Study on Information and Integrated of MES Big Data and Semiconductor Process Furnace Automation

Chang, Kuo-Song; Pan, Jeng‐Shyang; Chu, Kai Chun; Horng, Der Juinn; Huang, Jing

doi:10.1007/978-981-13-5841-8_70

Cited by 13 publications

(1 citation statement)

References 5 publications

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“…An important evolution in the structure of the industrial economy that can allow personnel production can change the overall economic dimension. Figure 1 shows the evolution from Industry 1.0 to Industry 4.0 [5].…”

Section: Smart Manufacturingmentioning

confidence: 99%

Application of Advanced Framework Technology in Smart Cities to Improve Resource Utilization

Chu¹,

Chang²,

Wang³

et al. 2021

Smart Cities - Their Framework and Applications

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Nowadays, the application technology and demand are growth; there have been millions of solutions for user communication in smart cities. However, the quality of the autonomy of handheld devices and the information exchange of applications are functions of requesting services or participating in communications. Therefore, it is very difficult and tedious to implement resource management and control in such an environment. This study here proposes distributed cyber-physical systems (CPS) for agent-based middleware framework (AMF) using to achieve technology, thereby improving the reliability of environmental communication in smart cities. The technical solution has the characteristics of avoiding the problem of data source interruption because of the proxy technology of the linear calculation model. The aforementioned agents are independent and autonomous of each other in terms of providing seamless resource sharing and response scheduling, and have nothing to do with communication time and request queries. In this study, the architecture mainly uses the best linear calculation model to classify overlapping agents, and then allocates non-overlapping resources, and finally analyzes the overall architecture operation performance by responding to processed queries, storage utilization and resource usage, pause time and response.

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Section: Smart Manufacturingmentioning

confidence: 99%