DISCO Technical Review February 2024

Fully automated quality management after singulation
for reliable failure prediction
DISCO Hi-TEC Europe GmbHAbstract
DIS100 is a unit that picks up die from the wafer after singulation and measures the die thickness, chipping, backside surface
roughness, and die strength using a fully automatic process. Efficient and highly accurate measurement is achieved by automating all of the existing manual processes. In addition, DIS100 also records and stores measurement data, improving traceability as required for purposes such as quality audits of automotive devices.

used for process qualification. However, the die that will
break later in the field and customer returns are most likely
not the ones that have median breaking strength values.
Much more of interest are the 0.10% or 1.00% strength
values, defining the lower edge of the process robustness,and for semiconductor device manufacturing in which alarge number of die are manufactured, the overall amountof these low-performance die is not negligible.

“The true logic of this world is in the calculus of probabilities“ – James Clerk Maxwell

1. Introduction
Semiconductor device manufacturing is most likely one of
the most advanced industries when it comes to 24/7 mass
production. Hundreds of billions of die are manufactured
each year and the recent trends towards electrification will
increase their future demand. One critical step in the semiconductor process chain is the separation of a wafer into
individual die, which is directly linked to the yield of theback-end process.

Fig.2 Images taken with a high speed camera during bending
strength monitoring

Fig.1 Fully automatic die inspection tool DIS100

To make a good prediction of these values, a large amountof sampling is necessary. However, this is usually hard toachieve, as previously, measurements were done by a human operator picking up each die with tweezers and placing them on a universal measurement tool, which is time
consuming and occasionally faces difficulties with repeatability and accuracy due to different setups and handling
methods. DIS100 (Fig.1), a fully automatic die inspection
tool, can overcome these problems. DIS100 reduces handling-induced measurement variations and errors, andmaximizes the sampling size to make more accurate predictions in terms of failure probabilities.

The general need to reach thinner silicon thicknesses for
power devices in order to improve the electrical performance and for memory devices in order to realize higher
capacity by stacking die is increasing the demand forhighly robust and reliable processing. One of the approaches used to investigate the mechanical robustness of
singulated die is the 3-point bending test. The 3-point
bending test is a destructive test, and is for example, applied using sample sizes of 25 and 40. Comparing the median bending strength of the data set is often used during
process development, for example to evaluate which parameter set gives the nominal highest strength and will be1

DISCO Technical Review January 2024
and that the deflection of the die is low, and both are key
criteria for the 3-point bending measurement assuming alinear bending behavior.

2. Equipment
DIS100 operates by repeating the following process flow
automatically for each individual die in a customer’s set
sampling size and pick-up position on the wafer (Fig.3).
(i) Set the frame cassette manually or via OHT(ii) Pick up the die from the dicing tape(iii) Sidewall inspection,* Backside inspection**(iv) Die flip (only if front side needs to be measured)(v) 3-point bending strength measurement**** Chipping and die thickness measurement** Backside roughness measurement*** High-speed camera monitoring
OHT compatibility, sidewall inspection, backside inspection, and high-speed camera are additional specifications(not standard).

Fig.4 Chipping analysis (upper images) and backside roughness
measurement (lower image)

By utilizing a wafer map, more efficient testing and failure
analysis can be realized. Two examples are introduced below. One is to utilize an electrical characteristics testing
wafer map for the probe test process. With this, only electrically dysfunctional dies are picked up and measured by
DIS100, and this can be used for quality management during high volume manufacturing. The other is utilizing acolor-coded wafer map of the bending strength results ofindividual die (Fig.5) for breakage analysis. With this, different kinds of failure modes can be found depending at
the wafer and lot level. Repeatable low mechanical robustness on the edge area of the wafer might be an indicator ofsystematic weakness inside the process chain, whereas localized weak positions on a single wafer are most likely
due to a single event, such as a particle laminated between
the tape and wafer, which can damage the die or lead to
reduced performance in the dicing and grinding processes.

Fig.3 Process flow of DIS100

The ability to measure the thickness of the sample with aresolution of 0.2 µm is also highly valuable due to thequadratic influence on the final result of testing (Eq1.1).
Especially for thin devices below 100µm, a total thickness
variation of several microns cannot be ignored and canlead to misinterpretation if not measured accurately. An alternative method that is often used is to measure the thickness at two positions of the wafer, one at the edge and another at the center, and assume that the surrounding die
have a similar thickness. However, there is a possibility
that the thickness of each die may vary using this method.
DIS100 measures the thickness of each die, and accurate
die strength can be calculated using these values.
Pre-damage of the die in the form of chipping of the sidewall can also be detected by an investigation prior tobreaking, similar to the surface condition of the backsidein terms of roughness (Fig.4). DIS100 measures and records die processing quality data. Therefore, this data canbe useful for failure prediction by taking the correlation of
the processing and die strength into consideration, as well
as for improving traceability.
For advanced monitoring, the use of a high-speed camera
with a sampling rate of up to 2M frames per second is aninteresting feature. Fig.2 shows four selected images atdifferent time stamps of a silicon die during bending
strength measurement. It is clearly visible that the crack
starts in the center of the die where the force is applied,Fig.5 Color-coded wafer map indicating the bending strength ofeach die2

DISCO Technical Review January 2024
higher and one factor lower compared to the outcome
achieved using higher sample sizes of 1000.This fluctuation is too large to make predictions for reliable failure
analysis. For n=500 the shape and scaling parameters areclose to the values gathered from n=1000.

3. ExperimentThe goal of this study is to investigate the influence on thelow percent values of the bending strength test by manipulating the sample sizes used for Weibull parameter fitting.
Data sets were generated based on 1000 measurements fortwo different separation approaches and then were split
into different sub group sizes for statistical analysis.

Table 1 Weibull fitting parameters and bending strength values
for different sample sizes

The second data set also consisting of an overall sample
quantity of a thousand die was partially split into 5 subgroups of 25 samples each. Table 2 shows the Weibull fitting and Figure 4 displays the calculated values for 1.00%
distribution. For the full sample size of 1000, the value
was found to be 519 MPa, and therefore measurement set
n3 for example, is already off by around 20%. Overall theconfidence level for a sample size of 25 seems to be insufficient, and the fluctuation from measurement to measurement is significant.

Fig.6 3-point bending test

All testing was done using the 3-point bending approachand die strength was calculated using (Eq.1).

Table 2 Weibull fitting parameters and bending strength values
for 5 measurements with a sample size of 25

Here, σ is the die strength (MPa), F represents the appliedload (N), L is the span of the lower support pins (mm), w
is the width, and t is the thickness of the die (mm) (Fig.6).
The Weibull distribution probability was calculated using(Eq.2).

Here, Q(σ) = (i-0.3)/(n+0.4) defines the quantile of thesampling, ß is the shape, and α is the scale parameter. AWeibull distribution was used to determine the low percentage bending strength values of 0.10% and 1.00%(Fig.7).

Fig.6 Fluctuation of the 1.00% values for 5 measurements witha sample size of 25

The last experiment was used to investigate the influenceof the die width (“w” in Fig.6) on the bending strength
outcome. Usually, a certain technology spans several different die sizes called basic types, and each size is designed to fit in a defined package. As the same die stackarchitecture and an identical dicing kerf with the same process for singulation are mostly used, similar stress levels
are induced on the die sidewall during the separation step.
In general, the width is part of the 3-point bending (Eq.1)
equation, and it is widely expected that measuring theFig.7 Weibull distribution probability plot

The first data set of a thousand die was split into individual
smaller sets of n=25, n=40, n=200 and n=500. For eachindividual set, the Weibull distribution was calculated, andlow percentage values were fitted. Table 1 shows that for
sample sizes of 25 and 40, the 0.10% value deviated by 87
MPa from each other, and the values were one factor3DISCO Technical Review January 2024
strength of one basic type is representative of the whole
portfolio. In Table 3, the median values are displayed withrespect to die widths of 2 mm, 2.5 mm, and 3 mm for a
fixed stack and die length. It is clearly visible that an increased die width leads to a lower bending strength. One
possible explanation might be the difference in stack andlayer thickness of patterned devices, which influences theapplied load on the sidewall of the die. Therefore it is necessary to test all relevant basic types individually to getreliable feedback about the process’ robustness.
Table 3 Influence of the die width on the bending strength result
for a certain stack configuration

4. Summary
To get a clear picture of the mechanical bending strength
after the separation process, it is necessary to increase thesample size compared to previous approaches that used asize of 25 or 40 samples. Accurate values based on highstatistics for reliable failure rate predictions can beachieved using the DIS100 by minimizing handling-induced errors due to the fully automatic process flow. . The
ability to use advanced inspection items like thickness,
chipping, and roughness measurement adds additional
value to the accuracy of the testing outcome and can prevent wrong interpretations of a certain result.

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