Emphasis on Research

The emphasis that HFE places on research has two distinguishing features: the application of the scientific method, and the knowledge of basic human capabilities. The ability to apply the scientific method is critical in situations where research on human performance is required and variations in performance must be accounted for and controlled. A standard HFE process always includes provisions for conducting human performance studies under controlled conditions, since the application of already available human performance data to the specific system/mission configuration is not always straightforward. The HFE practitioner, trained in the scientific method, is prepared to develop and exercise experimental designs which will account for the great variability in performance which distinguishes the human. By virtue of the subject matter of the discipline, the HFE practitioner is also well equipped to apply existing knowledge of human cognitive, learning, perceptual, sensory-motor, and physiological capabilities and limits to the design of interfaces between the human and system hardware, software, information and environments.

A major HFE research area is into how the application of the principles, methods and data of HFE will result in significant reductions in the incidence and impact of human errors in complex systems. The application of HFE to reduce errors is based on existing theories of human error causation in the HFE discipline. Specifically, HFE theory holds that, while errors can be attributed to deficiencies on the part of the human (slips, lapses, inattention, fatigue, insufficient skill or knowledge, etc.) the majority of errors are due to factors external to the individual, and, as such, are preventable.

These external factors can be classified as situational factors and design factors. Situational factors include those aspects of the operational setting, other than design, which influence human error incidence. These include: task difficulty, time constraints, interfering activities, poor communications, and excessive workloads. Design factors, which contribute to human errors, include aspects of the system hardware, software, procedures, environment and training, which affect human error likelihood. Design factors encompass such aspects of the system as equipment design features; information characteristics (availability, access, readability, currency, accuracy and meaningfulness); workspace arrangement; procedures and processes; environments; and training. Together the situational factors and the design factors constitute the human-systems interfaces.

In terms of avoiding human errors, the influence of personnel factors that contribute to error potential (fatigue, impairment, confusion, etc.) can be reduced through attention to requirements for "fitness for duty". Fitness for duty requires that the human in the system be fully competent, capable, rested, motivated, attentive, unimpaired, and aware of the situation. Ensuring fitness for duty is not an objective that is achieved once and then forgotten. Rather, it requires a sustained effort of engaging the human’s cognitive capabilities, vigilance, and attention through decision aiding, and intelligent prompting and cueing.

The influence of situational and design factors in error causation can be reduced through attention to the effective design and implementation of human-system interfaces. Again, these are the interfaces between the human and the other elements of the system.

Methods and data to evaluate human error potential have been developed to assess:

(a) human error potential due to equipment design including use of design check-lists, walkthroughs of operational sequences, interviews with operational personnel, observation of ongoing operations, and HFE analysis. Data include HFE standards against which measurements will be compared;

(b) human error potential due to procedures design such as use of procedures/documentation evaluation checklists, walkthroughs, procedures reviews, and interviews to determine procedure completeness, accuracy; clarity, consistency, compatibility with skill levels of users, accessibility, usability, readability, and updateability;

(c) human error potential due to training including use of training evaluation checklists, interviews with operational per-sonnel, and human factors analysis of training effectiveness;

(d) human error potential due to system manning including use of workload assessment simulation, walk-throughs of operational sequences with proscribed manning levels, interviews with operational personnel, observation of ongoing operations, and HFE analysis of the adequacy of manning levels; and

(e) human error potential due to environmental factors including use of design checklists, walkthroughs of operational sequences with suitably clothed test subjects, interviews with opera-tional personnel, observation of ongoing operations in extreme environments, and HFE analysis of the effects of intense cold, wind, reduced illumination, platform motion effects, slippery footing, sea spray, and precipitation.

A major problem faced by the HFE specialist in the evaluation of human error potential in system operation and maintenance is the difficulty in measuring human error, and estimating error probability. Human error estimates can be quantitative or qualitative. The quantitative approach to human reliability is predicated on the ability to predict mathematically the probability of error and the impact of design approaches on this probability. A number of researchers have developed tables of error probabilities for discrete activities with specific types of human-machine interfaces. The essence of this approach is that alternate design concepts can be compared based on their calculated overall probability of error.

This approach has inherent in it several significant difficulties. First of all there is the difficulty in dealing with the many variables which contribute to the probability of error occurrence at any point in time. These variables include design factors (e.g. panel layout, relationships among adjacent controls and displays, adequacy of labeling, etc.), situational factors (workloads, task complexity, etc.), personnel factors (fatigue, stress, capability level, etc.), and environmental factors (lighting, noise, etc.). Secondly, there is the problem of measuring error rates. Errors are infrequently occurring events, and the number of replications of a task required to enable prediction of error probability with any degree of statistical confidence approaches the astronomical. Any attempt to approximate error probabilities quantitatively without the empirical data cannot be justified from a statistical and a practical point of view. Another problem with error prediction is the difficulty associated with getting system personnel to report errors. Such an approach is viewed by the personnel as spotlighting their own deficiencies or those of co-workers. Finally, an approach to quantifying error rates is an exercise in overkill since the designer is not really interested in the actual error probability but only if it represents a problem for system operation or maintenance.

The approach of qualitatively describing error potential involves determining the likelihood of error given a set of design, job, personnel and environmental factors. The error likelihood approach attempts to determine if the likelihood of error presents a problem to be addressed in the design of the man-machine interfaces. It also addresses the likelihood that, having occurred, an error will be detected, and corrected.