Smart Manufacturing and Intelligent Manufacturing: A Comparative Review

Wang, Baicun; Tao, Fei; Fang, Xudong; Liu, Chao; Liu, Yuanyuan; Freiheit, Theodor

doi:10.1016/j.eng.2020.07.017

Cited by 218 publications

(85 citation statements)

References 101 publications

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“…The evaluation scores of the economic, environmental, and technological factors were obtained. To directly reflect the score difference for each city, their scores were mapped to [ 1 , 10 ]. These results are shown in Table 3 , Table 4 and Table 5 .…”

Section: Results and Analysismentioning

confidence: 99%

“…The manufacturing structure of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is constantly being upgraded, especially with intelligent manufacturing [ 1 , 2 ], equipment [ 3 ], and biomedicine [ 4 ]. However, in terms of the “reindustrialization” strategy [ 5 ] carried out by the United States, the Sino–United States trade war exposed a lack of key technologies in China’s manufacturing industry, giving it a disadvantage in international competition.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exploring Regional Advanced Manufacturing and Its Driving Factors: A Case Study of the Guangdong–Hong Kong–Macao Greater Bay Area

Dou

Sun

Wang

et al. 2021

IJERPH

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This study aims to analyze the development trend of the manufacturing industry of the Guangdong–Hong Kong–Macao Greater Bay Area (from 2008 to 2018) by constructing an evaluation system. On the basis of push–pull–mooring theory, we analyze these factors by using an entropy and cluster model. The results show the following: (1) Technological development had an obvious spatial distribution pattern of core regional radiation, while others did not. (2) Economic development was based on the city’s existing industrial development system, while environmental development depended on governmental policies. (3) Compared with the environmental factor, the development trends of the economic and technological factors were more similar. Lastly, we provide four strategies for the development of the manufacturing industry in different cities.

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Section: Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exploring Regional Advanced Manufacturing and Its Driving Factors: A Case Study of the Guangdong–Hong Kong–Macao Greater Bay Area

Dou

Sun

Wang

et al. 2021

IJERPH

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show abstract

“…Thus, in fact, one of the main tasks of an intelligent management system for modern digital "smart" production is to expand the physical production site and combine it with virtual components of digital design and modeling, as well as with suppliers and contractors [5]. As a result, a single information field is formed, where each participant in the added value chain has access to the most up-to-date information, which increases the transparency of all business processes, improves and accelerates communication between all participants.…”

Section: Methodsmentioning

confidence: 99%

Digital Technologies in the Smart Production Management System

2021

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The article analyzes the possibility of using such digital technologies as the Industrial Internet of Things (IIoT), Big Data and the creation of models of digital twins in the formation of intelligent management systems for "smart" production within the framework of the concept of digital transformation of the manufacturing sector Industry 4.0. The essence and features of these technologies, problematic aspects of their implementation in real production enterprises are considered. The concept of the functional structure of the digital production management system of a "smart" enterprise based on the digital twin model is proposed. The conclusion is made about the integrating role of technologies for the development and application of digital twin models in the construction of intelligent control systems for "smart" production.

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“…Although the objectives and methodologies are similar, there are evidences of different ways Smart Manufacturing and Intelligent Manufacturing are addressed in the literature (Mittal et al, 2019;Muhuri et al 2019;Wang et al, 2020).…”

Section: History and Future Of Intelligent And Smart Manufacturingmentioning

confidence: 99%