Conceptual Design of a Decision Support System for Material Flow Planning and its Transfer to Public Transport

Abstract

The lack of data-based decision-making prevents the creation of efficient, technically, and organizationally optimal material flows in intralogistics. This paper aims to develop a concept for a decision support system for optimizing forklift material flows based on sensor data. On the one hand, the efficiency and the data-drivenness of material flow planning shall be increased. On the other hand, a contribution to reducing logistics and material flow costs in manufacturing companies should be achieved. First, related works in sensor-based decision support for material flow planning are discussed. Then, a sensor-based concept of a decision support system for optimizing internal material flows of forklifts in manufacturing companies is developed. This concept consists of three layers. The data layer collects, prepares, and stores the required sensor data and additional constraints. The model layer integrates operations research methods to analyze, evaluate, and optimize internal material flows regarding the layout arrangement of sources and sinks, the forklift deployment and the order allocation, and the selection of optimal forklift types including proven automation. The knowledge layer prepares and visualizes the planning results to enable efficient and data-driven decisions by the planning team. In addition, the transfer to public transport is performed during the Öffi-Packerl research project. It is demonstrated that the transfer of industrial management methods to areas of application outside of production and logistics is possible. Partially, they must be adapted, but they still contribute to a significant added value outside of factories.