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A climate classification for corrosion control in electronic system design
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark.ORCID iD: 0000-0002-7101-8596
Department of Mechanical Engineering, Technical University of Denmark, Kongens Lyngby, Denmark.
Department of Mechanical Engineering, Technical University of Denmark, Kongens Lyngby, Denmark.
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark.ORCID iD: 0000-0003-4222-9631
2022 (English)In: Machine Learning with Applications, ISSN 2666-8270, Vol. 9, article id 100397Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 9, article id 100397
Keywords [en]
Climate classification, Corrosion, Electronics, K-means, Clustering, Printed circuit board enclosure, Reliability
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Quality technology and logistics
Identifiers
URN: urn:nbn:se:ltu:diva-92375DOI: 10.1016/j.mlwa.2022.100397OAI: oai:DiVA.org:ltu-92375DiVA, id: diva2:1685905
Note

Godkänd;2022;Nivå 0;2022-12-02 (sofila);

Funder: Innovation Fund Denmark

Available from: 2022-08-05 Created: 2022-08-05 Last updated: 2022-12-02Bibliographically approved

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Kulahci, Murat

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