Model Compression for IoT Applications in Industry 4.0 via Multiscale Knowledge Transfer

Fu, Shipeng; Li, Zhen; Li, Kai; Din, Sadia; Imran, Muhammad; Yang, Xiaobo

doi:10.1109/tii.2019.2953106

Cited by 32 publications

(7 citation statements)

References 18 publications

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“…This principle produced the minimum hop communication between nodes, and the optimized ant routing builds the best path in a multi-hop manner to forward the data packets. Fu et al (2019) proposed innovation to transfer diverse knowledge from the teacher network to the student network. The innovation is known as the multiscale knowledge transfer method (MSKT).…”

Section: Background and Literature Reviewmentioning

confidence: 99%

The impact of applying knowledge in the technological pillars of Industry 4.0 on supply chain performance

Sawangwong

Chaopaisarn

2021

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PurposeThe purpose of the study is to investigate the impact of technological pillars of Industry 4.0 based on knowledge to adopt the supply chain performance of Thai small and medium-sized enterprises (SMEs) 4.0. In addition, to increase knowledge and understanding of how to apply knowledge in technology 4.0 to improve the efficiency of supply chains and organizations.Design/methodology/approachAn integrated model was developed from applying knowledge in five technological pillars of Industry 4.0 such as Internet of things (IoTs), cloud computing, big data and analytics, additive manufacturing and cyber-security. The bibliometric analysis was used to find the relationship between the technological pillars of Industry 4.0 and the literature review. The survey questionnaires were sent to Thai SME 4.0 (manufacturing aspect). Of these, 240 useable responses were received, resulting in a response rate of 65.84%, after then, the exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM) and validity were used to evaluate the model through IBM SPSS 21 and AMOS 22.FindingsEFA showed the four groups of the technological pillars of Industry 4.0, such as support human, automation, real-time and security. These groups positively impact supply chain performance (increase delivery reliability, increase resource efficiency, decrease costs in the supply chain and reduce delivery time). Another important finding is that supply chain performance positively impacts organizational performance in profitability, return on investment (ROI) and sale growth.Originality/valueThis study is a model development to support the supply chain performance and increase understanding related to applying knowledge in technology 4.0 that remains unclear for SME 4.0.

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Section: Background and Literature Reviewmentioning

confidence: 99%

The impact of applying knowledge in the technological pillars of Industry 4.0 on supply chain performance

Sawangwong

Chaopaisarn

2021

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“…The problems of the development of Industry 4.0 are widely reflected in the works of many researchers: security and privacy in industry 4.0 (Alcaraz et al, 2020); safety digitalization (Savon et al, 2019); machine diagnostic methods applicability in the perspective of industry 4.0 (Asad et al, 2018); business intelligence (Bordeleau et al, 2019); national and regional comparative advantages in key enabling technologies (Ciffolilli & Muscio, 2018); model compression for IoT applications (Fu et al, 2020); prospects of using virtual technologies in modern corporate business systems (Klochko & Brizhak, 2019); modeling the management system of open innovation in E-economy (Kudryavtseva et al, 2018); Big Data approach (Kumar et al, 2018); digital supply chain model (Lizette Garay-Rondero et al, 2019); digitization and industry 4.0 optimization potential (Wirth & Klein, 2018); deep learning model in industry 4.0 (Ma et al, 2020); data science challenges (Piccialli et al, 2020); modelling of energy (Shinkevich et al, 2020); smart job shop under industry 4.0 (Wang et al, 2020); the impacts of industry 4.0 (Zheng et al, 2019) and ext.…”

Section: Problem Statementmentioning

confidence: 99%

To The Question Of Assessing The Maturity Level Of Industry 4.0

Kudryavtseva¹

2021

European Proceedings of Social and Behavioural Sciences

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“…Works have also been done identifying flow structure and flow regime transitions in two-phase air, and water flows [11] and predicting physical parameters in two-phase oil and water flows [26]. Currently, great technological advances are being presented due to the submergence of industry 4.0 and the industrial internet of things IioT [27], [28], [29]. One of the great pillars of this industrial revolution is machine learning, with its different techniques to solve, analyze and model problems in industrial processes.…”

Section: Introductionmentioning

confidence: 99%

Specialist system in flow pattern identification using artificial neural Networks

Camperos¹,

Diaz²,

Cely³

2023

J Appl Eng Science

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In this work, an application of artificial intelligence in the oils & gas industry is developed to iden-tify flow patterns in horizontal and vertical pipes of two-phase flow of oil and water, normalizing the word information and converting it to numerical values through the development of an artifi-cial neural network, whose input layer is composed of the surface velocities of each fluid, the ve-locity of the mixture, the volumetric fraction of the substances, diameter and the inclination of pipelines and the oil viscosity. The Artificial Neural Networks (ANN) has two hidden layers composed of 45 neurons. The database with which the model was trained, validated, and tested has 6993 rows of information corresponding to the inputs of the intelligent system and particular-ized for annular flow in horizontal pipes and DO/W in vertical pipelines. Notice that the infor-mation was obtained after re-engineering the information presented by 12 and 18 authors for hor-izontal and vertical piping, respectively. Finally, the mean square error obtained by the model was around 1.38%, with a maximum coefficient of determination of 0.79.

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Model Compression for IoT Applications in Industry 4.0 via Multiscale Knowledge Transfer

Cited by 32 publications

References 18 publications

The impact of applying knowledge in the technological pillars of Industry 4.0 on supply chain performance

The impact of applying knowledge in the technological pillars of Industry 4.0 on supply chain performance

To The Question Of Assessing The Maturity Level Of Industry 4.0

Specialist system in flow pattern identification using artificial neural Networks

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