ABSTRACT. Empirical evidence on sustainable organizational performance, cyber-physical production networks, and deep learning-assisted smart process planning in Industry 4.0-based manufacturing systems has been scarcely documented in the literature. Using and replicating data from Capgemini, the Economist Intelligence Unit, McKinsey, Management Events, and World Economic Forum, we performed analyses and made estimates regarding how data-driven supervision, predictive analytics, and optimization systems integrate product traceability, manufacturing maintenance, and process performance in smart manufacturing. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
JEL codes: E24; J21; J54; J64

Keywords: cyber-physical; production network; Industry 4.0; smart manufacturing

How to cite: Kovacova, M., and Lăzăroiu, G. (2021). “Sustainable Organizational Performance, Cyber-Physical Production Networks, and Deep Learning-assisted Smart Process Planning in Industry 4.0-based Manufacturing Systems,” Economics, Management, and Financial Markets 16(3): 41–54. doi: 10.22381/emfm16320212.

Received 11 April 2021 • Received in revised form 10 September 2021
Accepted 13 September 2021 • Available online 18 September 2021

Maria Kovacova
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Faculty of Operation and Economics
of Transport and Communications,
Department of Economics,
University of Zilina, Zilina, Slovak Republic
George Lăzăroiu
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The Institute of Smart Big Data Analytics,
New York City, NY, USA;
Spiru Haret University, Bucharest, Romania
(corresponding author)

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