Research Team Supply Chain Digitalization

Digitalization is ubiquitous, and thus supply chains are thoroughly disrupted by its emerging phenomena, such as Industrie 4.0 and Big Data. Within the first research area of Supply Chain Digitalization, the chair wants to meet the challenges that come with it, identify, and exploit opportunities that arise. To achieve this, the chair conducts research on emerging trends such as Supply Chain Performance Measurement, Production Planning under Industrie 4.0 and Predictive Maintenance and investigates how supply chain digitalization can facilitate through the means of Computational Intelligence and Supply Chain Analytics.

The research team Supply Chain Digitalization (fLTR):

Research

  • Predictive Maintenance, Prognostics and Health Management
  • Supply Chain Analytics, Machine Learning for Transport Planning
  • Optimization and Analytics, Automated Design of Optimizers for Supply Chain Planning
  • Performance Measurement Sytems, Performance Measures
  • Supply Chain Risk Management

Teaching of ST 2022

Bachelor

  • BA-VM Digital Supply Chain
    The increasing digitalization offers high potential to increase processes' efficiency, improve decision-making or develop new business models within supply chain management (SCM). However, its implementation confronts companies with high challenges - technical and non-technical ones. This module deals with digitalization's opportunities for SCM. In its first phase, lectures will provide you with basic knowledge on SCM and digitalization. The second phase will require each participant to focus on a specific application area or technology and write a seminar thesis about it.
  • BA-PS Digital Warehouse Twin
    A digital twin describes a virtual copy of a physical object. Such a digital twin can then be used to conduct planning or simulation studies and predict future system behavior. Our project partner Arvato, one of the largest providers of logistics services in Germany, already uses such digital twins of warehouses to enable, for example, ideal route planning. However, changes in the department store are currently only updated manually in the digital twin. Within this project seminar, the goal is to identify technologies and develop methods that simplify the creation and maintenance of digital twins for Arvato's warehouses.
  • BA/MA-PS One.Cockpit: Data Self-Services
    Over the course of time, our project partner has accumulated various applications, and this variety and the various UI concepts are too complex for the user to understand. A first goal is, therefore, to clean up the existing application landscape and to consolidate all “data applications” on one platform. For this purpose, various use cases are currently being collected and analyzed with regard to data sources, complexity of the business logic and sales potential, etc. In a second step, the project partner also wants to establish new, data-driven products and services for German / EU retail. They have already collected various studies and ideas on this but are still beginning.

Master

  • MA-CS Digitalization for Sustainable Supply Chains
    In recent years, customers and governments have increased the pressure on companies to turn their operations into more environmentally and socially friendly ones. However, companies are not isolated entities and use many resources from different suppliers as well as sell through various channels. Therefore, becoming more sustainable is a complex task, which is not realizable only by means of traditional and local initiatives. To overcome such issues in a world that is every day becoming more digital, it is necessary to invest in disruptive technologies and to strengthen collaboration along the whole supply chain. In this context, the present seminar should investigate digital transformation aspects around the topic of sustainability in supply chains. Despite benefits and opportunities given by the digitalization of businesses, there is little research on how and to which extent digital technologies can support environmental and social sustainability.
  • MA-PS Digitalization AeroTech 
    The manufacturing of airplanes is a special sector that deals with parts in low lot-sizes, but with very high quality requirements. On a glance, this seems like an ideal field for the application of Industry 4.0 related technologies. Nevertheless, actors in this sector are often rather conservative when introducing new technologies, often due to the high demands in regulation and documentation. In this project seminar, we work together with the consultancy psX and the aero-tech supplier Deharde to support Deharde on their road towards a more digitalized production environment. Therefore, we will apply Enterprise Architecture Management techniques, assess the as-is state of the production plant and identify potentials and solutions that would lead to the “maximum recommendable degree of digitalization”.
  • MA-PS Data-driven Transport Planning
    Due to factors such as globalization or rising e-commerce, freight transport becomes even more important. Of special relevance is the transport via road due to a demand for fast and flexible delivery as well as road’s direct access to customers. However, road transport planning has to cope with various challenges, e.g., demand volatility, cumbersome business processes or driver shortage. Increasingly collected and stored data might offer potential to find ways to deal with those challenges. Hence, the central idea of this project seminar, which will be conducted in cooperation with Hellmann Worldwide Logistics, is to analyze existing data to find improvement potential for transport planning. Aspects to consider are e.g. patterns regarding delays and capacity utilization or identification of geographical areas for customer leads.
  • BA/MA-PS One.Cockpit: Data Self-Services
    Over the course of time, our project partner has accumulated various applications, and this variety and the various UI concepts are too complex for the user to understand. A first goal is, therefore, to clean up the existing application landscape and to consolidate all “data applications” on one platform. For this purpose, various use cases are currently being collected and analyzed with regard to data sources, complexity of the business logic and sales potential, etc. In a second step, the project partner also wants to establish new, data-driven products and services for German / EU retail. They have already collected various studies and ideas on this but are still beginning.

Teaching of WT 2021/22

Bachelor

  • BA-PS  Advanced Service Parts Forecasting
    Spare parts are characterized by sporadic and intermittent demands that make prediction difficult. Although many algorithms, from exponential smoothing to Croston's method, have been researched, often only the simplest methods are used in practice. Besides the complexity of accurate algorithms, the implementation and embedding in a wide enterprise landscape is a major difficulty. Furthermore, new potentials arise from artificial intelligence methods and new data sources (e.g. sensors). This project seminar deals with the development of a future concept for spare parts forecasting, which can exploit the unused potentials, taking into account the numerous difficulties of spare parts demand forecasting.

Master

  • MA-PS Predictive Maintenance for AIOps
    The emergence of digitalization results in the need for IT operations to become more flexible and adapt to new infrastructure. AIOps (Artificial Intelligence for IT Operations) are a new approach to IT operations considering big data and machine learning as its central components. A reliably working infrastructure is essential for a successful application of AIOps. Hence, this project seminar focuses on the idea to apply predictive maintenance to IT infrastructure. The project is conducted in cooperations with IQ-optimize.

  • MA-PS Data Analytics for Supply Chain Performance Measurement 
    Today’s business environment requires supply chains to be proactive rather than reactive, demanding a new approach for supply chain performance measurement systems (SCPMS) which includes data analytics. This project seminar addresses the topic of data analytics-driven SCPMS (DA-SCPMS) focusing on forecast scenarios for supporting both the identification and management of complex and uncertain decision-making. Students collaborating with this seminar are expected to design and implement a DA-SCPMS prototype in the context of forecast scenarios in cooperation with thyssenkrupp Materials Services GmbH.

  • MA-CS Supply Chain Analytics
    Due to emerging technologies, storing and processing more data than ever before becomes possible. Hence, (big) data analytics gains currency over various industries. Supply Chain Management also starts to apply data analytics to gain new insights, adapt processes or even optimize the supply chain. However, implementing analytics is not an easy endeavour and various challenges need to be tackled before reaping the expected benefits.
    This seminar will look into supply chain analytics (SCA) and discuss it from various views. Topics both include application cases of SCA and issues surrounding the implementation process such as necessary capabilities.

Available theses

We offer various topics in the areas of our past theses, which can be seen here:

If you are interested in one of these areas, you can write a mail to the corresponding person, and we will work out a topic together!

Selected publications

  • Hellweg, F., Lechtenberg, S., Hellingrath, B., & Thomé, A. M. T. (2021). Literature Review on Maturity Models for Digital Supply Chains. Brazilian Journal of Operations & Production Management. (Accepted)
  • Wagner, C., & Hellingrath, B. (2021). Supporting the Implementation of Predictive Maintenance — a Process Reference Model. International Journal of Prognostics and Health Management, Vol. 12(002).
  • Wesendrup, K., & Hellingrath, B. (2020). A Process-based Review of Post-Prognostics Decision-Making. In Proceedings of the 5th European Conference of the PHM Society, Virtual.
  • Mello, R., Hellingrath, B., & Martins, R. (2019). Big Data Analytics in Supply Chain Performance Measurement Systems. In Proceedings of the 26th International Annual European Operations Management Association Conference, Helsinki, Finland.

Project partners