Deployment of an Distributed Strategic Material Flow Control for Automated Material Flow Systems Consisting of Autonomous Modules

The modularisation of hardware and software is one approach to handle the demand for increasing flexibility and changeability of automated material flow systems that are, for example, utilised in flexible production systems. In such automated material flow systems, autonomous modules communicate with each other to coordinate and execute transport tasks. In this paper a strategic material flow control is introduced, which is distributed on several modules realised with a multi-agent system. The strategic material flow control agent coordinates transport tasks with advanced logistical requirements, such as sequencing. A transport task states for a transport unit the system source and sink together with arrival criteria at the sink, e.g. sequence In order to fulfil the arrival criteria the strategic material flow agent selects additional destinations within the automated material flow system to buffer a transport unit. For the selection of suitable buffer modules, several strategies are proposed and evaluated in a simulation study

Deployment of an Distributed Strategic Material Flow Control for Automated Material Flow Systems Consisting of Autonomous Modules

Poster 1

Design, Application and Evaluation of a Multi Agent System in the Logistics Domain

The increasing demand for flexibility of automated production systems also affects the automated material flow systems (aMFS) they contain and demands reconfigurable systems. However, the centralized control concept usually applied in aMFS hinders an easy adaptation, as the entire control software has to be re-tested, when manually changing sub-parts of the control. As adaption and subsequent testing are a time-consuming task, concepts for splitting the control from one centralized to multiple, decentralized control nodes are required. Therefore, this paper presents a holistic agent-based control concept for aMFS, whereby the system is divided into so-called automated material flow modules (aMFM), each being controlled by a dedicated module agent. The concept allows the reconfiguration of aMFS, consisting of heterogeneous, stationary aMFM, during runtime. Furthermore, it includes aspects such as uniform agent knowledge bases through metamodel-based development, a communication ontology considering different information types and properties, strategic route optimization in decentralized control architecture and a visualization concept to make decisions of the module agents comprehensible to operators and maintenance staff. The evaluation of the concept is performed by means of material flow simulations as well as a prototypical implementation on a lab-sized demonstrator.Comment: 13 pages, https://ieeexplore.ieee.org/abstract/document/9042827

Efficient Messaging through Cluster Coordinators in Decentralized Controlled Material Flow Systems

The modularization of the hard- and software is one approach handling the demand for increasing flexibility and changeability of automated material flow systems. A control that is distributed across several different hardware controllers leads to a great demand for coordination between the modules while planning for example transports, especially if there is a mutual dependency between the modules on the executing tasks. Short-term changes in planning often initiate a rescheduling chain reaction, which causes a high communication load in the system. In the presented approach, module clusters with a centralized coordinator are automatically formed out of multiple modules and substitutional take over the surrounding communication for the modules. As a result, they minimize exchanged messages by focusing on the essential information

Efficient Messaging through Cluster Coordinators in Decentralized Controlled Material Flow Systems

The modularization of the hard- and software is one approach handling the demand for increasing flexibility and changeability of automated material flow systems. A control that is distributed across several different hardware controllers leads to a great demand for coordination between the modules while planning for example transports, especially if there is a mutual dependency between the modules on the executing tasks. Short-term changes in planning often initiate a rescheduling chain reaction, which causes a high communication load in the system. In the presented approach, module clusters with a centralized coordinator are automatically formed out of multiple modules and substitutional take over the surrounding communication for the modules. As a result, they minimize exchanged messages by focusing on the essential information