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Alert and on task: decoding how mental alertness and workload influence maritime operators task performance using task network modeling

Shengyuan Yan,Waqas Ahmed, Hanan Ahmed Saeed

Cognition, Technology & Work(2024)

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Abstract
The rapid technology growth in the maritime defense sector demands efficient and effective human performance, particularly in roles involving navigation, tactical decision-making, and emergency responses. To accommodate this demand, our study aims to find the effects of the two most significant performance influencing factors i.e., mental alertness and workload on the performance of Electronic Support Measures (ESM) receiver operators in complex task environments of a surface combat ship. A Discrete Event Simulation model with the Task Network Modeling approach was developed in IPME software. Alertness, measured by the Karolinska Sleepiness Scale (KSS), was predicted for Crew Chiefs’ schedules (4–8, 6–6, and 8–8) using the Three Process Model in FIPS software. The simulation integrated KSS predictions and VACP workload values, with 10 simulation runs, for each schedule, to assess the effects of mental alertness and workload on the total number of signals missed, the total number of signals logged, and percentage time at risk. The findings reveal that mental alertness variation due to different shift patterns in combination with mental workload significantly influence performance metrics, especially during night time operations, highlighting potential attention lapses and reduced efficiency. This comprehensive analysis provides valuable insights into the dynamics of shift work and task demands, aiming to enhance operational safety and performance in critical environments. The study’s methodology and findings offer a foundation for further research and practical applications in various industries where managing mental alertness and workload is crucial for safety and efficient crew performance.
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Key words
Alertness,Workload,Shiftwork,Human performance modeling,Surface combat ship,Performance shaping factors
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