Automatic characterisation method for statistical evaluation of tin whisker growth

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00316563" target="_blank" >RIV/68407700:21230/17:00316563 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.microrel.2017.04.007" target="_blank" >http://dx.doi.org/10.1016/j.microrel.2017.04.007</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.microrel.2017.04.007" target="_blank" >10.1016/j.microrel.2017.04.007</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic characterisation method for statistical evaluation of tin whisker growth

Popis výsledku v původním jazyce

In this paper, an automatic method was developed to characterise whisker growth quantitatively in SEM images. The key step of the automatic methods in this case is the determination of the optimal threshold value for image segmentation, i.e. separation of the objects (whiskers) from the background (substrate). A thresholding method was developed for this purpose and was compared to manual and to general purpose automatic methods as references. As it was proven in previous studies the vacuum deposited tin layers on copper substrates can produce numerous tin whiskers in various shapes and lengths in a short time. This layer deposition technology was therefore chosen for the comparison of the thresholding methods. Images of the produced whiskers were captured by a FEI Inspect S50 Scanning Electron Microscope. By executing the automatic methods in the captured images, the area density of the whiskers, and the maximum and the mean length of the whiskers were measured. Based on the results of area density, the automatic methods were compared to manual counting and the Mean Absolute Percentage Error (MAPE) was determined. Finally, the reference automatic methods were compared to the self-developed method from the maximum and mean length of whiskers point of view

Název v anglickém jazyce

Automatic characterisation method for statistical evaluation of tin whisker growth

Popis výsledku anglicky

In this paper, an automatic method was developed to characterise whisker growth quantitatively in SEM images. The key step of the automatic methods in this case is the determination of the optimal threshold value for image segmentation, i.e. separation of the objects (whiskers) from the background (substrate). A thresholding method was developed for this purpose and was compared to manual and to general purpose automatic methods as references. As it was proven in previous studies the vacuum deposited tin layers on copper substrates can produce numerous tin whiskers in various shapes and lengths in a short time. This layer deposition technology was therefore chosen for the comparison of the thresholding methods. Images of the produced whiskers were captured by a FEI Inspect S50 Scanning Electron Microscope. By executing the automatic methods in the captured images, the area density of the whiskers, and the maximum and the mean length of the whiskers were measured. Based on the results of area density, the automatic methods were compared to manual counting and the Mean Absolute Percentage Error (MAPE) was determined. Finally, the reference automatic methods were compared to the self-developed method from the maximum and mean length of whiskers point of view

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Microelectronics Reliability

ISSN

0026-2714

e-ISSN

—

Svazek periodika

73

Číslo periodika v rámci svazku

JUN

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

8

Strana od-do

14-21

Kód UT WoS článku

000403512300002

EID výsledku v databázi Scopus

2-s2.0-85019689980