Case Studies and Best Practices in Cloud-Based Big Data Analytics for Process Control

Authors

  • Rishabh Rajesh Shanbhag Independent Researcher, USA
  • Rajkumar Balasubramanian Independent Researcher, USA
  • Ugandhar Dasi Independent Researcher, USA
  • Nikhil Singla Independent Researcher, USA
  • Siddhant Benadikar Independent Researcher, USA

DOI:

https://doi.org/10.36676/jrps.v13.i5.1462

Keywords:

BDA, CC, Process Control, IIoT, PM, RA, DS, AI, ML, Edge Com

Abstract

In this research paper, case studies and exemplars and lessons learnt in cloud-based big data analytics for process control are reviewed. The paper presents big data, cloud computing and industrial process control system with prospects of enhancing effectiveness, increasing production rates, and effective decision making in the industries. The research in this paper involves a comprehensive literature review of the research topic, and an extension of the analysis to four specific business industries as well as a discussion of architectural elements for cloud-based big data solutions for process control business. It also presents various crucial issues such as data protection, adherence to legal requirements, and compatibility with other systems, giving solutions. In addition, the research compares the effectiveness of cloud-based solutions with on-premise ones and discuss other novelties, including edge computing and artificial intelligence as the tendencies potentially influencing process control. Consequently, the findings of this research can be helpful for both industry practitioners and researchers who aim to optimize process control and organization operation with the help of cloud-based big data analytics

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Published

29-11-2022

How to Cite

Rishabh Rajesh Shanbhag, Rajkumar Balasubramanian, Ugandhar Dasi, Nikhil Singla, & Siddhant Benadikar. (2022). Case Studies and Best Practices in Cloud-Based Big Data Analytics for Process Control. International Journal for Research Publication and Seminar, 13(5), 292–311. https://doi.org/10.36676/jrps.v13.i5.1462