Strategies for the Coupling of Autonomous Control and Central Planning: Evaluation of Strategies Using Logistic Objectives Achievement and Planning Adherence

Schukraft, Susanne; Grundstein, Sebastian; Freitag, Michael; Scholz‐Reiter, Bernd

doi:10.1109/smc.2015.34

Cited by 3 publications

(1 citation statement)

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“…In addition, compared to classical optimization approaches, the DLRP t offers extended degrees of freedom and variability, e.g., object individual decision functions (Rekersbrink and Wenning 2011). Schukraft et al (2015) applied different coupling strategies for the combined application of conventional planning and autonomous control methods in a shopfloor scenario similar to Scholz-Reiter et al (2010a). Depending on the extent of autonomous control for decision-making, these strategies can be rated from a low to a high level of autonomy.…”

Section: Autonomous Control and Conventional Planning And Controlmentioning

confidence: 99%

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: Autonomous Control and Conventional Planning And Controlmentioning

confidence: 99%