AWS-Institute for Digitized Products and Processes

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

The growing availability of structured battery databases opens new opportunities for data‐driven quality control in battery manufacturing. Efficient identification of anomalous cells is critical for ensuring safety, performance, and longevity. In this work, we present a machine‐l...

Analyzing structural and semantic similarities between formal business process models using ChatGPT-5.1: a test report

Abstract Large Language Models (LLMs) are emerging as a promising tool in Business Process Management for comparing and validating process models. In this study, we evaluated an LLM’s ability to compare reference models with systematically modified variants representing typical m...