Authors:
Christoph Ecker
1
;
Martin Riester
1
and
Sebastian Schlund
2
Affiliations:
1
Fraunhofer Austria Research GmbH, Theresianumgasse 7, Vienna, Austria
;
2
Institute of Management Science, TU Wien, Theresianumgasse 27, Vienna, Austria
Keyword(s):
Intralogistics, Material Flow Optimization, Forklift, LoRaWAN, IPS, Energy Efficiency.
Abstract:
Small batch sizes, increasing variant diversity and short delivery times raise the complexity of intralogistics in manufacturing companies. As a result, these challenges lead to economically- and energy-inefficient material flows. To address this issue, companies conduct material flow optimization. The decisive factor is that the planning often cannot be data driven. This is because there is no or insufficient data on internal material flows and optimization potentials cannot be fully exploited. The aim of this paper is to create economically- and energy-efficient material flows in manufacturing companies. The focus is on the development of a sensor prototype for the localization and utilization measurement of forklifts to close the current data gaps. Based on the current state of the art, the sensor prototype Duck Box is developed. This Indoor Positioning System (IPS) uses LoRa to determine the position of forklifts and an ultrasonic sensor to identify the utilization. The recorded
and in real time analysed data is transmitted to a database via Long Range Wide Area Network (LoRaWAN). Finally, the developed prototype is applied and evaluated in a case study. The results of this sensor-based approach show the significant added value for the economically- and energy-efficient optimization of material flows.
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