Abstract
In this article, we cumulate previous research findings indicating that cyber-physical production systems bring about operations shaping social sustainability performance technologically. We contribute to the literature on sustainable cyber-physical production systems by showing that the technological and operations management features of cyber-physical systems constitute the components of data-driven sustainable smart manufacturing. Throughout September 2020, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “sustainable industrial value creation”, “cyber-physical production systems”, “sustainable smart manufacturing”, “smart economy”, “industrial big data analytics”, “sustainable Internet of Things”, and “sustainable Industry 4.0”. As we inspected research published only in 2019 and 2020, only 323 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 119, generally empirical, sources. Future research should investigate whether Industry 4.0-based manufacturing technologies can ensure the sustainability of big data-driven production systems by use of Internet of Things sensing networks and deep learning-assisted smart process planning.
Highlights
Accepted: 11 January 2021The objective of our systematic review is to analyze the lately published literature on sustainable cyber-physical production systems and synthesize the interconnected insights on big data-driven smart urban economy
We want to elucidate whether industrial big data analytics, deep learning-assisted smart process planning, sustainable product lifecycle management, and cognitive decision-making algorithms can assist throughout the decarbonization process by use of digital technologies
Industrial big data analytics, deep learning-assisted smart process planning, sustainable product lifecycle management, and cognitive decision-making algorithms can assist throughout the decarbonization process by use of digital technologies while necessitating minimal investments
Summary
The objective of our systematic review is to analyze the lately published literature on sustainable cyber-physical production systems and synthesize the interconnected insights on big data-driven smart urban economy. By inspecting the most relevant (the Web of Science, Scopus, and ProQuest) and recent (2019–2020) sources, we have endeavored to prove that, in Industry 4.0, big data-driven technologies assist in the adoption of a cleaner production approach and in the advancement of sustainable smart manufacturing. The actuality and novelty of the current research are configured by paying attention to a hot emerging topic, that is, sustainable cyber-physical production systems. The research problem developed at full length of the systematic review is whether sustainable smart manufacturing platforms can be networked to assimilate the value chain throughout businesses and constitute a groundbreaking industrial form assisted by cognitive decisionmaking algorithms. Our main aim is to indicate that implementation of Internet of Things sensing networks, Published: 14 January 2021
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