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Three-process model of supervisory activity over 24 hours
V Andorre-Gruet1, Y Queinnec, D Concordet
1Laboratoire Travail et Cognition, UMR 5551, CNRS--Université Toulouse 2, France. andorre@univ-tlse2.fr
Scandinavian Journal of Work, Environment & Health
|January 23, 1999
Summary
Supervisory activity in chemical plants is influenced by cognitive demands, shift duration, and circadian rhythms. This model helps optimize shift schedules and durations for improved operational efficiency.
Area of Science:
- Industrial Engineering
- Human Factors Engineering
- Occupational Health
Background:
- Supervisory activity in automated industrial settings is complex.
- Understanding factors influencing this activity is crucial for operational efficiency and safety.
Purpose of the Study:
- To develop a model for sampling supervisory activity using endogenous and exogenous factors.
- To analyze supervisory data from computer systems in a chemical plant.
Main Methods:
- Data was collected from 8 controllers across 4 teams over 18 shifts in an automated chemical plant.
- Real-time coding of computer screen selections was performed.
- A model was developed incorporating endogenous (biological rhythms, fatigue) and exogenous (cognitive demands, shift duration) factors.
Main Results:
- Time-of-day fluctuations indicated endogenous factors like biological rhythms and fatigue.
- Cognitive demands, particularly during shift changeover, showed a peak in information gathering.
- Shift duration correlated with reduced information gathering, suggesting fatigue.
- Circadian rhythms exhibited minimum activity at night and maximum in the afternoon.
Conclusions:
- The developed model identifies key factors influencing supervisory activity.
- The model can inform the design of optimal shift durations and schedules for shift changeover in similar industrial environments.