Abstract
Climate factors such as humidity and temperature have a
significant impact on the corrosion reliability of electronic products.
Given the huge geographical variability in climate conditions globally, a
climate classification
is a useful tool that simplifies the problem of considering climate
when designing electronics packaging. Most current guidelines for
electronic product design rely on the Köppen–Geiger classification first
developed by Köppen over a century ago. Köppen devised a set of
heuristics to separate climates to match different vegetation types.
These climate classes are unlikely to be the optimal for electronic
product design. This paper presents a new climate classification using
parameters important for corrosion reliability of electronics. The
classification is based on real climate data measured every 3 h during a
5-year period at over 9000 locations globally. A key step is defining
relevant features of climate affecting corrosion in electronics.
Features related to temperature are defined, but also the amount of time
that the difference between Temperature and Dew Point is less than 1, 2
or 3 ℃. These features relate to the risk of condensation in electronic
products. The features are defined such that diurnal, seasonal and
yearly variation is taken into account. The locations are then clustered
using -means
clustering to obtain the relevant climate classes. This data-driven
classification, based on key features for corrosion reliability of
electronics, will be a useful aid for product design, reliability
testing and lifetime estimation.
Original language | English |
---|---|
Article number | 100397 |
Journal | Machine Learning with Applications |
Volume | 9 |
Number of pages | 10 |
ISSN | 2666-8270 |
DOIs | |
Publication status | Published - 2022 |
Keywords
- Climate classification
- Corrosion
- Electronics
- K-means
- Clustering
- Printed circuit board enclosure
- Reliability