Abstract
This study proposes a cognition-adaptive approach for the administrative control of human-machine safety interaction through Internet of Things (IoT) data. As part of Industry 4.0, a human operator possesses various characteristics, but cannot be consistently understood as well as a machine. Thus, human-machine interaction plays an important role. This study focuses on incumbent challenges on the basis of estimated mental states. Given the operation logs from data recording hardware, a Hidden Markov model on top of a human cognitive model was trained to capture a production line worker’s sequential faults. Our study found that retaining workers’ attention is insufficient and tracking the state of perception is key to accomplishing production tasks. A safe workflow policy requires attention and perception. Accordingly, our proposed Petri Net enhances operation safety and improves production efficiency.
Highlights
Given the prominence of Industry 4.0, tasks and demands for humans in factories have changed [1].As a critical entity in cyber–physical systems, human operators experience an increased complexity of jobs, such as specification and verification of production [2]
To fill in this research gap, this study aims to develop an effective set of safety rules based on data analytics and proposes an adaptive approach for administrative control of human–machine safety interaction through Internet of Things (IoT)
In order to verify our hypothesis in this study, we propose to reinforce the Petri Nets (PNs) workflow by integrating the cognitive states with affordable equipment
Summary
Given the prominence of Industry 4.0, tasks and demands for humans in factories have changed [1]. As a critical entity in cyber–physical systems, human operators experience an increased complexity of jobs, such as specification and verification of production [2]. As an advocated focus of automation, human involvement has regained its importance, the characteristics of making errors constantly persist. For factories categorized as safety-critical, such as those involving heavy machinery or hazardous substances, human intervention is deemed necessary to safeguard all occurrences of incidents and failures of processes and products. Administration applies regulations to force workers to follow certain rules to prevent work hazards in the old era. Aligning speedy workers (e.g., a robot) with slow ones (e.g., a human) is inappropriate. To assure the correct functioning of this critical component, an
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