arXiv Open Access 2025

Industrial AI Robustness Card: Evaluating and Monitoring Time Series Models

Alexander Windmann Benedikt Stratmann Mariya Lyashenko Oliver Niggemann

Lihat Sumber

Abstrak

Industrial AI practitioners face vague robustness requirements in emerging regulations and standards but lack concrete, implementation ready protocols. This paper introduces the Industrial AI Robustness Card (IARC), a lightweight, task agnostic protocol for documenting and evaluating the robustness of AI models on industrial time series. The IARC specifies required fields and an empirical measurement and reporting protocol that combines drift monitoring, uncertainty quantification, and stress tests, and it maps these to relevant EU AI Act obligations. A soft sensor case study on a biopharmaceutical fermentation process illustrates how the IARC supports reproducible robustness evidence and continuous monitoring.

Topik & Kata Kunci

cs.CY cs.AI

Penulis (4)

Alexander Windmann

Benedikt Stratmann

Mariya Lyashenko

Oliver Niggemann

Format Sitasi

APA MLA BibTeX

Windmann, A., Stratmann, B., Lyashenko, M., Niggemann, O. (2025). Industrial AI Robustness Card: Evaluating and Monitoring Time Series Models. https://arxiv.org/abs/2512.11868

Akses Cepat

Lihat di Sumber

Informasi Jurnal

Tahun Terbit: 2025
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓