Journal
27TH INTERNATIONAL CONFERENCE ON FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING, FAIM2017
Volume 11, Issue -, Pages 1950-1957Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.promfg.2017.07.341
Keywords
smart manufacturing; applications' integration and operation platform; cloud; small and medium-sized enterprieses
Funding
- Technology Innovation Program (Industrial Strategic Technology Development Program) - Korean Ministry of Trade, Industry Energy [10054508]
- Korea Evaluation Institute of Industrial Technology (KEIT) [10054508] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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Many developed countries are making various efforts to innovate their own manufacturing industries, through initiatives such as Manufacturing innovation 3.0, Industry 4.0, and Manufacturing 2025. Innovation in the manufacturing industry, represented by the so-called smart factories, is being developed through the latest technologies such as Internet of things (IoT), cloud, and big data. However, as the application of these technologies requires a lot of cost and time, small and medium-sized enterprises (SMEs) are often hampered in their efforts to take full advantage of them. For an enterprise that operates a manufacturing information system, the integrated management of information between systems is essential to the application of a new technology. If the enterprise lacks the relevant experts, it will have difficulty applying a new technology in the field. This study suggests the application of a cloud-based applications' integration and operation platform (AIOP) in order to resolve those problems. The AIOP must accept a large volume of data at IoT-based manufacturing fields, interconnect between manufacturing fields and AIOP, and provide application contents in the form of service. The suggested study contents are applied to a company that produces electric components using plastic injection molds to verify their effects. It is expected that this study can be used as a reference model for applying smart factory technologies to other SMEs in the future. (C) 2017 Published by Elsevier B.V.
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