REAL TIME STRESS MONITORING IN PROGRAMMABLE LOGIC CONTROLLER TECHNICIANS

Abstract

The presentation looks at the real-time monitoring of stress of PLC technicians, the advanced PLC workers in today industrial automation. PLC technicians have come a need to do systems diagnostics, control logic reprogramming, and production-sustaining emergency response in diagnosis control systems within tight deadlines. In addition to commanding a high level of professional expertise, these processes require deep cognitive and emotional stamina. As an example, performance assessments, productivity evaluations, and even subjective self-evaluations do not capture the significant internal, psychological, and physiological stress of the high-stakes operations faced by the technicians.

This methodology gap is addressed by conducting the current research within smart factory simulations equipped with wearable biosensing technologies, EEGs, HRVs, and GSRs. These devices monitor and record cognitive stress, neural, cardiovascular and electrodermal signals, and emotional arousal. In a controlled setting, twenty qualified PLC technicians were given tasks and asked to perform to the best of their abilities starting from simple to complex: routine maintenance, fault detection and correction, and ending with the most complex - critical error management. Each stage was designed to increase the mental workload step by step in terms of focus, memory, decisional analysis, and emotional control.

The research findings show that there is a noteworthy relationship between the difficulty of the task and the physiological signs of stress. High-complexity tasks were marked by heightened EEG beta activity, increased GSR conductivity, and lowered HRV. These biofeedback metrics exemplified the effectiveness of biosensing in monitoring and evaluating stress in real-time. Besides, the findings highlight the feasibility of creating adaptive automation systems that would react to an operator's stress by modifying the task, providing cognitive help, or activating safety measures. 

Apart from the technical aspects, the paper tackles critical societal issues regarding the use biometric data, such as the use of biometric data and the need for informed consent, data protection, non-bias, and design opacity. It argues for the proactive monitoring of stress within the industrial framework to promote the enhancement of human well-being, safety, and effectiveness, advocating for the protective stress monitoring systems. The research considers real-time cognitive-emotional tracking as an initial element for the forthcoming human-focused industrial automation.