ABSTRACT. This paper analyzes the outcomes of an exploratory review of the current research on Internet of Things-based real-time production logistics, sustainable industrial value creation, and artificial intelligence-driven big data analytics in cyber-physical smart manufacturing systems. The data used for this study was obtained and replicated from previous research conducted by Capgemini, Deloitte, IW Custom Research, Kronos, MHI, PwC, SME, and Software AG. We performed analyses and made estimates regarding deep learning-assisted smart process planning in cyber-physical manufacturing systems. Data collected from 4,700 respondents are tested against the research model. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
JEL codes: E24; J21; J54; J64

Keywords: Internet of Things; artificial intelligence; smart manufacturing system

How to cite: Nica, E., Stan, C. I., Luțan (Petre), A. G., and Oașa (Geambazi), R.-Ș. (2021). “Internet of Things-based Real-Time Production Logistics, Sustainable Industrial Value Creation, and Artificial Intelligence-driven Big Data Analytics in Cyber-Physical Smart Manufacturing Systems,” Economics, Management, and Financial Markets 16(1): 52–62. doi: 10.22381/emfm16120215.

Received 19 January 2021 • Received in revised form 12 March 2021
Accepted 15 March 2021 • Available online 20 March 2021