Determination of the Proper Rest Time for a Cyclic Mental Task Using ACT-R Architecture

Abstract

Objective Analysis of the effect of mental fatigue on a cognitive task and determination of the right start time for rest breaks in work environments. Background Mental fatigue has been recognized as one of the most important factors influencing individual performance. Subjective and physiological measures are popular methods for analyzing fatigue, but they are restricted to physical experiments. Computational cognitive models are useful for predicting operator performance and can be used for analyzing fatigue in the design phase, particularly in industrial operations and inspections where cognitive tasks are frequent and the effects of mental fatigue are crucial. Method A cyclic mental task is modeled by the ACT-R architecture, and the effect of mental fatigue on response time and error rate is studied. The task includes visual inspections in a production line or control workstation where an operator has to check products' conformity to specifications. Initially, simulated and experimental results are compared using correlation coefficients and paired t test statistics. After validation of the model, the effects are studied by human and simulated results, which are obtained by running 50-minute tests. Results It is revealed that during the last 20 minutes of the tests, the response time increased by 20%, and during the last 12.5 minutes, the error rate increased by 7% on average. Conclusion The proper start time for the rest period can be identified by setting a limit on the error rate or response time. Application The proposed model can be applied early in production planning to decrease the negative effects of mental fatigue by predicting the operator performance. It can also be used for determining the rest breaks in the design phase without an operator in the loop.

Reliability optimization model in man‐machine systems considering human factors in uncertain situations

“…Since human workload, in most situations, acts as a stressor, it is assumed to be proportional to arousal 19 . Consequently, perfect automation design permits operators to compensate for conditions, including workload redlines, that is, task overload or underload, and extended working hours which may all eventually result in increased fatigue and an augmented risk of performance decrements 20,21 . Certainly, the type of functions which can be skill‐, rule‐ or knowledge‐based 22 plays an important role in the level of human workload.…”