A hybrid modeling methodology for cyber physical production systems: framework and key techniques

Ma, Jun; Wang, Qiang; Jiang, Zhenan; Zhao, Zhibiao

doi:10.1007/s11740-021-01062-2

Cited by 4 publications

(5 citation statements)

References 29 publications

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“…In the understanding of Gao et al [ 141 ], this corresponds to the representation in the problem domain. Alternatively, or complementing the modelling of the higher-level physical behaviour, a macroscopic model structure or architecture can be created for the subsequent detailed models [ 133 , 140 , 142 , 143 , 144 ].…”

Section: Resultsmentioning

confidence: 99%

“…This corresponds to the description in a solution domain. Furthermore, the addition of semantic annotations is possible [ 136 , 144 ]. The detailed modelling requires a choice of computing models and a determination of the hardware to be used [ 129 ].…”

Section: Resultsmentioning

confidence: 99%

“…The detailed sub-models are then deployed and aggregated into a super-model [ 129 , 133 , 134 , 136 , 138 , 139 , 140 , 141 , 144 , 145 ]. In the software context, this can be described as software synthesis or code generation [ 129 , 141 ].…”

Section: Resultsmentioning

confidence: 99%

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A Literature Review on the Development and Creation of Digital Twins, Cyber-Physical Systems, and Product-Service Systems

Fett,

Wilking,

Goetz

et al. 2023

Sensors

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Digital Twins offer vast potential, yet many companies, particularly small and medium-sized enterprises, hesitate to implement them. This hesitation stems partly from the challenges posed by the interdisciplinary nature of creating Digital Twins. To address these challenges, this paper explores systematic approaches for the development and creation of Digital Twins, drawing on relevant methods and approaches presented in the literature. Conducting a systematic literature review, we delve into the development of Digital Twins while also considering analogous concepts, such as Cyber-Physical Systems and Product-Service Systems. The compiled literature is categorised into three main sections: holistic approaches, architecture, and models. Each category encompasses various subcategories, all of which are detailed in this paper. Through this comprehensive review, we discuss the findings and identify research gaps, shedding light on the current state of knowledge in the field of Digital Twin development. This paper aims to provide valuable insights for practitioners and researchers alike, guiding them in navigating the complexities associated with the implementation of Digital Twins.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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A Literature Review on the Development and Creation of Digital Twins, Cyber-Physical Systems, and Product-Service Systems

Fett,

Wilking,

Goetz

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…The outcomes of our systematic review develop on empirical research [1][2][3][4][5][6][7][8][9][10][11]39,40,44,[121][122][123][124][136][137][138][139][140][144][145][146][147][148][157][158][159][160] contending that sustainable cyber-physical production systems developed on functional and behavioral patterns can address the inconveniences of disruptive Industry 4.0-related production environments. Wireless sensor technology monitor manufacturing assets and networked production or logistics business operations in real time.…”

Section: Discussionmentioning

confidence: 99%

“…There is an emergent body of literature in relation to how Cyber-Physical Systems (CPS) address the integration of Internet of Things sensing networks, computational applications, and artificial intelligence-based decision-making algorithms with physical devices, being engineered as an interconnection between cyber and physical components. This is crucial in the advancement of smart manufacturing by use of cloud computing, social networking, and big data [1][2][3]. Cyber-Physical Production Systems (CPPSs) develop out of the deployment of CPS principles to manufacturing environments.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence-Based Decision-Making Algorithms, Internet of Things Sensing Networks, and Deep Learning-Assisted Smart Process Management in Cyber-Physical Production Systems

et al. 2021

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With growing evidence of deep learning-assisted smart process planning, there is an essential demand for comprehending whether cyber-physical production systems (CPPSs) are adequate in managing complexity and flexibility, configuring the smart factory. In this research, prior findings were cumulated indicating that the interoperability between Internet of Things-based real-time production logistics and cyber-physical process monitoring systems can decide upon the progression of operations advancing a system to the intended state in CPPSs. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March and August 2021, with search terms including “cyber-physical production systems”, “cyber-physical manufacturing systems”, “smart process manufacturing”, “smart industrial manufacturing processes”, “networked manufacturing systems”, “industrial cyber-physical systems,” “smart industrial production processes”, and “sustainable Internet of Things-based manufacturing systems”. As we analyzed research published between 2017 and 2021, only 489 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 164, chiefly empirical, sources. Subsequent analyses should develop on real-time sensor networks, so as to configure the importance of artificial intelligence-driven big data analytics by use of cyber-physical production networks.

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Enhancing the effectiveness of joint production and maintenance scheduling based on a multi-agent system and a Pigouvian approach of externalities

Kedy,

Penda,

Nneme Nneme

et al. 2024

Prod. Eng. Res. Devel.

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A hybrid modeling methodology for cyber physical production systems: framework and key techniques

Cited by 4 publications

References 29 publications

A Literature Review on the Development and Creation of Digital Twins, Cyber-Physical Systems, and Product-Service Systems

A Literature Review on the Development and Creation of Digital Twins, Cyber-Physical Systems, and Product-Service Systems

Artificial Intelligence-Based Decision-Making Algorithms, Internet of Things Sensing Networks, and Deep Learning-Assisted Smart Process Management in Cyber-Physical Production Systems

Enhancing the effectiveness of joint production and maintenance scheduling based on a multi-agent system and a Pigouvian approach of externalities

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