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ABSTRACT. The aim of this paper is to synthesize and analyze existing evidence on cyber-physical process monitoring systems, real-time big data analytics, and industrial artificial intelligence in sustainable smart manufacturing. Using and replicating data from Capgemini, Forrester, McKinsey, PwC, and World Economic Forum, we performed analyses and made estimates regarding how networked integrated production equipment and sensors and machine learning tools configure the predictive monitoring of manufacturing plants. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
JEL codes: E24; J21; J54; J64

Keywords: cyber-physical; process monitoring; sustainable smart manufacturing

How to cite: Cohen, S., and Macek, J. (2021). “Cyber-Physical Process Monitoring Systems, Real-Time Big Data Analytics, and Industrial Artificial Intelligence in Sustainable Smart Manufacturing,” Economics, Management, and Financial Markets 16(3): 55–67. doi: 10.22381/emfm16320211.

Received 11 April 2021 • Received in revised form 13 September 2021
Accepted 16 September 2021 • Available online 18 September 2021

Sarah Cohen
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Cognitive Computing Technologies
Research Unit at AAER, Glasgow, Scotland
(corresponding author)
Jaroslav Macek
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Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic

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