Human Performance Variability in Task Execution Times Under Generic Human-System Integration Conditions in Naval Operations

Abstract

This main objective of this paper was to assess and model variability of task performance relevant to human-systems integration efforts in naval ship operations, including the estimation of task execution times under generic task conditions. A method was developed for quantifying and modeling human operator execution times in selected naval ship operations. The proposed method is based on time contributions for each task component with due consideration of three core task performance elements: skills, knowledge and task requirements. The experimental analysis utilized a hybrid approach based on linear regression, weighted scoring method and artificial neural networks. The proposed modeling approach demonstrates promising results for developing a realistic solution for assessment of task performance times relevant to training requirements and total ownership cost for competing technology upgrades, with emphasis on maintaining manpower readiness and mitigating possible performance degradation due to unforeseen mission conditions.