Research

The Professorship of Business Administration, especially Procurement and Production, is integrated into the Institute of Quantitative Logistics at the Faculty of Economics and Social Sciences at the Helmut Schmidt University/University of the Federal Armed Forces Hamburg. Its research focuses on the development and application of quantitative methods in Operations Research to support management decisions and to automate industrial processes in procurement, production and logistics.

Research topics

Our research includes both applied and theoretical topics, particularly in the following areas:

  • Container logistics
    The use of standardized loading units, especially containers, is an essential element of modern intermodal logistics processes. Transshipment terminals form an important interface within and between different modes of transport. In this context, we are particularly interested in process optimization at seaports and inland ports. Examples include positioning and restacking strategies for the efficient usage of storage blocks, the scheduling of vehicles and cranes used to move containers within a terminal, or an integrated examination of multiple planning problems.
  • New technologies in intermodal transport
    The use of unmanned aerial vehicles and other autonomous vehicles in intermodal transport allows for increased flexibility and automation of a wide range of processes. The application of these technologies is no longer just a vision of the future, but a rapidly growing, interdisciplinary research area that gives rise to a wide range of exciting research projects.
  • Production scheduling
    As a traditional field of research in the area of production management, scheduling is concerned with the allocation of limited resources (machines, personnel, tools, etc.) to production processes. Numerous questions in theory and practice, current developments in the field of process automation (e.g. real-time data collection via sensors), as well as the continuing digitalization and the resulting increasing data volume, are constantly posing new and exciting research questions.
  • Integration of game theoretic aspects intio classical optimization problems
    We integrate and analyze game theoretic concepts, especially in the area of competeitive location planning (leader-follower problems) and scheduling (mechanism design in machine scheduling).

Publications, Talks, Conferences

Detailed information on our publications and talks is available on the team sites:

Research Projects

Current Projekts

Data-driven Optimization Techniques for Integrated Process Planning and Scheduling

Project Description

The focus of this project is on optimization and automation of process planning and scheduling in a make-to-order setting. Manufacturing a specific product can be done in several different ways, using a wide range of manufacturing technologies and various flexible (equipped with a set of tools) and autonomous, non-identical machines in different processing steps. Some machines need to be operated by highly qualified human operators. Decisions to be made are, among others, the selection of a process plan to produce each work piece, the machine to perform each processing step, predicting processing time, and scheduling of a heterogeneous workforce, just to name a few.

Manufacturing production has to be altered in order to cope with market and technology changes. Production systems must be capable of reacting quickly to disturbances as well as to failures of machines and processes. This capability is achieved by using available technology alternatives and real-time re-calculation of production routes based on robust production plans. Data analytics and artificial intelligence will permit to retrieve relevant information from unstructured data. The generated information will define the basis for continuous improvement and learning.

Our main steps towards automating production planning are data collection, model building, design learning of (exact) robust methods and finally, transfer into practice.

Funding

DFG

Details

Completed Projects

Sustainable Personnel Planning in Highly Customized Assembly Lines with Work Sharing (SuPerPlan)

Project Description

In SuPerPlan, we study paced mixed-model assembly lines (MALs) where highly customized products are processed by human operators. We will analyze concepts of planning the work of operators at such lines, build appropriate models and develop new algorithms, which aim at enhancing both economic and social sustainability of these assembly lines. We believe that this can be achieved by performing some tasks in an alternating or collaborative manner by groups of workers according to rules specified by the planners. This form of organization is referred to as work sharing. We identify three types of work sharing that enable companies to enrich work assignment, to reduce ergonomic risks and the variance of job completion times, and thus help enterprises to customize their product range and produce available to promise. However, work sharing adds additional complexity to the planning of assembly lines.

Work sharing at MALs has barely been investigated in the past, resulting in a significant research gap. Moreover, an appropriate methodological support for managers is currently missing. To bridge this gap, SuPerPlan investigates the impact of work sharing on planning in a plentitude of settings in MALs, such as personnel planning, assembly line design, or assembly line balancing and scheduling. We will extract optimization problems and develop suitable solution algorithms that integrate different aspects of work sharing of different types. One of our major challenges will be coping with the increase of complexity due to taking work sharing into account, as most of the optimization problems are already computationally intractable when work sharing is not considered.

Our planning procedures will take aspects of social sustainability into account, such as individual skills, equitable distribution of labor, and ergonomic risks. The attention will be centered on considering the assembly line stem personnel as opposed to temporary workers. We also intend to design participative planning approaches in the form of mechanisms that take into account preferences of workers. These planning algorithms must be transparent and have a disincentive effect to possible selfish manipulations. We believe that the results of this project will bring a positive social impact to the society by improving working conditions at assembly lines and enhancing product customization at a large number of enterprises.

Funding

DFG

Details

Echtzeitnahes kollaboratives Planen und Optimieren (EKPLO), in German

Project Description

Ausgangslage:
Durch die von der Vision “Industrie 4.0” angestoßene und vorangetriebene, echtzeitnahe Erfassung von Prozess- und Kontextdaten sowie deren Verarbeitung, ist die Komplexität von Advanced Planning and Scheduling (APS) Systemen deutlich gestiegen. Ergebnisse und Pläne, die von Optimierungsverfahren „berechnet“ werden, können häufig von den Verantwortlichen nicht mehr nachvollzogen werden. Sie werden daher oft nicht akzeptiert und durch herkömmliche Pläne ersetzt bzw. mit historisch gewachsenen Praktiken umgangen.

Projektziel:
Ziel des Projektes EKPLO ist es, die Potentiale von APS Systemen – insbesondere für kleine und mittelständische Unternehmen – unter der besonderen Berücksichtigung der Mitarbeiter als entscheidende Akteure bei der (wertschöpfungskettenübergreifenden) Auftrags- und Ressourcenplanung nutzbar zu machen. Das entstehende System nennen wir Human-Centered APS (HAPS).

Vorgehen und Innovation:
In EKPLO wird ein klassisches APS-System durch Funktionalitäten zur Visualisierung der APS-Algorithmen, zur Kommunikations- und Kollaborationsunterstützung, sowie zur endnutzerfreundlichen Anpassung der APS-Algorithmen ergänzt. Dies soll wesentlich zur Verringerung der Komplexität, zur besseren Unterstützung der Mitarbeiter im echtzeitnahen Daten- und Entscheidungskontext, sowie zur schnellen Anpassung des Systems durch sowohl die Anwender einerseits, als auch durch die Entwickler andererseits, beitragen.
Die Innovation dieses Projektes bzw. des neuartigen Systems liegt in der einzigartigen Kombination verschiedener, häufig voneinander getrennter Forschungs- und Anwendungsbereiche. Hierdurch und durch eine agile Vorgehensweise bei der Projektdurchführung, entsteht ein holistischer Ansatz zur Bewältigung dieser sozio-technischen, intra- aber auch interorganisationalen Aufgabenstellung.

Im Teilprojekt Human-Centered Scheduling Algorithms (HCSA) werden unter der Leitung von Dr. Dominik Kreß und in enger Zusammenarbeit mit den Kooperationspartnern APS-Algorithmen (weiter-) entwickelt und bedarfsgerecht angepasst. Gleichzeitig erarbeitet das Team Techniken zur Algorithmenvisualisierung und -manipulation.

Anmerkung:
Das Projekt wurde am Lehrstuhl für Wirtschaftsinformatik, Betriebliche Anwendungs- und Entscheidungsunterstützungssysteme, der Universität Siegen durchgeführt.

Funding

(European Union, North Rhine-Westphalia)

EFRE
EFRE

Details

HSU

Letzte Änderung: 29. November 2024