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A big data analytics platform for smart factories in small and medium-sized manufacturing enterprises: An empirical case study of a die casting factory

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Abstract

This paper proposes an architecture and system modules for a big data analytics platform to implement smart factories in small and medium-sized enterprises. The big data analytics platform enables small and medium-sized enterprises 1) to achieve the integrated system environment between the legacy system and the platform; 2) to address quality issues by applying analytical models to their factories; and 3) to reduce their financial burdens of infrastructure and experts for the platform through cloud computing. In terms of evaluation, the proposed platform was applied to the factory of a die casting company in South Korea. Using the big data analytics platform that was developed, this paper also introduced the application scenario to identify defects in the die casting process. From this empirical research, we have clarified the difficulties and challenges in applying big data analytics to small and medium-sized manufacturing enterprises. For future works, this paper suggests a manufacturing data analytics library to provide consolidated information, including a data-mining model, its datasets, and preprocessing methods for specific manufacturing problems.

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Authors and Affiliations

  1. IT Converged Process R&D Group, Korea Institute of Industrial Technology, 143, Hanggaul-ro, Sangnok-gu, Ansan-si, Gyeonggi-do, 15588, South Korea

    Ju Yeon Lee & Bo-Hyun Kim

  2. Smart Manufacturing Technology Group, Korea Institute of Industrial Technology, 89, Yangdaegiro-gil, Ipjang-myeon, Seobuk-gu, Cheonan-si, Chungcheongnam-do, 31056, South Korea

    Joo Seong Yoon

Authors
  1. Ju Yeon Lee
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  2. Joo Seong Yoon
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  3. Bo-Hyun Kim
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Correspondence to Ju Yeon Lee.

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Lee, J.Y., Yoon, J.S. & Kim, BH. A big data analytics platform for smart factories in small and medium-sized manufacturing enterprises: An empirical case study of a die casting factory. Int. J. Precis. Eng. Manuf. 18, 1353–1361 (2017). https://doi.org/10.1007/s12541-017-0161-x

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  • DOI: https://doi.org/10.1007/s12541-017-0161-x

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