ABSTRACT. We develop a conceptual framework based on a systematic and comprehensive literature review on robotic wireless sensor networks, industrial artificial intelligence, and deep learning-assisted smart process planning in sustainable cyber-physical manufacturing systems. Building our argument by drawing on data collected from McKinsey, Ovum, PwC, and World Economic Forum, we performed analyses and made estimates regarding industrial big data analytics. The data for this research were gathered via an online survey questionnaire. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
JEL codes: E24; J21; J54; J64
Keywords: industrial artificial intelligence; cyber-physical manufacturing system
How to cite: Blake, R., Michalkova, L., and Bilan, Y. (2021). “Robotic Wireless Sensor Networks, Industrial Artificial Intelligence, and Deep Learning-assisted Smart Process Planning in Sustainable Cyber-Physical Manufacturing Systems,” Journal of Self-Governance and Management Economics 9(4): 48–61. doi: 10.22381/jsme9420214.
Received 22 April 2021 • Received in revised form 13 December 2021
Accepted 16 December 2021 • Available online 21 December 2021