Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

Mihai Andronie, George Lăzăroiu, Roxana Ștefănescu, Cristian Uță and Irina Dijmărescu
Additional contact information
Mihai Andronie: Department of Economic Sciences, Spiru Haret University, 030045 Bucharest, Romania
George Lăzăroiu: Department of Economic Sciences, Spiru Haret University, 030045 Bucharest, Romania
Roxana Ștefănescu: Department of Juridical Sciences and Economic Sciences, Spiru Haret University, 500152 Brașov, Romania
Cristian Uță: Department of Economic Sciences, Spiru Haret University, 030045 Bucharest, Romania
Irina Dijmărescu: Department of Pediatrics, Grigore Alexandrescu Children’s Emergency Hospital, 011743 Bucharest, Romania
Authors registered in the RePEc Author Service: Roxana Stefanescu

Sustainability, 2021, vol. 13, issue 10, 1-23

Abstract: With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.

Keywords: sustainable smart manufacturing; artificial intelligence-based decision-making algorithm; big data analytics; cyber-physical production system; digital twin; sensing technology (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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