficient of thermal expansion below and above Tg.

Volume

Fig. 1 Molding process

3 Chemical shrinkage

1

4

2 5

6 Tg2 Tcure Temperature Tg1 Fig. 2 Scheme of curing shrinkage during polymerization process of molding compound In addition the specific volume of a fully cured sample was measured at different temperatures and pressures. The measurements were fitted with a Tait equation, which allowed deriving the coefficient of

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thermal expansion (eq. 2) as well as the temperature dependent bulk modulus (eq. 3). CTEv (T )  k1

 21 k 2 1  tanhC1 T  Tg 0 

(2)

1  s0  k1  12 k2 A K (T ) A  1  tanh C1 T  Tg 0   

c B (T )

(3)

Fig. 3Fig. 3 depicts the coefficient of thermal expansion for different pressures, ranging from 10 to 100 MPa, of mold type B fitted with a Tait equation.

CTE [1/K]

4.00E-05 3.00E-05 2.00E-05 1.00E-05 0.00E+00 0

50

100

150

200

250

Temperature [°C]

10 MPa 20 MPa 30 MPa 40 MPa 50 MPa 60 MPa 70 MPa 80 MPa 90 MPa 100 MPa

Fig. 3 Fitted linear coefficient of thermal expansion using Tait equation Fig. 4Fig. 4 shows the bulk modulus for different pressures (in MPa) of mold type B fitted with a Tait equation. 35000 K [MPa]

30000 25000 20000 15000 10000 0

50

100

150

200

250

Temperature [°C]

10 MPa 20 MPa 30 MPa 40 MPa 50 MPa 60 MPa 70 MPa 80 MPa 90 MPa 100 MPa

Fig. 4 Fitted bulk modulus using Tait equation A detailed discussion about the used method for material characterization is described by Jansen at al. [9] and will not be included in that paper. Bimaterial sample Bimaterial strips (Fig. 5Fig. 5) were selected to study the effect of the polymerization of the studied molding compounds. Such samples are often used to investigate the validity of material models [1], [2], [8]. Copper Mold

Fig. 5 Bimaterial strip used in the study The molding compounds were molded on a copper substrate. In Table 2Table 2 the dimensions of the

bimaterial samples are shown. In reference case, molding compound is 2 mm thick, whilst copper substrate only 0.4 mm. 10 strips per molding compound (type A, B, E) were manufactured using the same process as real Bosch products. This investigation allows revealing the difference between studied materials, such as difference in CTE, Tg and curing shrinkage. In order to investigate the effect of an effective CTE [1] for verification purposes, molding compound type E was prepared with lower thickness 0.6 mm (Sample 2) as well as lower copper substrate thickness 0.2 mm (Sample 3 – only 5 samples). Dimensions of all studied configurations are presented in Table 2Table 2. Table 2 Dimensions of a bimaterial strips Length Width Thickness [mm] [mm] [mm] Sample 1 (reference)

50

9

EMC: 2.0 mm Cu: 0.4 mm

Sample 2

50

9


Sample 3

50

9


Warpage measurements FEM simulation is a powerful tool which can accelerate design time. However its accuracy depends on many factors, such as material description, geometry representation, boundary and load conditions and finally the evaluation method. FEM simulations need to be validated and correlated with experimental techniques. There are many available techniques that can be used for validation purposes: strain measurements, stress measurements, deformation measurements. Among these, warpage measurements done at different temperatures exhibit several advantages [4]: - Non-destructive method, - Wide range of temperature, - Deformation in out-of-plane as well as in-plane directions, - Process and reliability environment is possible to be simulated, - Material properties can be extracted. A Topography and Deformation Measurements (TDM) apparatus from INSIDIX has been used to measure warpage of the bimaterial samples. Warpage has been measured in a temperature range between 25 and 225°C. At 225°C, the sample was kept for 10 min. Temperature increased/decreased with a 2K/min ramp rate. This low temperature change was selected to assure a homogeneous distribution of the temperature over the entire sample. Warpage has been measured during heating up and cooling down phase.


Fig. 6Fig. 6 depicts schematically the INSIDIX apparatus. The bimaterial sample is placed in a temperature chamber, copper facing up. Directly above the sample, a CCD camera is placed which takes a picture of the observed surface. At the side, a source of light is located. The element under investigation is heated up from top and bottom by infrared heating elements. Directly beneath the lower heating element there are also cooling pipes used to cool down the structure with required cooling rate. The machine is controlled by a steering driver placed in the apparatus and connected to a PC.

t gh c e Li o u r s Temperature chamber

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µm µm µm

Fig. 7 Roughness of a copper substrate

Camera

Thermocouple

One example profile is presented in Fig. 7Fig. 7. One can see that the roughness of the copper substrate is 28µm in average, but it can vary between 41µm and 12µm. In that range warpage can be exaggerated.

Heating element Bimetal sample Heating element

Fig. 6 Scheme of TDM warpage apparatus Warpage is measured using a fringe pattern projection technique. It allows measuring both absolute and relative deformation. Before the measurements, the apparatus needs to be calibrated. During that process a deformation of a calibration plate in out-of-plane and in-plane direction is measured, and a benchmark pattern is saved. Later on, when the actual sample is investigated it’s initial surface already deviates from flatness. A new pattern is compared with the reference pattern. Based on the deviation, warpage is calculated. The same procedure is done by applying a temperature loads. Warpage is a deformation measurement in out-of-plane direction. Based on the deformation in in-plane direction, one can evaluate the relative strain between reference and measured temperature. Surface topography of the sample depends on the crystal orientation of a material as well as machining of the material itself [7]. In addition, as the precision of measurements systems increases it causes an increase of the noise in a “high density” measured area [10]. The noise is caused by the surface roughness, small unevenness or even some technological holes or existence of small components. Last but not least it can be caused by an error caused by the measurement system itself. Inaccuracy caused by roughness of the surface should be removed from warpage measurements. It is desirable to filter the raw data in order to get more precise information about warpage of the bimaterial sample itself, without local deformation or imperfection of a measured surface. For example, roughness of the surface of the copper substrate can influence the warpage measurements.

In the current study among available filtering methods, a Robust Gaussian Fillter has been used. It provides very good agreement between obtained results. In addition, the big advantage of that filter is that it can recognize accidental or local features of a product like deep valleys or small passive components and remove them from evaluation. In that case, the filtered curve follows a trend and skips local deformation. Warpage calculated in that way was used for the following evaluation. The effect of applying Robust Gausian Filter is shown in Fig. 8Fig. 8. The blue, “noisy” line corresponds to the raw data, and the red curve is the warpage after filtering. It can be noticed that the difference between measured curve and filtered one, at peak of the curve, is as much as 40µm, which corresponds to the roughness of the copper surface (Fig. 7Fig. 7). µm

Raw data

Robust Gaussian filter

mm

Fig. 8 Warpage of a bimaterial sample, Mold Type E, sample 8, T=85°C Warpage of a bimaterial sample depends on the coefficient of thermal expansion of both materials as well as on the cure shrinkage. In the studied cases, below glass transition temperature molding compounds have lower CTE then copper. Because of that at the initial stage from 25°C to 100°C warpage increases. When the temperature is higher than Tg, CTE of the mold is higher than that of copper and warpage decreases. At the peak temperature, warpage changes it’s shape from convex to concave. Zero warpage temperature that is quite often called stress free temperature was



measured between 150 to 250°C depending on mold type as well as used sample. As an example, Fig. 9Fig. 9 depicts the results for sample 1 for mold type E, measured during heating up phase between 25 to 225°C.

can be calculated (eq. 4) and compared with the one obtained from experiment (Fig. 11Fig. 11). E

50 0 -50 0

10

20

30


(4)

X dyn  A0

40

10000 1000 100

50

10

Length [mm]

T=50°C

T=75°C

T=100°C

T=150°C

T=175°C

T=200°C

T=225°C

0

T=125°C

Fig. 9 Warpage of a bimaterial sample, Mold Type E, sample 1, T=25 to 225°C  heating up phase In order to see the standard deviation and its influence on the properties of the studied molding compounds multiple strips were measured. As an example, results of mold type E at 100°C for 10 different bimaterial samples are presented in Fig. 10Fig. 10. 400 300 200 100 0 0

10

20

30

40

50

-100 Length [mm] Sample 1 Sample 6

Sample 2 Sample 7

Sample 3 Sample 8

Sample 4 Sample 9

100

200

300

Temperature [°C]

Sample 5 Sample 10

Fig. 10 Warpage of a bimaterial sample, Mold Type E, sample 1 to 10, T=100°C  heating up phase FEM material validation In order to check the accuracy of the implemented model, DMA tests done to evaluate time and temperature properties of molding compound were next simulated. A tensile, sinusoidal load applied at different temperatures and frequencies utilized in the experiment, was simulated in FEM software [6]. A viscoelastic material model can be composed of many different parameters. In the studied case, it was implemented using around 30 prony pairs which already lead to 60 parameters. The shift factor of the master curve was implemented by means of a look up table that was also composed of around 60 additional parameters. In case of error in the material model, it is very hard to debug such a macro. Therefore it is recommended to do a material evaluation, like a DMA test, before using it in a product simulation. Using the reverse engineering approach a storage and loss modulus

E' - experiment

E'' - experiment

E' - FEM

E'' - FEM

Fig. 11 Storage and loss modulus of investigated molding compound, here mold type A The load applied to a bimaterial sample has been composed from three sections. First one simulates a cooling down process from post mold cure temperature, T=180°C up to room temperature. Section two simulates storage at room temperature. The last section, a temperature profile as in the experiment starting from room temperature until 225°C, with 10 min dwell time at 225°C and then cooling down to room temperature, is analyzed. During heating up and cooling down phase temperature changes with 2K/min. The load profile used in the simulations is presented in Fig. 12Fig. 12. The blue line corresponds to a simulated temperature profile, whilst dots represent points at which warpage was evaluated (25 up 225°C, every 25K). 60000 60600 61200 61800 62400 250 63000 63600 64200 200 64800 65400 150 66000 66600 67200 100 67800 68400 69000 50 69600 70200 708000

25 50 75 100 125 150 175 200 225 225 200 175 150 125 100 75 50 25 25

0



Load profile used in FEM simulation

Cooling down after PMC

Temperature [°C]

T=25°C

Warpage [µm]


100000

250 200 150 100

E', E'' [MPa]

Warpage [µm]

400 350 300

Fdyn  Lm

Warpage heating up phase

Warpage cooling down phase

Storage time

20000

40000

60000

80000

100000

Time [s]

Fig. 12 Load profile used in FEM simulation Fig. 13Fig. 13 shows comparison of warpage experiment and FEM simulation. Dots represents warpage of a bimaterial samples at studied temperature obtained using Robust Gaussian Filter. Results are presented only for the heating up phase. One can see that in case of material type A and B (Fig. 13Fig. 13a and Fig. 13Fig. 13b respectively) the deviation is very low. Standard deviation was calculated for each of the temperatures. Below Tg, it was in the range of 20µm, whereas above it was in the range of 30µm.


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In Fig. 13Fig. 13c results of mold type E are presented. Here one can see that deviation is higher than in case of material type A and B. The continuous line presents results of FEM simulation. The coefficient of thermal expansion was fitted to the average values of all 10 measurements, focusing on minimizing relative error between simulation and experiment. a) 400

Warpage [µm]

300 200 100 0 0

50

100

150

200

250

-100 -200 Temperature [°C]

b) 400

Warpage [µm]

300

100 0 0

50

100

150

200

250

-200 Temperature [°C]

c) 400

Warpage [µm]

300 200 100 0 0

50

100

150

200

250

-100 -200 Temperature [°C]

Fig. 13 Warpage of three studied molding compound, a) molding compound A, b) moldin compound B, c) molding compound E Based on the warpage measurements, FEM simulations were conducted, in order to estimate


Table 3 Material properties of studied molding compound based on the conducted studies Type A Type B Type E Modulus of elasticity 24857 22450 20800 @RT [MPa] CTE below Tg [ppm/K]

9.3

10.3

11

CTE above Tg [ppm/K]

29

34.3

35.4

104 134

108 134

105 125

0.0

0.1

0.2

Tg [°C] By TMA: By DMA:

200

-100

material properties of the studied materials. Using bimaterial strip of mold on a copper substrate, it is possible to obtain coefficient of thermal expansion, glass transition temperature as well as effective curing shrinkage. Table 3Table 3 presents data obtained from the material characterization and FEM validation study. One can see that most of the values differ from those found in the data sheet. It is important to note that in case of Tg, in the data sheet values corresponds to a DMA test. However for a FEM material modeling, it is crucial to model correctly the coefficient of thermal expansion. Based on the data sheet one would use a glass transition temperature which is 20 to 30°C higher than the one obtained using TMA test. This would lead to an underestimation of thermal strains of molding compound.

Effective cure shrinkage [%]

As a next step in order to validate the effective properties of curing shrinkage as well as the coefficient of thermal expansion, new samples with different thicknesses of mold and copper were prepared and the whole procedure has been repeated. Measurements were only done for molding compound type E. Measured warpage and the simulation results are presented together in Fig. 14Fig. 14. It can be seen that the deviation between measured samples with lower thickness of mold (0.6 instead of 2.0mm) for EMC type E is much lower than in case of samples with 2 mm thick molding compound. Warpage of a bimaterial strip with copper thickness of 0.4 mm is presented in Fig. 14Fig. 14a. Results of thinner copper substrate 0.2mm is presented in Fig. 14Fig. 14b. Zero warpage temperature -- stress free temperature - lies for all three dimension ratios in the same range. A detailed comparison of the obtained parameters regarding coefficient of thermal expansion as well as glass transition and curing shrinkage is presented in Table 4Table 4. In general, parameters do not deviate much. Curing shrinkage for all three configurations is found to be in the range of 0.19 to


Formatted: Font: Not Bold Formatted: Font: Not Bold

0.20%. The coefficient of thermal expansion below Tg is also in good agreement with values provided in data sheet. Some deviations appeared in case of the glass transition temperature as well as the coefficient of thermal expansion above Tg. For the reference case, Tg is lowest and deviates from the value found in the data sheet by 20K. In case of the sample with 0.6 mm molding compound thickness and 0.4 mm copper thickness, Tg deviates from the data sheet value by 10K only. For the last sample with the lowest thickness of copper, Tg is in between the before mentioned cases. The coefficient of thermal expansion above the glass transition temperature was found to be similar for cases with the same copper thickness (0.4 mm). In case of copper thickness 0.2mm it deviated by 5ppm/K. It needs to be remembered that here the number of bimaterial strips was limited to 5. a) 400

Warpage [µm]

300 200 100 0 -100

0

50

100

150

200

250

-200 Temperature [°C]

b) 800

Warpage [µm]

600 400 200 0 0

50

100

150

200

250

-200 -400

Temperature [°C]

Fig. 14 Warpage of molding compound E, a) Cu=0.4mm, EMC=0.6mm, b) Cu=0.2mm, EMC=0.6mm Table 4 Material properties molding compound type E with bimaterial strips of different dimensions Cu thickness 0.4 mm 0.4 mm 0.2 mm EMC thickness 2.0 mm 0.6 mm 0.6 mm

CTE below Tg [ppm/K] CTE above Tg [ppm/K] Tg [°C] By TMA: Curing shrinkage [%]

11.0

10.7

10.8

35.4

34.3

39.8

105

115

109

0.20

0.19

0.19

Conclusions FEM simulation is a crucial step in nowadays product design. However, if numerical analyses are planned to be used as a virtual qualification tool, they need very accurate input data. In case of organic materials such as molding compound, comprehensive material characterization as well as detailed validation of the model is required. In the paper, method of material characterization using DMA and PVT measurement techniques was presented. Based on the measurements, a viscoelastic material model was prepared for three molding compounds. The accuracy of the models was confirmed by running FEM analysis simulating the DMA tests. Coefficient of thermal expansion, glass transition temperature and effective curing shrinkage were obtained by fitting simulation results to warpage experiments of bimaterial samples. By comparison of the data that are available in the molding compound data sheets with measured values, one can see that the glass transition temperature in the data sheets was obtained by means of DMA test. In case of CTE, Tg is about 20 to 30K lower than that provided by the vendor of molding compounds. Changing the geometry of the bimaterial strips yielded in general no change in parameters. Only small deviations appeared in case of CTE above Tg, and Tg itself but in case of curing shrinkage the effective value is the same. Zero warpage temperature nearly independent from studied geometry. An implementation of user defined material law is not yet done. When it will be available then FEM simulation will be repeated and its effect will be checked in case of theoretical samples as well as in product simulation. Acknowledgments The Author would like to thank Thorsten Wallisch (RBosch) and Rolland Mueller (RBosch) for support with warpage measurements using TDM machine. References [1] T. Falat, K.M.B. Jansen, J. deVreugd, S. Rzepka, “Influence of Cure Dependency of Molding Compound Properties on Warpage and Stress Distribution During and After the Encapsulation of Electronic Components”, 10th International Conference on Thermal, Mechanical and Multiphysics Simulation and Experiments in

Micro-Electronics and Micro-Systems. EuroSimE 2009, Delft 2009 [2] J. deVreugd, K.M.B. Jansen, L.J. Ernst, C. Bohm, T. Falat, , “Cure Induced Warpage of MicroElectronics: Comparison with Experiments”, 10th International Conference on Thermal, Mechanical and Multiphysics Simulation and Experiments in Micro-Electronics and Micro-Systems. EuroSimE 2009, Delft 2009 [3] B. Boehme, K.M.B. Jansen, S. Rzepka, K.J. Wolter, “Comprehensive Material Characterization of Organic Packaging Materials”, 10th International Conference on Thermal, Mechanical and Multiphysics Simulation and Experiments in MicroElectronics and Micro-Systems. EuroSimE 2009, Delft 2009 [4] I. Richard, R. Fayolle, J.C. Lecomte, “New experimental approach for failure prediction in electronics: Topography and deformation measurement complemented with acoustic microscopy”, 6th International Conference on Thermal, Mechanical and Multiphysics Simulation and Experiments in Micro-Electronics and MicroSystems. EuroSimE 2005, [5] M. Thakur, C. Quan, C.J. Tay, “Surface Profiling Using Fringe Projection Technique Based on Lau Effect”, www.sciencedirect.com [6] S. Rzepka, A. Mueller, B. Michel, “Virtual Prototyping Advanced by Statistic and Stochastic Methodologies”, 11th International Conference on Thermal, Mechanical and Multiphysics Simulation and Experiments in Micro-Electronics and MicroSystems. EuroSim 2010, Bordeaux 2010 [7] Huifen Li, C.F. Cheung, X.Q. Jang, W.B. Lee, S. To, “A Novel Robust Gaussian Filtering Method for the Characterization of Surface Generation in Ultra-precision Machining”, www.sciencedirect.com [8] H. Shirangi, B. Wunderle, O. Wittler, H. Walter, B. Michel, “Modeling Cure Shrinkage and Viscoelasticity to Enhance the Numerical Methods for Predicting Delamination in Semiconductor Packages”, 10th International Conference on Thermal, Mechanical and Multiphysics Simulation and Experiments in Micro-Electronics and MicroSystems. EuroSimE 2009, Delft 2009 [9] K.M.B. Jansen, M. Hawryluk, P. Gromala, “Cure dependent characterisation of moulding compounds”, 12th International Conference on Thermal, Mechanical and Multiphysics Simulation and Experiments in Micro-Electronics and MicroSystems. EuroSimE 2011, Linz 2011 [10] M:C: Malburg, “Fitting, Filtering and Analysis: Feature Extraction in Dimensional Metrology Applications”, www.digitalmetrology.com