Modeling a drilling control system, as a Discrete-Event-System

Saadallah, Nejm; Meling, Hein; Daireaux, Benoît

doi:10.1109/ccca.2011.6031461

Cited by 2 publications

(1 citation statement)

References 10 publications

(16 reference statements)

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“…Furthermore, UML is unable to capture the concurrency in DES and has no similar modeling concept of PN tokens, which can be used to model object movements and the physical flow and information flow of IoT objects. The language of PN is also larger than automata language and thus PN can model a larger set of system than automata does (Saadallah et al , 2011). PN has been proven to be an effective system-modeling tools to model and analyze DES and distributed manufacturing system (Hsu et al , 2003; Xu and Shatz, 2003; Lv and Lin, 2017).…”

Section: Iot Systems Modeling Frameworkmentioning

confidence: 99%

IoT-based production logistics and supply chain system – Part 1

Lim

Yang

2018

IMDS

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Purpose The lack of reference architecture for Internet of Things (IoT) modeling impedes the successful design and implementation of an IoT-based production logistics and supply chain system (PLSCS). The authors present this study in two parts to address this research issue. Part A proposes a unified IoT modeling framework to model the dynamics of distributed IoT processes, IoT devices, and IoT objects. The models of the framework can be leveraged to support the implementation architecture of an IoT-based PLSCS. The second part (Part B) of this study extends the discussion of implementation architecture proposed in Part A. Part B presents an IoT-based cyber-physical system framework and evaluates its performance. The paper aims to discuss this issue. Design/methodology/approach This paper adopts a design research approach, using ontology, process analysis, and Petri net modeling scheme to support IoT system modeling. Findings The proposed IoT system-modeling approach reduces the complexity of system development and increases system portability for IoT-based PLSCS. The IoT design models generated from the modeling can also be transformed to implementation logic. Practical implications The proposed IoT system-modeling framework and the implementation architecture can be used to develop an IoT-based PLSCS in the real industrial setting. The proposed modeling methods can be applied to many discrete manufacturing industries. Originality/value The IoT modeling framework developed in this study is the first in this field which decomposes IoT system design into ontology-, process-, and object-modeling layers. A novel implementation architecture also proposed to transform above IoT system design models into implementation logic. The developed prototype system can track product and different parts of the same product along a manufacturing supply chain.

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Section: Iot Systems Modeling Frameworkmentioning

confidence: 99%