Behind every smart factory — the sensors, the dashboards, the AI-driven alerts — there is still a human brain. And that brain gets tired, stressed and overwhelmed in ways that no production KPI currently captures. Industry 4.0 has transformed the physical and digital layers of manufacturing. The human layer is still waiting.

Neurophysiology is changing that. EEG signals, eye-tracking, heart rate variability, galvanic skin response, tools once confined to neuroscience labs are now finding their way onto the shop floor, offering a window into the cognitive state of workers that self-report questionnaires and behavioral observation simply cannot match. When a worker is mentally fatigued, when a new assistive system is reducing cognitive load rather than adding to it, when a decision-support dashboard is actually helping… neurophysiology can measure that, objectively and in real time.

Yet the academic evidence base is thin. Few studies have rigorously demonstrated what these tools can do in a real manufacturing context, and no coherent framework exists to guide their application. This thesis sets out to build one. Starting from a systematic literature review, the research maps the current state of neurophysiology applications in smart production, develops a structured framework for their use and validates it through field experiments in real industrial settings.

The result is both a scientific contribution to an emerging and underexplored discipline and a practical toolkit for companies that want to design human-centered Industry 4.0 environments with actual evidence behind them.

If you have ever wondered what is really happening inside the mind of a worker navigating a smart factory and you want to be among the first researchers to measure it rigorously and systematically, this thesis is where that question gets answered.