Visualizing failure effects in complex human-machine systems

The ability to understand a system's behavior in both normal and failed conditions is fundamental to the design of error tolerant systems as well as to the development of diagnostics. The System Analysis for Failure and Error Reduction (SAFER) Project seeks to provide designers with tools to visualize potential sources of error and their effects early in the design of human-machine systems. The project is based on an existing technology that provides a failure-space modeling environment, analysis capabilities for troubleshooting, and error diagnostics using design data of machine systems. The SAFER Project extends the functionality of the existing technology in two significant ways. First, by adding a model of human error probability within the tool, designers are able to estimate the probabilities of human errors and the effects that these errors may have on system components and on the entire system. Second, the visual presentation of failure-related measures and metrics has been improved through a process of user-centered design. This paper will describe the process that was used to develop the human error probability model and will present novel metrics for assessing failure within complex systems.