6 papers
End-to-End Data Quality-Driven Framework for Machine Learning in Production Environment
Firas Bayram, Bestoun S. Ahmed, Erik Hallin
This paper introduces a novel end-to-end framework that efficiently integrates data quality assessment with machine learning (ML) model operations in real-time production environme…
Smart Manufacturing: MLOps-Enabled Event-Driven Architecture for Enhanced Control in Steel Production
Bestoun S. Ahmed, Tommaso Azzalin, Andreas Kassler +2
We explore a Digital Twin-Based Approach for Smart Manufacturing to improve Sustainability, Efficiency, and Cost-Effectiveness for a steel production plant. Our system is based on…
Quality Assurance for LLM-RAG Systems: Empirical Insights from Tourism Application Testing
Bestoun S. Ahmed, Ludwig Otto Baader, Firas Bayram +2
This paper presents a comprehensive framework for testing and evaluating quality characteristics of Large Language Model (LLM) systems enhanced with Retrieval-Augmented Generation…
Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach
Firas Bayram, Bestoun S. Ahmed
Artificial intelligence (AI), and especially its sub-field of Machine Learning (ML), are impacting the daily lives of everyone with their ubiquitous applications. In recent years,…
Adaptive Data Quality Scoring Operations Framework using Drift-Aware Mechanism for Industrial Applications
Firas Bayram, Bestoun S. Ahmed, Erik Hallin
Within data-driven artificial intelligence (AI) systems for industrial applications, ensuring the reliability of the incoming data streams is an integral part of trustworthy decisi…
An Adaptive Metaheuristic Framework for Changing Environments
Bestoun S. Ahmed
The rapidly changing landscapes of modern optimization problems require algorithms that can be adapted in real-time. This paper introduces an Adaptive Metaheuristic Framework (AMF)…