Several Typical Paradigms of Industrial Big Data Application

TL;DR

This paper introduces the concept of big data cloud and the 3M definition to better characterize industrial big data, and proposes three typical application paradigms to guide industrial data utilization.

Contribution

It presents a new conceptual framework and three application paradigms specifically tailored for industrial big data, addressing limitations of existing definitions.

Findings

Proposes the big data cloud concept and 3M definition for industrial data.

Builds three application paradigms: fusion calculation, model correction, information compensation.

Provides systematic methods for industrial big data application.

Abstract

Industrial big data is an important part of big data family, which has important application value for industrial production scheduling, risk perception, state identification, safety monitoring and quality control, etc. Due to the particularity of the industrial field, some concepts in the existing big data research field are unable to reflect accurately the characteristics of industrial big data, such as what is industrial big data, how to measure industrial big data, how to apply industrial big data, and so on. In order to overcome the limitation that the existing definition of big data is not suitable for industrial big data, this paper intuitively proposes the concept of big data cloud and the 3M (Multi-source, Multi-dimension, Multi-span in time) definition of cloud-based big data. Based on big data cloud and 3M definition, three typical paradigms of industrial big data applications are built, including the fusion calculation paradigm, the model correction paradigm and the information compensation paradigm. These results are helpful for grasping systematically the methods and approaches of industrial big data applications.