Rethinking Reliability Engineering: Lessons From FABER to Modernize ALT in the AI Era

Fatigue life estimation and accelerated life testing (ALT) are foundational methodologies in quality and reliability engineering. They ensure the durability and performance of materials and systems exposed to operational stresses such as thermal cycling, mechanical vibrations, humidity, corrosion, and multiaxial loads. Despite their shared objective of reliability assessment, these approaches differ in methodology and focus, offering complementary strengths. Compared to other approaches in reliability engineering, such as condition monitoring and predictive maintenance, neither fatigue life estimation nor ALT has seen significant development in the AI era.

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Publication Details

Journal
IEEE reliability magazine
Published
2025-04-16
DOI
https://doi.org/10.1109/mrl.2025.3555200
Primary Topic
Reliability and Maintenance Optimization
Type
article
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article

Rethinking Reliability Engineering: Lessons From FABER to Modernize ALT in the AI Era

Jing Lin
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IEEE reliability magazine
Reliability and Maintenance Optimization
article

Rethinking Reliability Engineering: Lessons From FABER to Modernize ALT in the AI Era

Jing Lin
article en

Abstract

Fatigue life estimation and accelerated life testing (ALT) are foundational methodologies in quality and reliability engineering. They ensure the durability and performance of materials and systems exposed to operational stresses such as thermal cycling, mechanical vibrations, humidity, corrosion, and multiaxial loads. Despite their shared objective of reliability assessment, these approaches differ in methodology and focus, offering complementary strengths. Compared to other approaches in reliability engineering, such as condition monitoring and predictive maintenance, neither fatigue life estimation nor ALT has seen significant development in the AI era.

IEEE reliability magazine Vol. 2(2)
Luleå University of Technology (SE)
Industry, innovation and infrastructure
Openalex Percentile: Top 92%
Reliability and Maintenance Optimization
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