4 research outputs found
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
Data Visualization Support for Complex Logistics Operations and Cyber-physical Systems
Today, complex logistics operations include different levels of communication and interactions. This paper explores the requirements of these operations and conceptualizes important key performance indicators, stakeholders, and different data visualizations to support the stakeholders in order to understand interactions between entities easier and faster. Three different levels were identified-supply chain, automated warehouse, and intelligent agent-to define the complex logistics operations. For each level, important stakeholders and performance indicators were determined. A case study was designed and described to exemplify the role of cyber-physical systems in complex logistics operations. Moreover, different data visualizations were developed as part of a dashboard to illustrate key performance indicators of different levels for the purpose of supporting stakeholders. This exploratory study concludes by identifying important data necessary for each performance indicator, suggesting ways to collect these data, and exemplifying how data visualization approach can be used through a dashboard design.QC 20180327SCOTT - Secure Connected Trustable Thing
Data visualization support for complex logistics operations and cyber-physical systems
Today, complex logistics operations include different levels of communication and interactions. This paper explores the requirements of these operations and conceptualizes important key performance indicators, stakeholders, and different data visualizations to support the stakeholders in order to understand interactions between entities easier and faster. Three different levels were identified-supply chain, automated warehouse, and intelligent agent-to define the complex logistics operations. For each level, important stakeholders and performance indicators were determined. A case study was designed and described to exemplify the role of cyber-physical systems in complex logistics operations. Moreover, different data visualizations were developed as part of a dashboard to illustrate key performance indicators of different levels for the purpose of supporting stakeholders. This exploratory study concludes by identifying important data necessity for each performance indicator, suggesting ways to collect these data, and exemplifying how data visualization approach can be used through a dashboard design
Data Visualization Support for Complex Logistics Operations and Cyber-physical Systems
Today, complex logistics operations include different levels of communication and interactions. This paper explores the requirements of these operations and conceptualizes important key performance indicators, stakeholders, and different data visualizations to support the stakeholders in order to understand interactions between entities easier and faster. Three different levels were identified-supply chain, automated warehouse, and intelligent agent-to define the complex logistics operations. For each level, important stakeholders and performance indicators were determined. A case study was designed and described to exemplify the role of cyber-physical systems in complex logistics operations. Moreover, different data visualizations were developed as part of a dashboard to illustrate key performance indicators of different levels for the purpose of supporting stakeholders. This exploratory study concludes by identifying important data necessary for each performance indicator, suggesting ways to collect these data, and exemplifying how data visualization approach can be used through a dashboard design.QC 20180327SCOTT - Secure Connected Trustable Thing