PSI - Issue 75

Available online at www.sciencedirect.com Structural Integrity Procedia (2025) 000 – 000 Available online at www.sciencedirect.com ScienceDirect

www.elsevier.com/locate/procedia

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Procedia Structural Integrity 75 (2025) 72–84

Fatigue Design 2025 (FatDes 2025) Optimized specifications from mission profile campaigns and data management tool Sébastien Boudevin a , Denis Chojnacki a , Amaury Chabod b , Nicolas Sias b *, a CETIM, 52, Avenue Félix - Louat - CS 80067, 60304 Senlis Cedex,France b HOTTINGER BRUEL & KJAER France SAS, 2-4 rue Benjamin Franklin, 94370 Sucy-en-brie, FRANCE

© 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under the responsibility of Dr Fabien Lefebvre with at least 2 reviewers per paper Abstract The progressive electrification of many types of machinery (agricultural, construction machines, etc.) is already engaged, whether for environmental requirements reasons, standards or efficiency. This transformation is most often achieved through the selection of components intended for a different primary use in terms of products (e.g. automotive). This on-going electrification leads to changes in technology, structure, design and final user behavior. In contrast with existing technologies, where standards may give guidelines, electric powertrain and its integration in complete new products requires new specification inputs. This raises a number of potential issues, such as the durability/safety of these components in another environment (e.g. telescopic handlers, excavators) and the overall product energy efficiency. As a result, customer usage in different life situations may result in a massive production of measurements. These variations must be finely understood with a dedicated infrastructure, which me rges data storage, indexation and ability to achieve request with a good agility, and raw signals analysis tools, to calculate metrics. The Big Data environment enables to merge a variety of data, provide automatized analysis, up to a request-based dynamic dashboard. © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Fatigue Design 2025 organizers Keywords: Data Lake, Big Data, Electrification, Uncertainty quantification, Mission Profile

* Corresponding author. Tel.: +33682596914. E-mail address: Denis.Chojnacki@cetim.fr

2452-3216 © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Fatigue Design 2025 organizers

2452-3216 © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under the responsibility of Dr Fabien Lefebvre with at least 2 reviewers per paper 10.1016/j.prostr.2025.11.009