Generation of characteristic surfaces for order-picking systems under uncertainty

• Applicants: Professorin Dr. Sonja Kuhnt; Professorin Dr.-Ing. Sigrid Wenzel
• Subject Area: Production Systems, Operations Management, Quality Management and Factory Planning
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 544959882

The research project is based on the research assumption that with a smaller number of simulation runs, simulation-based characteristic surfaces with uncertainty bands can provide comparable statements as simulation studies. Therefore, a methodology is developed with the aim of empirically investigating complex systemic interactions between different logistics parameters (such as load and performance parameters) under consideration of statistical uncertainty to determine optimal operating points. For this purpose, statistical experimental design, meta-modelling, and discrete event simulation are combined. The object of interest of the systemic investigations are order picking systems. The new methodology is based on a classification of order picking systems with the help of representative reference models, a taxonomy of statistical models for logistics performance indicators and their allocation to the reference models as well as the corresponding implementation in simulation models. In addition to the development of the methodology in the sense of a planning assistance, empirical system-theoretical insights into representative order picking systems are gained. To achieve the goals, a classification of order picking systems based on criteria and influence factors as well as representative reference models for order picking will be first developed; the evaluation of these results will be carried out by means of a Delphi study. For the reference models, executable simulation models will be implemented interlinked with the development of a taxonomy for statistical models for the building of characteristic surfaces. With the help of the taxonomy and the simulation models, empirical analyses are carried out to determine fundamental systemic interdependencies for the reference models. The research results obtained are incorporated into the development of a procedure model and the elaboration of checklists as well as rules for application and interpretation. Furthermore, the methodology will be implemented in a software-based demonstrator and a case study-based evaluation will be conducted.

• DFG Programme: Research Grants