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Industrial Big Data Analytics: Challenges and Opportunities

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Abstract

Manufacturing industries generate a large amount of data from various devices, systems and applications. Challenges, including both data management and data analysis exist in Industry 4.0 with few solutions to handle processing large amounts of data. The data needs to be processed, analyzed and secured to help improve the systems efficiency, safety and scalability. Hence, a new approach is needed to support industrial big data analytics. Industry 4.0 is a new advanced manufacturing vision originated by the German government. Since it is a new concept, there are only several existing surveys that discuss the connection between cyber physical systems and industrial big data analytics. Therefore, this survey will present new concepts, methodologies and application scenarios to reach full industrial autonomy and bring more attention to existing challenges between big data analytics and cyber physical systems. Current solutions, implemented through cyber physical systems, are discussed to highlight desired future research directions.

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Authors and Affiliations

  1. School of Engineering, University of Guelph, Guelph, ON, Canada

    Abdulrahman Al-Abassi & Hadis Karimipour

  2. Cyber Science Lab, School of Computer Science, University of Guelph, Guelph, ON, Canada

    Hamed HaddadPajouh & Ali Dehghantanha

  3. College of Computer and Software Engineering, Kennesaw State University, Marietta, GA, USA

    Reza M. Parizi

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  1. Abdulrahman Al-Abassi
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  4. Ali Dehghantanha
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  1. University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

  2. Cyber Science Lab, School of Computer Science, University of Guelph, Guelph, ON, Canada

    Ali Dehghantanha

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Al-Abassi, A., Karimipour, H., HaddadPajouh, H., Dehghantanha, A., Parizi, R.M. (2020). Industrial Big Data Analytics: Challenges and Opportunities. In: Choo, KK., Dehghantanha, A. (eds) Handbook of Big Data Privacy. Springer, Cham. https://doi.org/10.1007/978-3-030-38557-6_3

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