Planning cellular manufacturing systems using fuzzy logic

Wang, T.J.; Chaharbaghi, Kazem

doi:10.1049/ic:19951562

Cited by 1 publication

(1 citation statement)

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“…At present, there are many research achievements in discrete intelligent factories in industries such as automobiles and ships [3,4], and there has been a deep exploration of the information standard system architecture of intelligent factories, establishing a standard system architecture for intelligent factory information that is suitable for China's national conditions [5]. Although there has been some progress in the research on intelligent factories in the electrical equipment manufacturing industry [6][7][8], no one has comprehensively studied and analyzed the indicator system of intelligent factories in electrical equipment manufacturing from five aspects: research and development, manufacturing, service, management, and basic support technology.…”

Section: Introductionmentioning

confidence: 99%

Construction of index system based on overall architecture of intelligent factory for electrical equipment manufacturing

Guo,

Miao,

Zhang

et al. 2024

Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023)

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In order to improve the level of intelligent manufacturing in electrical equipment manufacturing industry, this paper summarizes the current situation of electrical equipment manufacturing industry and the construction target of intelligent factory, and describes the architecture reference model of intelligent factory in electrical equipment manufacturing from three dimensions: system level, content structure and product category. Based on the above architecture, the smart factory index system is further constructed from the five aspects of digital research and development, manufacturing, management, service and basic support technology. The index system will provide reference for the construction of smart factories in electrical equipment manufacturing, and provide direction for the promotion and application of smart factories.

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Section: Introductionmentioning

confidence: 99%