Domain modeling for scenario sensing and edge decision-making

Shi, Haoran; Liu, Shijun; Pan, Li

doi:10.1109/edge60047.2023.00028

2023 IEEE International Conference on Edge Computing and Communications (EDGE) 2023

DOI: 10.1109/edge60047.2023.00028

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Domain modeling for scenario sensing and edge decision-making

Haoran Shi,

Shijun Liu,

Li Pan

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2024

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A Meta-Model Architecture and Elimination Method for Uncertainty Modeling

Shi,

Liu,

Pan

2024

IET Software

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Uncertainty exists widely in various fields, especially in industrial manufacturing. From traditional manufacturing to intelligent manufacturing, uncertainty always exists in the manufacturing process. With the integration of rapidly developing intelligent technology, the complexity of manufacturing scenarios is increasing, and the postdecision method cannot fully meet the needs of the high reliability of the process. It is necessary to research the pre-elimination of uncertainty to ensure the reliability of process execution. Here, we analyze the sources and characteristics of uncertainty in manufacturing scenarios and propose a meta-model architecture and uncertainty quantification (UQ) framework for uncertainty modeling. On the one hand, our approach involves the creation of a meta-model structure that incorporates various strategies for uncertainty elimination (UE). On the other hand, we develop a comprehensive UQ framework that utilizes quantified metrics and outcomes to bolster the UE process. Finally, a deterministic model is constructed to guide and drive the process execution, which can achieve the purpose of controlling the uncertainty in advance and ensuring the reliability of the process. In addition, two typical manufacturing process scenarios are modeled, and quantitative experiments are conducted on a simulated production line and open-source data sets, respectively, to illustrate the idea and feasibility of the proposed approach. The proposed UE approach, which innovatively combines the domain modeling from the software engineering field and the probability-based UQ method, can be used as a general tool to guide the reliable execution of the process.

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A Meta-Model Architecture and Elimination Method for Uncertainty Modeling

Shi,

Liu,

Pan

2024

IET Software

Self Cite

View full text Add to dashboard Cite

show abstract

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Domain modeling for scenario sensing and edge decision-making

Cited by 1 publication

References 20 publications

A Meta-Model Architecture and Elimination Method for Uncertainty Modeling

A Meta-Model Architecture and Elimination Method for Uncertainty Modeling

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