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Smart Reconfigurable Manufacturing: Literature Analysis

Li, Xingyu (författare)
School of Engineering Technology, Purdue University, West Lafayette, IN, USA
Athinarayanan, Ragu (författare)
School of Engineering Technology, Purdue University, West Lafayette, IN, USA
Wang, Baicun (författare)
School of Mechanical Engineering, Zhejiang University, Hangzhou, China
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Yuan, Wei (författare)
R&D Division, Hitachi America, Ltd., Farmington Hills, MI, USA
Zhou, Quan (författare)
R&D Division, Hitachi America, Ltd., Farmington Hills, MI, USA
Jun, Martin (författare)
Mechanical Engineering, Purdue University, West Lafayette, IN, USA
Bravo, Jose (författare)
School of Engineering Technology, Purdue University, West Lafayette, IN, USA
Gao, Robert X. (författare)
Department of Mechanical & Aerospace Engineering, Case Western Reserve University, Cleveland, OH, USA
Wang, Lihui (författare)
KTH,Produktionsutveckling
Koren, Yoram (författare)
Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, USA
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 (creator_code:org_t)
Elsevier B.V. 2024
2024
Engelska.
Ingår i: 11th CIRP Global Web Conference, CIRPe 2023. - : Elsevier B.V.. ; , s. 43-48
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
Stäng  
  • Smart manufacturing (SM) enhances the competitiveness of manufacturing companies by promoting automation and overall equipment effectiveness (OEE), targeting to produce 100% qualified products fully automatically. One of the key challenges to the SM initiatives is the continuous demand fluctuations in the specification and quantity, especially when a new product variant comes to the production line. Reconfigurable manufacturing (RM) system provides cost-effective, rapid response to abrupt market changes. It provides a solution by its flexibility in repurposing tools, adding machines, and modifying software to rapidly respond to changing demands at low unit costs. The ability of SM technologies through self-programming and cloud computation may significantly complements RM initiatives. There is increasing evidence that SM and RM may augment each other through their complementary strengths, leading to the new paradigm of smart reconfigurable manufacturing (SRM). To highlight the complementary strengths, this paper investigates the converging trend of RM and SM based on natural language processing, e.g., topic modeling and semantic embedding. Key characteristics and industrial use cases are subsequently summarized to systematically delineate the new SRM paradigm and illustrate its advantages and feasibility in practice.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)

Nyckelord

Natural Language Processing
Reconfigurable Manufacturing Systems
Smart Reconfigurable Manufacturing
Smart Manufacturing

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