Task Analysis of the UH-60 Mission and Decision Rules for Developing a UH-60 Workload Prediction Model. Volume 2. Mission Analysis Appendixes A - E

Bierbaum, Carl R.; Szabo, Sandra M.; Aldrich, Theodore B.

doi:10.21236/ada201486

Cited by 26 publications

(33 citation statements)

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“…The task names, subsystems, and workload estimates from the task/workload analysis stage, and the function and segment decision rules from the model construction stage of the UH-60A analysis (Bierbaum, Szabo, & Aldrich, 1989), were entered into TOSS using the data entry routines of the system. Then, each of the 34 unique segments of the model was simulated.…”

Section: Methodsmentioning

confidence: 99%

“…To place the MH-60K workload predictions in perspective relative to other similar aircraft, a baseline workload prediction model was prepared for the UH-60A aircraft. The task/ workload analysis and model construction phases of the UH-60A baseline model were described in a report by Bierbaum, Szabo, and Aldrich (1989).…”

Section: Overviewmentioning

confidence: 99%

“…The MH-60K workload prediction model was developed with the same procedures as the UH-60A model (Bierbaum, Szabo, & Aldrich, 1989).…”

Section: Analysis II -The Mh-60k Workload Prediction Modelmentioning

confidence: 99%

“…Furthermore, the scenario developed for the MH-60K analysis is highly similar to the scenario and conditions used to develop the UH-60A workload prediction model (Bierbaum, Szabo, & Aldrich, 1989).…”

Section: Develop a Composite Mission Scenariomentioning

confidence: 99%

See 3 more Smart Citations

Task Analysis and Workload Prediction Model of the MH-60K Mission and a Comparison with UH-60A Workload Predictions. Volume 1. Summary Report

Bierbaum¹,

Hamilton²

1990

Self Cite

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Section: Methodsmentioning

confidence: 99%

Section: Overviewmentioning

confidence: 99%

“…The MH-60K workload prediction model was developed with the same procedures as the UH-60A model (Bierbaum, Szabo, & Aldrich, 1989).…”

Section: Analysis II -The Mh-60k Workload Prediction Modelmentioning

confidence: 99%

Section: Develop a Composite Mission Scenariomentioning

confidence: 99%

See 2 more Smart Citations

Task Analysis and Workload Prediction Model of the MH-60K Mission and a Comparison with UH-60A Workload Predictions. Volume 1. Summary Report

Bierbaum¹,

Hamilton²

1990

Self Cite

View full text Add to dashboard Cite

“…The workload theory implemented in this effort assigns values representing the amount of effort that must be expended in each channel in order to perform the task. Table 3 scales are taken directly from Bierbaum, Szabo, and Aldrich (1989).…”

Section: Participantsmentioning

confidence: 99%

Crew systems analysis of unmanned aerial vehicle (UAV) future job and tasking environments

Barnes¹,

Knapp²,

Tillman³

et al. 2000

PsycEXTRA Dataset

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Approved for public release; distribution is unlimited. AbstractThe purpose of the research project was to understand the future crew environments for developing unmanned aerial vehicle (UAV) systems. A variety of human engineering tools (job assessment software system [JASS], enhanced computer-aided testing [EC AT], and Micro Saint™) were used to address crew issues related to the utility of having rated aviators as crew members, supplementing current crews with imagery and intelligence specialists, and the use of automation to improve systems efficiency. Data from 70 soldiers and experts from Fort Huachuca, Arizona, Fort Hood, Texas, and Hondo, Texas, were collected as part of this effort. The general finding was that the use of cognitive methods and computerized tool sets to understand future crew environments proved to be cost effective and useful. Specifically, no evidence was found to support a requirement for rated aviators in future Army missions, but the use of cognitively oriented embedded training simulators was suggested to aid novices in developing the cognitive skills evinced by experts. The efficacy of adding imagery specialists to 96U crews was discussed, and specific recommendations related to automation were derived from the workload modeling. CONTENTS

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Informing System Design Using Human Performance Modeling

Watson

Rusnock

Miller

et al. 2017

Systems Engineering

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Humans play a key role in the operation and support of most systems and model-based systems engineering (MBSE) offers new opportunities to properly consider human capabilities and involvement. This research presents an approach for systems engineers to integrate system models with human performance modeling for early and more effective system design. Unlike analyses using traditional physics-based models found in most extant MBSE literature, adjusting system parameters for human-based analyses can greatly impact the design of the system itself. Adjusting a human-system parameter can lead to design implications including adjustments to task allocation, process and workflow, and interface design. To demonstrate this, a quantitative case-study approach is used. Starting with a set of Systems Modeling Language (SysML) diagrams, a task analysis is performed to inform an "as is" model of human performance in the Improved Performance Research Integration Tool (IMPRINT). An alternative IMPRINT model is created with varying design parameters and utilized to perform a trade study. Through the analysis, constraints and assumptions placed on the human are verified and the results of varying automation estimated. With current design emphasis in MBSE and model-based engineering (MBE), there is great opportunity to emphasize human considerations and integrate human performance analysis. Published 2017.

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Task Analysis of the UH-60 Mission and Decision Rules for Developing a UH-60 Workload Prediction Model. Volume 2. Mission Analysis Appendixes A - E

Cited by 26 publications

References 0 publications

Task Analysis and Workload Prediction Model of the MH-60K Mission and a Comparison with UH-60A Workload Predictions. Volume 1. Summary Report

Task Analysis and Workload Prediction Model of the MH-60K Mission and a Comparison with UH-60A Workload Predictions. Volume 1. Summary Report

Crew systems analysis of unmanned aerial vehicle (UAV) future job and tasking environments

Informing System Design Using Human Performance Modeling

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