ABSTRACT. Employing recent research results covering Internet of Things-based real-time production logistics, big data-driven decision-making processes, and industrial artificial intelligence in sustainable cyber-physical manufacturing systems, and building my argument by drawing on data collected from Capgemini, Deloitte, IoT World Today, Management Events, McKinsey, PAC, PwC, and SME, I performed analyses and made estimates regarding intelligent remote equipment control and optimization of the manufacturing processes through autonomous robotic systems, predictive maintenance, and sensing technologies in data-driven autonomous production collaboration, the smart transformation of the industrial units, and the manufacturing dynamic monitoring. Robust and flexible automation, smart connected devices, distributed and reconfigurable manufacturing systems, predictive maintenance, and collaborative robotics are pivotal in decentralized cooperative production. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
JEL codes: E24; J21; J54; J64

Keywords: sustainability; cyber-physical manufacturing; big data; Internet of Things

How to cite: Gordon, A. (2021). “Internet of Things-based Real-Time Production Logistics, Big Data-driven Decision-Making Processes, and Industrial Artificial Intelligence in Sustainable Cyber-Physical Manufacturing Systems,” Journal of Self-Governance and Management Economics 9(3): 61–73. doi: 10.22381/jsme9320215.

Received 12 March 2021 • Received in revised form 9 September 2021
Accepted 11 September 2021 • Available online 18 September 2021

Alison Gordon
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Big Data Analytics Research Unit
at ISBDA, Dublin, Ireland

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