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Development of an IoT-based inventory management solution and training module using smart bins

  • Flexibility, transparency and changeability of warehouse environments are playing an increasingly important role to achieve a cost-efficient production of small batch sizes. This results in increasing requirements for warehouses in terms of flexibility, scalability, reconfigurability and transparency of material and information flows to deal with large number of different components and variable material and information flows due to small batch sizes. Therefore, an IoT-based inventory management solution and training module has been developed, implemented and validated at Werk150 – the Factory on campus of the ESB Business School. Key elements of the developed solution are smart bins using weight mats to track the bin’s content and additional sensors and buttons which are connected to an IoT – Hub to collect data of material consumption and manual handling operations. The use of weight mats for the smart bins offers the possibility to measure the container content independent of the specific component geometry and thus for a variety of components based on the specific component weights. The developed solution enables focusing on key for success elements of the system to provide synchronization of the flow of materials and information resulting an increase of flexibility and significantly higher transparency of the material flow. AIbased algorithms are applied to analyse the gathered data and to initiate process optimizations by providing the logistics decision makers a profound and transparent basis for decision making. In order to provide students and industry visitors of the learning factory with the necessary competences and to support the transfer into practice, a training module on IoT-based inventory management was developed and implemented.

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Author of HS ReutlingenChukomin, Alexander; Hummel, Vera; Schuhmacher, Jan
Erschienen in:Proceedings of the 13th Conference on Learning Factories (CLF 2023), 9-11 May 2023, Reutlingen University, Germany
Place of publication:Rochester, NY
Document Type:Conference proceeding
Publication year:2023
Tag:AI; IoT; TOC; bottlenecks; intralogistic; inventory management; material flow; smart bins; training module
Page Number:7
DDC classes:004 Informatik
Open access?:Ja
Licence (German):License Logo  Open Access