Indonesia Network Infrastructures and Workforce Adequacy to Implement Machine Learning for Large-Scale Manufacturing

  • Steven Anderson
  • Ansarullah Lawi
Keywords: Digitalization, Machine Learning, Manufacturing, Network Infrastructure

Abstract

Technological development prior to industrial revolution 4.0 incentivized manufacturing industries to invest into digital industry with the aim of increasing the capability and efficiency in manufacturing activity. Major manufacturing industry has begun implementing cyber-physical system in industrial monitoring and control. The system itself will generate large volumes of data. The ability to process those big data requires algorithm called machine learning because of its ability to read patterns of big data for producing useful information. This study conducted on premises of Indonesia’s current network infrastructure and workforce capability on supporting the implementation of machine learning especially in large-scale manufacture. That will be compared with countries that have a positive stance in implementing machine learning in manufacturing. The conclusions that can be drawn from this research are Indonesia current infrastructure and workforce is still unable to fully support the implementation of machine learning technology in manufacturing industry and improvements are needed.

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Author Biographies

Steven Anderson

PT. Riau Andalan Pulp & Paper. Batam, Indonesia.

Ansarullah Lawi

Faculty of Engineering, Universal University. Batam, Indonesia.

This is an open access article, licensed under CC-BY-SA

Creative Commons License
Published
        Views : 413
2021-06-22
    Downloads : 308
How to Cite
[1]
S. Anderson and A. Lawi, “Indonesia Network Infrastructures and Workforce Adequacy to Implement Machine Learning for Large-Scale Manufacturing”, International Journal of Artificial Intelligence, vol. 8, no. 1, pp. 1-16, Jun. 2021.
Section
Articles

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