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Thrust 3: Effectiveness

Title

3A.3: Human Performance Modeling and User-centered Design

Project Leader

Prof. Steven Jiang (NCAT)

Statement of Project Goals

The goal of the project is to develop an integrated human performance model that can address both cognitive and physical perspectives simultaneously in complex fluid power (FP) systems where human operators interact with the machines, and to use user centered design approach to develop human machine interface for selected fluid power systems (test beds) that are user-centered, safe, easy and comfortable to use.

Project Role in Support of Strategic Plan

In fluid power systems where human operators interact with the machines, the overall effectiveness of the system depends on the effectiveness of the human operator performance.  Modeling human performance has been proven to be a very critical tool in developing/improving systems.  However, existing performance modeling tools often concentrate on either cognitive or physical aspect of the operator, failing to take into the consideration the interaction between the two.  To better understand operator performance, a new integrated model needs to be developed that addresses this concern.  This project proposes a framework to integrate cognitive and physical models of human performance for a fluid power system.  A case study using the excavator test bed is underway to validate the integrated model and provide design suggestions for other complex fluid power systems.  Specifically, the interaction between operator and the machine will be studied to assess the overall system effectiveness.  With regard to any revision or a new design of a fluid power system interface,  a user centered design approach is recommended so that end users are involved in the design process from the very early stage and ensures the interface will be easy, comfortable, and safe to use, and consequently, will be more effective.

Description and Explanation of Research Approach

Research efforts in complex fluid power systems where human operators interact with the machines to complete tasks are mainly focused on improving machine performance.  For instance, excavators have gone through technological innovations to improve the machine efficiency over the years.  However, issues such as high pressure, friction, containment, and constant movement continue to present problems with controllability, leaks, and losses in efficiency in many fluid power systems. Therefore, research is needed to improve machine performance in FP systems.  Unfortunately, the side effect of this is that very little attention has been given to operators of those fluid power systems. In fact, many complex fluid power systems are still manually controlled, requiring excessive amounts of energy, intense task concentration, high skill level, and decision-making capabilities.  Operators need to interact with machines effectively to accomplish the desired tasks.  Unfortunately, complex interactions between the operator and the system due to these requirements can often lead to errors and misunderstandings, and consequently degrade the overall system performance despite the fact the machine performance has advanced.  Machines alone simply cannot accomplish complex tasks. Human performance deals with the physical and cognitive limitations of humans and has been widely used in aviation, automobile, military, medicine, and other industries.  However, only limited research has been conducted in those complex fluid power systems [1].

Research efforts on human performance often concentrate on either physical or cognitive part of the performance, failing to take into consideration the interaction between those two.  This is especially true for the complex fluid power systems [1].  With the development of fluid power technology at CCEFP moves forward, it is critical to assess the impact of those technology have on the interaction between human operators and machines where these technologies will be deployed.  For those complex fluid power systems where both physical and cognitive resources of human operators are required, it is even more critical to evaluate the impact on human performance.  Therefore, a framework that integrates both physical and cognitive human performance needs to be developed for those complex fluid power systems.  We adopted the following sequential approaches:

  1. Define levels of human performance: environment, system, human, and task.
  2. Define performance states.
  3. Differentiate Cognitive and Physical Functions.
  4. Categorization of metrics and extraction of performance variables.
  5. Link of performance variables.
  6. Select modeling tools to support the framework.
  7. Integrate performance models.
  8. Implement the framework.
  9. Applying the framework to appropriate fluid power systems.

Relationship of Performance States

Figure 1: Definition and relationship of performance states

LInking of performance variables

Figure 2: Linking of performance variables

Integrated Human Performance Model Representation

Figure 3. Integrated Human Performance Model Representation

References

1.     Hughes, K., Jiang, X. (2010), "Using Discrete Event Simulation to Model Excavator Operator Performance", International Journal of Human Factors and Ergonomics in Manufacturing and Service Industries, 20(5), 408-423.

2.     Hughes, K., Jiang, X., Jiang, Z., Mountjoy, D., Park, E. (2010), "A Preliminary Study of an Integrated Human Performance Model", Proceedings of the 2010 Industrial Engineering Research Conference, Cancun, Mexico, June 5-9,2010.

3.     Delpish, R., Jiang, X., Park, E. , Udoka, S., Jiang, Z., (2010), "Development of a User-Centered Framework for Rescue Robot Interface Design", Proceedings of the 2010 Industrial Engineering Research Conference, Cancun, Mexico, June 5-9,2010.

4.     Jenkins, Q., Jiang, X. (2010), "Measuring Trust and Application of Eye Tracking in Human Robotic Interaction", Proceedings of the 2010 Industrial Engineering Research Conference, Cancun, Mexico, June 5-9,2010.

5.     Liu, Y., Jiang, X., Jiang, Z., Park, E. (2010), "Predicting Backhoe Excavator Operator Performance Using Digital Human Modeling", Proceedings of the 2010 Industrial Engineering Research Conference, Cancun, Mexico, June 5-9,2010.

6.     Osafo-Yeboah, B., Elton, M., Jiang, X., Book, W., Park, E. (2010), "Usability Evaluation of a Coordinated Excavator Controller with Haptic Feedback", Proceedings of the 2010 Industrial Engineering Research Conference, Cancun, Mexico, June 5-9,2010.

7.     Chung, C., Jiang, X., Jiang, Z., Udoka, S. (2010), "Using Digital Human Modeling to Predict Operator Performance of a Compact Rescue Crawler", Proceedings of the 2010 Industrial Engineering Research Conference, Cancun, Mexico, June 5-9,2010.