ABSTRACT. This paper analyzes the outcomes of an exploratory review of the current research on digital-twin-based cyber-physical production systems. The data used for this study was obtained and replicated from previous research conducted by Deloitte, Gartner, Job Wizards/Konica Minolta, and PTC. I performed analyses and made estimates regarding benefits of digital twins in companies, digital twin business values, practical actions to advance digital twin strategies, and different digital twins that enterprises can use. Data collected from 4,300 respondents are tested against the research model by using structural equation modeling.
JEL Codes: E24; J21; J54; J64

Keywords: digital twin; cyber-physical production system; Internet of Things

How to cite: Breillat, Richard (2020). “Industrial Artificial Intelligence, Internet of Things Smart Devices, and Big Data-driven Decision-Making in Digital-Twin-based Cyber-Physical Production Systems,” Economics, Management, and Financial Markets 15(1): 47–53. doi:10.22381/EMFM15120204

Received 8 January 2020 • Received in revised form 20 March 2020
Accepted 22 March 2020 • Available online 28 March 2020

Richard Breillat
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Big Data Algorithmic Analytics Laboratory
at ISBDA, Montreal, Canada

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