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Industrial Internet of Things (IIoT) and its applications have seen a paradigm shift since the advent of artificial intelligence and machine learning. However, these methods are mostly data-centric and lack flexibility. Brain-Computer Interface (BCI) is envisioned as an efficient solution that may overcome the shortcomings of data-centric techniques by introducing human intuition in the process loop. In this work, we present an exhaustive study on the feasibility of adopting BCI techniques for industrial applications, particularly Electroencephalography (EEG). We present a comprehensive literature survey on the basics of EEG (including signal processing techniques) and its involved paradigms, together with its application scope. We identify the potential use cases of EEG-based BCI systems in industries in the current traction while accounting for their pros and cons. Additionally, we also highlight the existing challenges …