A climate classification for corrosion control in electronic system design

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 de...

Full description

Bibliographic Details
Main Authors: Max Spooner, Rajan Ambat, Hélène Conseil-Gudla, Murat Kulahci
Format: Article
Language:English
Published: Elsevier 2022-09-01
Series:Machine Learning with Applications
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2666827022000767
Description
Summary: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 K-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.
ISSN:2666-8270