Human Systems Integration Research Articles

A systems engineering framework for integration of cognitive ergonomics in smart factory configurations

The current manufacturing industry is increasingly compelling manufacturing firms to turn to technology to improve operations. A relatively unexplored area is the role that cognitive ergonomics with the effective implementation of technology has on smart factory configurations. The manufacturing industry continues to increase the information processing content operators engage in (i.e., multitasking) to perform their work tasks. Cognitive ergonomics are known predictors of preventing injuries and accidents in industry and drive towards improving work conditions, human performance, safety, and avoiding human errors. Cognitive ergonomics evaluates the interaction of the human operator with the task they are performing and their mental capabilities. Although these principles are currently being explored in manufacturing, it is still uncertain how cognitive ergonomics can be applied to smart factory configurations. A smart factory combines technology to create a network that has the capability to communicate and act independently to advance manufacturing systems further. Smart factories can assist people and machines by interacting with the environment surrounding to make tasks more comfortable and more efficient. By investigating current literature on cognitive ergonomics, the goal of this work is to pave the way for further research into human-systems integration of technology implementation in smart factory configurations. The technology methods discussed will seek to aid the human operator in the decision-making process throughout their work task. Also, a framework is developed for the integration of cognitive ergonomics in smart factory configurations using the D-E-J-I systems engineering model. In summary, this paper aims to investigate how current cognitive ergonomic principles can be utilized to support the effective implementation of technology to aid the human operator in smart factory configurations.

Human Factors Contributions to the Development of Standards for Displays of Unmanned Aircraft Systems in Support of Detect-and-Avoid.

The aim is to provide a high-level synthesis of human factors research that contributed to the development of detect-and-avoid display requirements for unmanned aircraft systems (UAS). The integration of UAS into the U.S. National Airspace System is a priority under the Federal Aviation Administration's Modernization and Reform Act. For UAS to have routine access to the National Airspace System, UAS must have detect-and-avoid capabilities. One human factors challenge is to determine how to display information effectively to remote pilots for performing detect-and-avoid tasks. A high-level review of research informing the display requirements for UAS detect-and-avoid is provided. In addition, description of the contributions of human factors researchers in the writing of the requirements is highlighted. Findings from human-in-the-loop simulations are used to illustrate how evidence-based guidelines and requirements were established for the display of information to assist pilots in performing detect-and-avoid. Implications for human factors are discussed. Human factors researchers and engineers made many contributions to generate the data used to justify the detect-and-avoid display requirements. Human factors researchers must continue to be involved in the development of standards to ensure that requirements are evidence-based and take into account human operator performance and human factors principles and guidelines. The research presented in this paper is relevant to the design of UAS, the writing of standards and requirements, and the work in human-systems integration.

ICT Governance, Human Factors and Cyber Situational Awareness

The article summarises the results from the four sessions during the Second International Scientific Conference Digital Transformation, Cyber Security and Resilience DIGILIENCE 2020 These are ICT Governance and Management for Digital Transformation, Cyber Situational Awareness and Information Exchange, Human Systems Integration Approach to Cybersecurity and Education and Training for Cyber Resilience

STEAM for Space Leaders of Tomorrow: Human–Systems Integration as a Technique and an Art

Human–systems integration (HSI) is progressively becoming a central discipline. HSI is grounded on the coconstruction of technology, organizations, and people's activities and jobs. HSI also requir...

Exploring Bayesian analyses of a small-sample-size factorial design in human systems integration: the effects of pilot incapacitation

In contrast to many other areas of science, the highly-topical Bayesian statistics have not been adopted widely to Human Systems Integration (HSI). These methods overcome the weaknesses of the frequentist null-hypothesis significance testing. Bayesian probabilities reflect a direct and quantifiable evidence for either the null- or the alternative hypothesis given the data. A case study on the effects of pilot incapacitation on workload and technology acceptance during different flight phases for single pilot operations (SPO) compared to the contemporary dual crewing configuration demonstrates how Bayesian statistics produce much more transparent and unambiguous results. For example, workload was higher during incapacitation than in normal flight as well as during arrival than in other flight phases. These effects were independent from crew distribution encouraging further research regarding SPO. Finally, Bayesian statistics remain robust against the sample size which is why they provide interpretable results even for small-sample-size designs prevalent in many application domains of HSI.

Implementing Human Systems Integration in the Department of Homeland Security

The Department of Homeland Security (DHS) formally incorporated Human Systems Integration (HSI) in systems and policy development in 2012. Since then, DHS components have been establishing HSI capabilities to meet their unique human needs. This discussion panel will focus on the operational transformation and governance strategy for implementing a successful human systems integration (HSI) program across components within the Department of Homeland Security (DHS). Members of the Transportation Security Administration (TSA), United States Coast Guard (USCG), and Department of Homeland Security Science and Technology Directorate (DHS S&T) will discuss the challenges faced when advocating for HSI, and the best practices developed to better integrate research activities with systems engineering.

The National Academies Board on Human System Integration (BOHSI) Panel: Explainable AI, System Transparency, and Human Machine Teaming

The National Academies Board on Human Systems Integration (BOHSI) has organized this session exploring the state of the art and research and design frontiers for intelligent systems that support effective human machine teaming. An important element in the success of human machine teaming is the ability of the person on the scene to develop appropriate trust in the automated software (including recognizing when it should not be trusted). Research is being conducted in the Human Factors community and the Artificial Intelligence (AI) community on the characteristics that software need to display in order to foster appropriate trust. For example, there is a DARPA program on Explainable AI (XAI). The Panel brings together prominent researchers from both the Human Factors and AI communities to discuss the current state of the art, challenges and short-falls and ways forward in developing systems that engender appropriate trust.

HFES Goes to Washington

Learn how HFES members can get involved in advocating for the science of human factors and ergonomics (HF/E). This panel will present an overview of the Human Factors and Ergonomics Society’s activities in working to promote the science of HF/E in Congress and across government agencies. The activities of the Government Relations Committee will be discussed, to include outreach to Congress and responses to pending legislation, as well as the development of policy statements on Human Systems Integration, Airline Seating, and Autonomous Vehicles. Nicholas Saab will provide a discussion of the many activities Lewis-Burke Associates engages in on behalf of HFES. As our government relations experts, Lewis-Burke tracks relevant legislation, and activities and opportunities for HF/E involvement in supporting government operations across its many agencies. They help represent the society on the ground in DC and provide inputs on our behalf across a wide range of topics. New to HFES, the Science Policy Fellows program was established in 2018 to provide a valuable opportunity for members to learn how to navigate the federal policy process and successfully advocate for human factors and ergonomics on the national stage. They receive extensive training in public affairs, advocacy, and outreach, and represent HFES in an annual Capitol Hill day in Washington, DC. In addition to working with the Government Relations Committee, the Science Policy Fellows are each developing a tailored outreach program to include continued participation in Capitol Hill Day and interactions with policy makers in DC, supporting the Society’s policy objectives at the local and/or state level, serving on the GRC or a subcommittee, or other activities developed by each participant. Our 2018 Science Policy Fellows, Caroline Cao, Holly Handley and Carisa Harris-Adamson, will each present on their experiences and activities. This special session provides an opportunity for HFES members to learn more about how the society is representing and supporting our profession in Washington, and about how they can get involved in promoting human factors and ergonomics at the local, state or national level.

Where do we start? Guidance for technology implementation in maintenance management for manufacturing.

Recent efforts in Smart Manufacturing (SM) have proven quite effective at elucidating system behavior using sensing systems, communications and computational platforms, along with statistical methods to collect and analyze real-time performance data. However, how do you effectively select where and when to implement these technology solutions within manufacturing operations? Furthermore, how do you account for the human-driven activities in manufacturing when inserting new technologies? Due to a reliance on human problem solving skills, today's maintenance operations are largely manual processes without wide-spread automation. The current state-of-the-art maintenance management systems and out-of-the-box solutions do not directly provide necessary synergy between human and technology, and many paradigms ultimately keep the human and digital knowledge systems separate. Decision makers are using one or the other on a case-by-case basis, causing both human and machine to cannibalize each other's function, leaving both disadvantaged despite ultimately having common goals. A new paradigm can be achieved through a hybridized systems approach - where human intelligence is effectively augmented with sensing technology and decision support tools, including analytics, diagnostics, or prognostic tools. While these tools promise more efficient, cost-effective maintenance decisions, and improved system productivity, their use is hindered when it is unclear what core organizational or cultural problems they are being implemented to solve. To explicitly frame our discussion about implementation of new technologies in maintenance management around these problems, we adopt well established error mitigation frameworks from human factors experts - who have promoted human-systems integration for decades - to maintenance in manufacturing. Our resulting tiered mitigation strategy guides where and how to insert SM technologies into a human-dominated maintenance management process.

Toward a cooperation index based on EEG-workload causality: preliminary findings on aerospace-like tasks.

According to Human-System Integration analyses, cooperation between humans is one of the most relevant factors in many of today's human activities: do not take it into account in models of working environments is highly farfetched. Although the Human Factor aspects have obtained much benefit from the use of neurophysiological signals to estimate human-machine interaction, very few are the indications about neurophysiological analysis of human cooperation deviating from typical laboratory tasks. Among these, some evidence showed that there is a relationship between the mental workload experienced by the subjects cooperating and some characteristics of the brain network obtained through multi-subjects connectivity analysis. Accordingly, this work aimed to identify common dynamics in time series that describe the EEG-based mental workload of cooperating subjects and to exploit this information to create an index of cooperation. In order to answer the question whether a causality between the workload values of the two subjects can be in some way discerned and related to the cooperation required by the task, Granger's causality test has been performed. This method was applied to two different tasks simulating features of the aerospace domain. The results showed that the causality test was statistically significant for the most collaborating couple. In addition, causality values are modulated by the presence of real couples compared to fake couples. The extension of the experimental sample could open up the possibility for the development of an objective and neurophysiological signals-based cooperation index.

Engineering, Life Sciences, and Health/Medicine Synergy in Aerospace Human Systems Integration: The Rosetta Stone Project—An Executive Summary

Abstract The successful design, development, and operation of human-rated and human-operated systems require the combined effort of engineering, science, and human health disciplines. This is extre...

Individual Differences in Attributes of Trust in Automation: Measurement and Application to System Design.

Computer-based automation of sensing, analysis, memory, decision-making, and control in industrial, business, medical, scientific, and military applications is becoming increasingly sophisticated, employing various techniques of artificial intelligence for learning, pattern recognition, and computation. Research has shown that proper use of automation is highly dependent on operator trust. As a result the topic of trust has become an active subject of research and discussion in the applied disciplines of human factors and human-systems integration. While various papers have pointed to the many factors that influence trust, there currently exists no consensual definition of trust. This paper reviews previous studies of trust in automation with emphasis on its meaning and factors determining subjective assessment of trust and automation trustworthiness (which sometimes but not always are regarded as an objectively measurable properties of the automation). The paper asserts that certain attributes normally associated with human morality can usefully be applied to computer-based automation as it becomes more intelligent and more responsive to its human user. The paper goes on to suggest that the automation, based on its own experience with the user, can develop reciprocal attributes that characterize its own trust of the user and adapt accordingly. This situation can be modeled as a formal game where each of the automation user and the automation (computer) engage one another according to a payoff matrix of utilities (benefits and costs). While this is a concept paper lacking empirical data, it offers hypotheses by which future researchers can test for individual differences in the detailed attributes of trust in automation, and determine criteria for adjusting automation design to best accommodate these user differences.

Human Factors Considerations for Enabling Functional Use of Exosystems in Operational Environments

The domain of human factors considers how to improve system design by considering the human within the design process, rather than designing a system and then considering the effects on the human after the design is completed. There have been decades of work in the domain of human factors and human–system integration in applications for complex systems to understand concepts within the physical domain (e.g., system sizing and injury risk) and cognitive domain (e.g., workload, situation awareness, and automation mode confusion). Exosystem technologies are reaching the point where the transition to an operational environment is within reach. This paper presents human factors principles related to the cognitive domain. We present examples of these concepts in the context of exosystem design for operational environments and to aid the development of system evaluation standards. We also review current exosystem evaluation methods and present how performance metrics and tasks can be expanded to better describe system function in the context of known human factors complexities.

Evaluating sociotechnical dynamics in a simulated remotely-piloted aircraft system: a layered dynamics approach

As coordination mechanisms change and technology failures occur, a sociotechnical system must reorganise itself across human and technological layers to maintain effectiveness. We present a study examining reorganisation across communication, controls and vehicle layers of a remotely-piloted aircraft system (RPAS) using a layered dynamics approach. Team members (pilot; navigator; photographer) performed 5 simulated RPAS missions using different operator configurations, including all-human and human-autonomy teams. Reorganization (operationally defined using entropy) time series measured the changing system reorganisation profiles under different operator configurations and following autonomy failures. Correlations between these reorganisation profiles and team effectiveness scores describe the manner in which the system had to be coordinated to maintain effectiveness under these changing conditions. Four unplanned autonomy failures were analysed to visualise system reorganisation following a technology failure. With its objective and real-time modelling and measurement capabilities, layered dynamics complements existing systems thinking tools for understanding sociotechnical complexity and enhancing system effectiveness.Practitioner summary: A layered dynamics approach for understanding how a sociotechnical system dynamically reorganises itself is presented. The layered dynamics of RPAS were analysed under different operator configurations and following autonomy failures. Layered dynamics complements existing system-thinking tools for modelling sociotechnical system complexity and effectiveness.Abbreviation: RPAS: remotely-piloted aircraft system; HIS: human-systems integration; EAST: event analysis of systemic teamwork; H1: hypothesis 1; H2: hypothesis 2; H3: hypothesis 3; CERTT-STE: cognitive engineering research on team tasks--synthetic task environment; AVO: air vehicle operator; PLO: payload operator; DEMPC: data exploitation, mission planning, and communications; ACT-R: adaptive control of thought-rational; sec: seconds; ANOVA: analysis of variance

Human System Integration at System Limits and System Failure of Cooperatively Interacting Automobiles: Concept and First Results

Abstract In 2019, autonomy and autonomous cars are still heavily debated and investigated, but might be at the peak point of public attention, which might ramp down in the next years without diminishing the need to develop safe autonomous capabilities. Thinking beyond autonomy, the research and development paradigm of human autonomy teaming, here cooperativity and cooperatively interacting vehicles makes good use of autonomous capabilities and functions and puts these into the service of a cooperative system of systems. In this system, automobiles are cooperating with each other, with other traffic participants and with drivers and passengers on board. This article focuses on one aspect of system cooperation, on the cooperation between the vehicle and inhabitants in normal operations, at the limits of the automation, and at system failure. Modes, transitions, and especially the take-over ability are identified as crucial elements of a system architecture. A model to determine the take-over ability online and an interaction design to couple this model with the automation and the driver is presented and enriched with first results. An outlook sketches the next steps towards a confidence horizon as an interaction element to bridge the dangerous valleys of automation and cooperation with autonomous functions.

USING THE STUDENTS' STATE INDICES FOR DESIGN OF ADAPTIVE LEARNING SYSTEMS

The paper discusses what scientific ideas could be used to increase effectiveness of adaptive learning systems. Possibilities to use changes of learner's cognitive state indicators under influence of internal (heart rate and blood pressure) and external (speed and density of solar wind) factors are discussed. It is described experience of use of the learner's cognitive state assessment (accounting psychological, physiological and external parameters) to assess his/her cognitive changes over weeks. The experimental results demonstrated individual nature of subjects' psychological and physiological changes over observation time (1,5 month) and their relationship. The authors' approach is based on the model describing formation and functioning of the “functional system of cognitive activity”. The question discussed is: what indices of a human performance indicators (behavioral, internal and/or external) could be useful for model construction? A human cognitive load can be under influence of different external and internal factors that can provoke his/her performance degradation. The results demonstrated the similar tendency for studied groups of subjects in previous studies: individual nature of changes of cognitive and physiological indices in day-to-day performance, as well as potentially significant influence of parameters of solar wind on them. As a result, such type of measurements of internal (physiological) and external (solar physics) parameters in combination with test performance indices could be used for assessment and prediction of effectiveness of cognitive activity, and adaptation of learning process according to the particularly learner's readiness to learn on a particular day and time. Different approaches and methods were proposed to take into account a human state, abilities, individual features to plan a human activity. Looking at learning as a type of activity in human-system integration, it is possible to consider today’s learner as an operator-researcher who acts in digital environment. At the same time, a human and tools of activity need mutual adaptation in complex systems. Psychophysiological model of learning and cognitive abilities development could be a basis for more effective design of learning achievements, organization and process, their quality, namely for adaptive learning on the base of accounting a learner's current cognitive state indices. Those results could be applied in design of adaptive learning systems, as it was made for industry in the previous developments of the authors. Principles of use of student's state indices in adaptive learning systems are proposed.

Design methodology for a simulator of a robotic surgical system.

Traditional spinal surgery procedures are completed with limited direct visualization. This imposes limitations on the surgeon's ability to place screws into the spine. The Mazor Renaissance robotic system was developed to improve the accuracy of pedicle screw insertion. Current training for this device comes with significant constraints. This suggests that a simulation-based solution may be valuable to the current training. This paper describes efforts to apply the theories of human-system integration (HSI) and instructional system design to define the requirements for a design of a simulator for specific robotic surgery system. From this, an instructional plan was conducted, to which an HSI-driven design document for a simulation system was developed. This paper describes the efforts to create a design method for a simulator of a specific robotic surgery system and provides a blended design process, which can be used during the early life cycle of any surgical simulation design.

The National Academies Board on Human System Integration Panel: Integrating Social and Behavioral Sciences Within the Weather Enterprise

The National Academies Board on Human-Systems Integration (BOHSI) has organized this session. An initial presentation by the Staff Director and the Chair of BOHSI will provide an overview of the Academies and BOHSI. Then the panel chair will present the findings of the 2017 National Academies consensus study entitled “Integrating Social and Behavioral Sciences Within the Weather Enterprise”, a collaborative effort overseen by the Board on Atmospheric Sciences and Climate and the Board on Human-Systems Integration. The presentation will include discussion of the critical need for integrating social and behavioral sciences into the weather enterprise. It will also include a summary of relevant research, private sector activities, current research to operations progress, data collection activities, funding support and barriers to progress. It will summarize research gaps and present a framework to sustainably use social and behavioral science research in the weather enterprise. Panelists will address issues related to future opportunities for human factors researchers and practitioners and will engage the audience in a discussion of these issues.

Human Systems Integration Risk Management Tool

The Human Systems Integration Risk Management Tool (HSI-RMT) is a software-based interactive application designed to track, analyze, and mitigate human performance risk associated with the development of systems. It spans system development from concept formation to sustainment, that is – across the entire system acquisition lifecycle. HSI-RMT combines two previously developed tools: the HSI Capabilities and Requirements Tool (HSI-CART) and the HSI Program Risk Assessment Tool (HSI-PRAT). The former addresses HSI in capability requirements planning and the latter human performance considerations in system acquisition. HSI-RMT overlays a risk management approach onto the two tools in order to help the HSI practitioner identify, analyze, and mitigate human performance risk to program success. Tool content, in the form of best practice questions, was developed by Air Force HSI and industry subject matter experts. HSI-RMT promises to be a useful tool to help HSI practitioners manage human-centric risk across the system lifecycle. A demonstration will be given.

CURATe Measures for Human-Integrated Systems: A Model Checking Approach

To support safe and effective human-system integration, a safety-critical system should be Complete, Understandable, Robust, Accurate, and Time efficient (CURATe) with respect to the user, interface, device, and environmental context. Using highly automated model checkers, researchers have shown that CURATe-related specifications can be verified early in the design process for a subset of system elements and interactions. This research introduces an extended model checking approach that aims to address all CURATe measures with respect to a broader range of human-integrated system elements: the interface, including documentation, configurable hardware, and control units; the user, including capabilities, actions, and knowledge; the device, including automation, actuators, and transducers; and the environment, including stimuli and constraints that could shape behavior. We describe a concept for what elements/interactions among them need to be modeled formally as well as a concept for applicable CURATe specifications. With respect to these concepts, we propose a formal model architecture and one temporal logic encoding for each CURATe specification.