Working groups

The working group of the KI-Sustain project focuses on the efficient recycling of post-consumer recyclates. The interdisciplinary approach includes collaboration, cooperation between the Departments of Engineering Management (Stricker) and Mechanical Engineering & Material Science (Taha). This means that expertise in AI methods on the one hand and an understanding of the requirements for recyclates and components in plastics technology on the other are pooled in the project.

The project team consists of two professors, Prof. Dr.-Ing. Nicole Stricker and Prof. Dr.-Ing. Iman Taha, as well as academic staff member Teresa Werner, M. Eng, who specializes in Mechanical Engineering.

The working group of the SKIPS project at the Aalener Institut für Strategic Management (AAUF) focuses on the development and implementation of AI-based solutions for the optimization of corporate management and controlling processes. The research focuses on improving planning, budgeting and forecasting through the use of machine learning (ML) and neural networks (NN), with the aim of increasing forecasting accuracy and enabling well-founded strategic decisions. A unique selling point of the working group is the integration of external data sources and the targeted improvement of internal data quality in order to create a holistic and precise database for business decisions. These innovative approaches are developed specifically for small and medium-sized enterprises (SMEs), family businesses and funds, financial resources and tailored to their specific needs.

The working group is headed by Prof. Dr. habil. Patrick Ulrich, who contributes his extensive 1. science and scholarshop (allgem.) expertise as well as his many years of experience in the Management of research projects and the practical cooperation, cooperative venture, partnership, collaboration with companies in order to realize effective and application-oriented solutions.

The current research project SKIPS aims to integrate AI methods into the planning and forecasting processes of companies and thus significantly improve the accuracy of forecasts. The Ulrich working group is supported by research assistants/associate/fellow Felix Stockert, Benjamin Nothacker and Heinrich Graf Adelmann.

The working group of the FiAZ 2.0 project has its professional origins in the fields (of) computer science and Business Information Systems. As a result, its subject area includes the development of artificial intelligence (AI) for time series as well as special processes, procedures for anomaly detection. Another field of research is the explainability of AI (Explainable AI). As a result, Prof. Dr. Andreas Theissler and Prof. Dr. Manfred Rössle combine both in-depth field-specific, subject-area specific, subject-specific know-how, underlined by numerous publications, and several years of experience in the Management of research projects.

With the project "Transferable Framework for Interpretable Anomaly Detection for Industrial Time Series 2.0" (FiAZ 2.0), the FiAZ project for the transparent and comprehensible detection of unusual patterns is being continued. FiAZ 2.0 focuses specifically on water, energy supply and the circular economy in order to improve their sustainability and efficiency. The aim is to develop a user-friendly framework that is understandable and usable even without special expert knowledge in the field (of) artificial intelligence. Manuel Wengert is supporting the project as a research assistant/associate/fellow.