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Complex systems, such as nuclear power plants and commercial airliners, place significant demands on human performance with respect to safe operation. Accidents and incidents indicate that unwanted operator performance variations make an important contribution to the risk associated with these systems, even where high levels of automation are introduced []. As a result, it is essential that system safety programs encompass assessment and support of operator activities. Collection and analysis of human performance data provide key inputs into this process.
This article describes theoretical and practical issues in the collection of human performance data for system safety purposes, and discusses the links between theory and practice in that context, using observations in full-scope, high-fidelity training simulators as the main examples. The basis of data collection, in theory, is described through references to models, classifications, methods, and approaches to data validity. The status of contemporary theory in the human sciences and its implications are also discussed. Several practical issues are also outlined, including barriers to data collection and the selection of data collection techniques. Finally, conclusions are drawn regarding the importance of human performance data collection for system safety, and the interplay between theory and practice.
In the context of human performance data collection, attempts at practice without a clearly articulated theoretical foundation can lead to unfocused effort, invalid data and wasted resources. Theory must, to some degree, accommodate practical constraints if it is to be useful. Consequently, knowledge of relevant theory, practice and the relationship between the two is vital for the efficient collection of valid data for application in system safety projects.
Background
In industrial settings, human performance data are collected for system safety application purposes, such as:
- Assessment of human reliability, where the aim is to provide qualitative and quantitative input to system safety assessment
- Application in design, where data can indicate necessary improvements to tasks, displays, procedures, etc.
- Training feedback, where the intention is to use data to improve the safety performance of individuals, teams and the training program
Data collected for one purpose are not necessarily useful for another []. However, in practice, data collected for the three high-level purposes identified above overlap considerably []. At a more detailed level, the goals of data collection can include identification of operator performance variations (such as misdiagnoses of faults), quantification of human error probabilities, verification of procedures, appraisal of the adequacy of supervisory activities, and assessment of the quality of communications within operating teams. These goals, and many others that can be pursued through data collection, have important safety implications.
Data about operator performance can be obtained from several sources, including:
- Observations of human performance in full-scope, high-fidelity training simulators
- Event reports
- Accident investigations
- Observations in the field
In outline form, the data collection activity entails establishment of a theoretical basis, implementation of a practical process to collect data, analysis of the collected data to yield outputs of interest, such as estimates of human reliability and risk reduction recommendations, and application of these outputs in safety assessment, design, training and elsewhere.
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