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Development and implementation of an autonomous control system for target-optimised use of intralogistics transport systems in the Learning Factory Werk 150 at Reutlingen University

  • Rapidly changing market conditions and global competition are leading to an increasing complexity of logistics systems and require innovative approaches with respect to the organisation and control of these systems. In scientific research, concepts of autonomously controlled logistics systems show a promising approach to meet the increasing requirements for flexible and efficient order processing. In this context, this work aims to introduce a system that is able to adjust order processing dynamically, and optimise intralogistics transportation regarding various generic intralogistics target criteria. The logistics system under consideration consists of various means of transport for autonomous decision-making and fulfilment of transport orders with defined source-sink relationships. The context of this work is set by introducing the Learning Factory Werk 150 with its existing hardware and software infrastructure and its defined target figures to measure the performance of the system. Specifically, the important target figures cost and performance are considered for the transportation system. The core idea of the system’s logic is to solve the problem of order allocation to specific means of transport by linking a Genetic Algorithm with a Multi-Agent System. The implementation of the developed system is described in an application scenario at the learning factory.

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Author of HS ReutlingenGroße Erdmann, Julian; Hummel, Vera; Schuhmacher, Jan
Erschienen in:Procedia manufacturing
Place of publication:Amsterdam
Document Type:Journal article
Publication year:2020
Tag:autonomous control systems; intralogistics; target optimisation; transport systems
Issue:Learning Factories across the value chain – from innovation to service – The 10th Conference on Learning Factories 2020
Page Number:6
First Page:405
Last Page:410
DDC classes:620 Ingenieurwissenschaften und Maschinenbau
Open access?:Ja
Licence (German):License Logo  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International