UTASiMo: a simulation-based tool for task analysis. (January 2018)

• Record Type: Journal Article
• Authors: Angelopoulou, Anastasia; Mykoniatis, Konstantinos
• Is Part Of: Simulation. Volume 94:Number 1(2018)
• Page Start: 43
• Page End: 54
• Publication Date: 2018-01
• Subjects: Agent based -- discrete event -- human operator variability -- modeling -- simulation -- task analysis -- UTASiMo; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549717711270
• Languages: English
• ISSNs: 0037-5497

Abstract

Research on task analysis and human performance has focused on the development of adequate tools, models, and methods to understand, analyze, and improve the relationship between humans and systems. As technology continues to advance and to change the nature of human work, techniques of analysis are changing to meet the new needs. This work attempts to fill the gaps in the current task analysis tools and describes the architecture and development of a simulation model, named UTASiMo. UTASiMo is a simulation tool that aims to enhance task analysis by automatically generating a multi-method simulation model for well-defined tasks based on a spreadsheet template filled in by the user. The generated model analyzes and simulates tasks performed by individual simulated agents representing human operators while accounting for the estimation of an operator's utilization and error prediction. This work highlights the design, development, and evaluation of the hybrid architecture (discrete event and agent based) of UTASiMo. The development of the system dynamics model, which is responsible for the human error assessment, is a work in progress and is excluded from the present paper. A real-world case study has been adapted to evaluate the hybrid architecture of UTASiMo. The same case study was modeled using the Micro Saint simulation tool. The results produced by UTASiMo were compared with the real-world data as well as with the results produced by Micro Saint for validation purposes. The comparisons indicate the validity of the UTASiMo-generated model and also that the hybrid architecture produces more variability in the results than using only one method. The comparisons also show promise that the tool will reduce the time and effort of the task analysis simulation.