Uml as a Basis to Model Autonomous Production Systems

Scholz‐Reiter, Bernd; Kolditz, Jan; Hildebrandt, Torsten

doi:10.1007/978-0-387-49864-5_65

Cited by 4 publications

(6 citation statements)

References 2 publications

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“…In this context, the Autonomous Logistics Engineering Methodology (ALEM) offers a procedure model for configuring autonomous logistic processes and their infrastructure. The process mapping is based on a view concept that distinguishes between five views of modeling (Scholz-Reiter et al 2007b). The "structure view" contains the representation of the logistic objects as well as their interrelationships.…”

Section: Engineering Methodology For Autonomous Logistic Processesmentioning

confidence: 99%

“…The "process view" is used to model the logical and temporal sequence of activities and states of the logistic objects. Finally, the "communication view" focuses on the content and temporal sequence of the information exchange between the logistic objects (Scholz-Reiter et al 2007b). The notation within the described views is based on the Unified Modeling Language (UML).…”

Section: Engineering Methodology For Autonomous Logistic Processesmentioning

confidence: 99%

“…The simulation environment uses a C++ class library for the discrete-event simulation of communication networks (Becker et al 2006). With the Autonomous Logistics Engineering Methodology (ALEM), a framework for the modeling of autonomous logistic processes and their infrastructure was developed (Scholz-Reiter et al 2007b).…”

Section: Modeling Approachesmentioning

confidence: 99%

See 2 more Smart Citations

Autonomous Control of Logistic Processes: A Retrospective

Schukraft

Teucke

Freitag

et al. 2021

Dynamics in Logistics

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Manufacturing and logistic service companies are increasingly confronted with high dynamics and complexity. Due to its particular suitability for short-term and situation-dependent decision-making, autonomous control can improve planning and control of production and related transportation processes. This chapter gives an overview of the research that the BIBA—Bremer Institut für Produktion und Logistik GmbH has performed over the past years in the field of autonomously controlled production and transportation networks. The chapter focuses on the modeling approaches and the autonomous control methods that have been developed. These methods have been evaluated using both theoretical and real-world scenarios. The results show the applicability and suitability of autonomous control in complex and dynamic production and transportation environments. In addition, influences on the methods’ performance and the integration of autonomous control into conventional planning and control systems are discussed. Finally, the chapter looks at the significance of autonomous control in the context of Industry 4.0 and shows the relations between both concepts.

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Section: Engineering Methodology For Autonomous Logistic Processesmentioning

confidence: 99%

Section: Engineering Methodology For Autonomous Logistic Processesmentioning

confidence: 99%

See 1 more Smart Citation

Autonomous Control of Logistic Processes: A Retrospective

Schukraft

Teucke

Freitag

et al. 2021

Dynamics in Logistics

Self Cite

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“…Further, autonomous logistic systems require decision alternatives. These can be achieved by reserve machinery capacity or branches within product structures, for example [13].…”

Section: Autonomous Controlmentioning

confidence: 99%

Modeling of orders in autonomously controlled logistic systems

Scholz‐Reiter

Sowade

Hildebrandt

et al. 2010

Prod. Eng. Res. Devel.

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The paper extends the Autonomous Logistics Engineering Methodology (ALEM) by a deeper understanding of immaterial logistic objects to trigger manufacturing processes. Further, a hierarchical modeling concept is introduced to split customer orders logically into partial orders, which run directly at the shop floor level. Each partial order consists of certain manufacturing steps. The amendments enable adequate modeling of autonomous manufacturing processes. The research is a further step to integrate autonomously controlled processes in logistics.

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“…For example, knowledge maps, a layout diagram, and product structure diagrams have been added [11], [13]. ALEM applies a view concept in order to deal with the complexity of its models [6], [14].…”

Section: B Modeling Autonomuos Contolled Processesmentioning

confidence: 99%

Configuring the Infrastructure of Autonomous Logistics' Control Systems

Scholz‐Reiter

Sowade

Rippel

2011

2011 IEEE Ninth International Symposium on Parallel and Distributed Processing With Applications Workshops

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Abstract-Autonomous control is a suitable concept in order to increase the flexibility and robustness of logistic systems by enabling decentralized decision-making and execution at the system elements. However, design of the corresponding control system's infrastructure is complex due to a high number of possible configurations. Further, logistic process experts have to consider several domain specific functional and nonfunctional requirements. Thereto, this paper introduces a three-phase procedure model, which guides logistics experts through the configuration process of the infrastructure of autonomous logistics' control systems. The model employs general design concepts of procedure models and composes them to a new, application area specific model that fits the needs of autonomously controlled logistic systems. Autonomous Logistic Control System, Infrastructure Configuration, Procedure Model

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Uml as a Basis to Model Autonomous Production Systems

Cited by 4 publications

References 2 publications

Autonomous Control of Logistic Processes: A Retrospective

Autonomous Control of Logistic Processes: A Retrospective

Modeling of orders in autonomously controlled logistic systems

Configuring the Infrastructure of Autonomous Logistics' Control Systems

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