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Management of human error by design

Design-induced errors and error prevention as well as the concept of lines of defense against human error are discussed. The concept of human error prevention, whose main focus has been on hardware, is extended to other features of the human-machine interface vulnerable to design-induced errors. In particular, it is pointed out that human factors and human error prevention should be part of the process of transport certification. Also, the concept of error tolerant systems is considered as a last line of defense against error.

Wiener, Earl

SPIDARman: System-Level Physics-Informed Detection of Anomalies in Reactor Collected Data Considering Human Errors

In nuclear power plants (NPPs), anomalies arising from sensors or human errors (HEs) can undermine the performance and reliability of plant operations. Anomaly detection models can be employed to detect sensor errors and HEs. Additionally, physics-informed machine learning models can utilize the known physics of the system, as described by mathematical equations, to ensure that sensor values are consistent with physical laws. Hence, we propose SPIDARman: System-level Physics-Informed Detection of Anomalies in Reactor Collected Data Considering Human Errors, a holistic physics-informed anomaly detection approach based on generative adversarial networks (GANs) to detect anomalies in both automatically collected sensor data and manually collected surveillance data. Here we test our approach on data collected from a flow loop testbed, showcasing its potential to detect anomalies. Results demonstrate that the proposed model performs better than the baseline GAN-based models in detecting sensor and surveillance anomalies, suggesting the potential of physics-informed anomaly detection GAN models in NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Application of the epidemiological model in studying human error in aviation

An epidemiological model is described in conjunction with the analytical process through which aviation occurrence reports are composed into the events and factors pertinent to it. The model represents a process in which disease, emanating from environmental conditions, manifests itself in symptoms that may lead to fatal illness, recoverable illness, or no illness depending on individual circumstances of patient vulnerability, preventive actions, and intervention. In the aviation system the analogy of the disease process is the predilection for error of human participants. This arises from factors in the operating or physical environment and results in errors of commission or omission that, again depending on the individual circumstances, may lead to accidents, system perturbations, or harmless corrections. A discussion of the previous investigations, each of which manifests the application of the epidemiological method, exemplifies its use and effectiveness.

Cheaney, E. S.

Using APEX to Model Anticipated Human Error: Analysis of a GPS Navigational Aid

The interface development process can be dramatically improved by predicting design facilitated human error at an early stage in the design process. The approach we advocate is to SIMULATE the behavior of a human agent carrying out tasks with a well-specified user interface, ANALYZE the simulation for instances of human error, and then REFINE the interface or protocol to minimize predicted error. This approach, incorporated into the APEX modeling architecture, differs from past approaches to human simulation in Its emphasis on error rather than e.g. learning rate or speed of response. The APEX model consists of two major components: (1) a powerful action selection component capable of simulating behavior in complex, multiple-task environments; and (2) a resource architecture which constrains cognitive, perceptual, and motor capabilities to within empirically demonstrated limits. The model mimics human errors arising from interactions between limited human resources and elements of the computer interface whose design falls to anticipate those limits. We analyze the design of a hand-held Global Positioning System (GPS) device used for radical and navigational decisions in small yacht recalls. The analysis demonstrates how human system modeling can be an effective design aid, helping to accelerate the process of refining a product (or procedure).

VanSelst, Mark

Automation of Commanding at NASA: Reducing Human Error in Space Flight

Automation has been implemented in many different industries to improve efficiency and reduce human error. Reducing or eliminating the human interaction in tasks has been proven to increase productivity in manufacturing and lessen the risk of mistakes by humans in the airline industry. Human space flight requires the flight controllers to monitor multiple systems and react quickly when failures occur so NASA is interested in implementing techniques that can assist in these tasks. Using automation to control some of these responsibilities could reduce the number of errors the flight controllers encounter due to standard human error characteristics. This paper will investigate the possibility of reducing human error in the critical area of manned space flight at NASA.

Dorn, Sarah J.

The Unintended Consequences of Focusing on Human Error (And How You Can Help)

The literature on human performance is rich with findings of cognitive failures and methods to identify, label, and measure them. In many real-world contexts, however, outcomes are driven far more by successful than failed cognition. Designers of systems intended for human use, in an effort to be “data driven,” rely upon findings from the cognitive performance literature to inform their system designs. When most available data are about human error, data-driven designs focus on the human primarily as a source of failure. Designs intended to support or replace humans often fail to acknowledge or understand the capabilities that humans routinely contribute to successful performance. Consequently, designs intended to “protect” the system from “error-prone” humans can design-out the capability for the human to effectively intervene or adapt. The development of paradigms to study successful human performance represents a significant and largely untapped opportunity for research in cognition.

Jon Holbrook

An experimental approach to validating a theory of human error in complex systems

The problem of 'human error' is pervasive in engineering systems in which the human is involved. In contrast to the common engineering approach of dealing with error probabilistically, the present research seeks to alleviate problems associated with error by gaining a greater understanding of causes and contributing factors from a human information processing perspective. The general approach involves identifying conditions which are hypothesized to contribute to errors, and experimentally creating the conditions in order to verify the hypotheses. The conceptual framework which serves as the basis for this research is discussed briefly, followed by a description of upcoming research. Finally, the potential relevance of this research to design, training, and aiding issues is discussed.

Morris, N. M.

Defining the Relationship Between Human Error Classes and Technology Intervention Strategies

One of the main factors in all aviation accidents is human error. The NASA Aviation Safety Program (AvSP), therefore, has identified several human-factors safety technologies to address this issue. Some technologies directly address human error either by attempting to reduce the occurrence of errors or by mitigating the negative consequences of errors. However, new technologies and system changes may also introduce new error opportunities or even induce different types of errors. Consequently, a thorough understanding of the relationship between error classes and technology "fixes" is crucial for the evaluation of intervention strategies outlined in the AvSP, so that resources can be effectively directed to maximize the benefit to flight safety. The purpose of the present project, therefore, was to examine the repositories of human factors data to identify the possible relationship between different error class and technology intervention strategies. The first phase of the project, which is summarized here, involved the development of prototype data structures or matrices that map errors onto "fixes" (and vice versa), with the hope of facilitating the development of standards for evaluating safety products. Possible follow-on phases of this project are also discussed. These additional efforts include a thorough and detailed review of the literature to fill in the data matrix and the construction of a complete database and standards checklists.

Wiegmann, Douglas A.

The role of AI in detecting and mitigating human errors in safety-critical industries: A review

For safety-critical industries, human error (HE) presents continual risks to system productivity, reliability and safety. Artificial intelligence (AI) and machine learning (ML) methods have emerged as promising approaches to understand, categorize and mitigate the risk of HE in safety-critical industries. Furthermore, this review offers an examination of the current landscape regarding the utilization of AI/ML with regards to HE in safety-critical industries, categorizing literature into descriptive modeling, predictive modeling, prescriptive modeling, and generative modeling techniques. Additionally, the review aims to provide insights regarding themes in literature, challenges, and future research directions. Findings of the review suggest that AI/ML methods can prove useful in addressing the HE problem across safety-critical industries.

42 ENGINEERING

Human Error In Complex Systems

Report presents results of research aimed at understanding causes of human error in such complex systems as aircraft, nuclear powerplants, and chemical processing plants. Research considered both slips (errors of action) and mistakes (errors of intention), and influence of workload on them. Results indicated that: humans respond to conditions in which errors expected by attempting to reduce incidence of errors; and adaptation to conditions potent influence on human behavior in discretionary situations.

Morris, Nancy M.

Uncertainty-Aware and Explainable Human Error Detection in the Operation of Nuclear Power Plants

The timely and accurate identification of incidents, such as human factor error, is important to restore nuclear power plants (NPPs) to a stable state. However, the identification of abnormal operating conditions is difficult because of the existence of multiple scenarios. In addition, to implement mitigation actions rapidly after an incident occurs, operators must accurately identify an incident by monitoring the trends of many variables. The mental burden posed by this can increase human error and cause failure in identifying incidents. Failure to identify incidents directly results in erroneous mitigation measures, which are detrimental to NPPs. In this study, we leverage uncertainty-aware models to identify such errors and thereby increase the chances of mitigating them. We use the data collected from a physical test bed. The goal is to identify both certain and accurate models. For this, the two main aspects of focus in this study are explainable artificial intelligence (XAI) and uncertainty quantification (UQ). While XAI elucidates the decision pathway, UQ evaluates decision reliability. Their integration paints a comprehensive picture, signifying that understanding decisions and their confidence should be interlinked. Thus, in this study we leverage UQ measures (e.g. entropy and mutual information) along with Shapley additive explanations to gain insights into the features contributing to both accuracy and uncertainty in error identification. Furthermore, our results show that uncertainty-aware models combined with XAI tools can explain the artificial intelligence–prescribed decisions, with the potential of better explaining errors for the operators.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS

Human Error and the International Space Station: Challenges and Triumphs in Science Operations

Any system with a human component is inherently risky. Studies in human factors and psychology have repeatedly shown that human operators will inevitably make errors, regardless of how well they are trained. Onboard the International Space Station (ISS) where crew time is arguably the most valuable resource, errors by the crew or ground operators can be costly to critical science objectives. Operations experts at the ISS Payload Operations Integration Center (POIC), located at NASA's Marshall Space Flight Center in Huntsville, Alabama, have learned that from payload concept development through execution, there are countless opportunities to introduce errors that can potentially result in costly losses of crew time and science. To effectively address this challenge, we must approach the design, testing, and operation processes with two specific goals in mind. First, a systematic approach to error and human centered design methodology should be implemented to minimize opportunities for user error. Second, we must assume that human errors will be made and enable rapid identification and recoverability when they occur. While a systematic approach and human centered development process can go a long way toward eliminating error, the complete exclusion of operator error is not a reasonable expectation. The ISS environment in particular poses challenging conditions, especially for flight controllers and astronauts. Operating a scientific laboratory 250 miles above the Earth is a complicated and dangerous task with high stakes and a steep learning curve. While human error is a reality that may never be fully eliminated, smart implementation of carefully chosen tools and techniques can go a long way toward minimizing risk and increasing the efficiency of NASA's space science operations.

Harris, Samantha S.

What Happened, and Why: Toward an Understanding of Human Error Based on Automated Analyses of Incident Reports

The objective of the Aviation System Monitoring and Modeling (ASMM) project of NASA s Aviation Safety and Security Program was to develop technologies that will enable proactive management of safety risk, which entails identifying the precursor events and conditions that foreshadow most accidents. This presents a particular challenge in the aviation system where people are key components and human error is frequently cited as a major contributing factor or cause of incidents and accidents. In the aviation "world", information about what happened can be extracted from quantitative data sources, but the experiential account of the incident reporter is the best available source of information about why an incident happened. This report describes a conceptual model and an approach to automated analyses of textual data sources for the subjective perspective of the reporter of the incident to aid in understanding why an incident occurred. It explores a first-generation process for routinely searching large databases of textual reports of aviation incident or accidents, and reliably analyzing them for causal factors of human behavior (the why of an incident). We have defined a generic structure of information that is postulated to be a sound basis for defining similarities between aviation incidents. Based on this structure, we have introduced the simplifying structure, which we call the Scenario as a pragmatic guide for identifying similarities of what happened based on the objective parameters that define the Context and the Outcome of a Scenario. We believe that it will be possible to design an automated analysis process guided by the structure of the Scenario that will aid aviation-safety experts to understand the systemic issues that are conducive to human error.

Maille, Nicolas P.

Analyzing human errors in flight mission operations

A long-term program is in progress at JPL to reduce cost and risk of flight mission operations through a defect prevention/error management program. The main thrust of this program is to create an environment in which the performance of the total system, both the human operator and the computer system, is optimized. To this end, 1580 Incident Surprise Anomaly reports (ISA's) from 1977-1991 were analyzed from the Voyager and Magellan projects. A Pareto analysis revealed that 38 percent of the errors were classified as human errors. A preliminary cluster analysis based on the Magellan human errors (204 ISA's) is presented here. The resulting clusters described the underlying relationships among the ISA's. Initial models of human error in flight mission operations are presented. Next, the Voyager ISA's will be scored and included in the analysis. Eventually, these relationships will be used to derive a theoretically motivated and empirically validated model of human error in flight mission operations. Ultimately, this analysis will be used to make continuous process improvements continuous process improvements to end-user applications and training requirements. This Total Quality Management approach will enable the management and prevention of errors in the future.

Bruno, Kristin J.

Reflections on human error - Matters of life and death

The last two decades have witnessed a rapid growth in the introduction of automatic devices into aircraft cockpits, and eleswhere in human-machine systems. This was motivated in part by the assumption that when human functioning is replaced by machine functioning, human error is eliminated. Experience to date shows that this is far from true, and that automation does not replace humans, but changes their role in the system, as well as the types and severity of the errors they make. This altered role may lead to fewer, but more critical errors. Intervention strategies to prevent these errors, or ameliorate their consequences include basic human factors engineering of the interface, enhanced warning and alerting systems, and more intelligent interfaces that understand the strategic intent of the crew and can detect and trap inconsistent or erroneous input before it affects the system.

Wiener, Earl L.

On Space Exploration and Human Error: A Paper on Reliability and Safety

NASA space exploration should largely address a problem class in reliability and risk management stemming primarily from human error, system risk and multi-objective trade-off analysis, by conducting research into system complexity, risk characterization and modeling, and system reasoning. In general, in every mission we can distinguish risk in three possible ways: a) known-known, b) known-unknown, and c) unknown-unknown. It is probably almost certain that space exploration will partially experience similar known or unknown risks embedded in the Apollo missions, Shuttle or Station unless something alters how NASA will perceive and manage safety and reliability

Bell, David G.

Predicting Human Error in Air Traffic Control Decision Support Tools and Free Flight Concepts

The document is a set of briefing slides summarizing the work the Advanced Air Transportation Technologies (AATT) Project is doing on predicting air traffic controller and airline pilot human error when using new decision support software tools and when involved in testing new air traffic control concepts. Previous work in this area is reviewed as well as research being done jointly with the FAA. Plans for error prediction work in the AATT Project are discussed. The audience is human factors researchers and aviation psychologists from government and industry.

Mogford, Richard