Advances in Human Error, Reliability, Resilience, and Performance

Mining is an important contributor to the social and economic fabric of our society. However, it continues to be regarded as one of the most dangerous industries. Compared to manufacturing, mining is more complex, which can pose additional challenges for mining and safety managers in terms of achieving sustainable safety outcomes. More advanced approaches are required. This paper first discusses the state of mining safety in Australia, followed by an examination of some of the complexities that characterizes the industry. It then introduces High-reliability organizations and Collective mindfulness as an advanced organizational safety management strategy that can be used to achieve sustainable safety improvement. A pragmatist research framework and two organizational theories follow this, which can be used to inform further research in these fields. The paper concludes with a research proposition which can be used to empirically investigate these concepts in mining organizations.

The objective of this work is the development of a management model for system reliability analysis influenced by technical factors and human factors (Socio Technical Reliability Analyzes - STRA). Such analysis is made from the understanding of technology, operational and organizational contexts and the determination of human reliability, equipment reliability, operational reliability and process known as integrated reliability or sociotechnical reliability. With this management tool, equipment and process failures as well as human failures will be reduced, and the result will be increased reliability and operational availability.

On 30 June 2013, nineteen men, the Prescott Fire Department (PFD), Granite Mountain Hot Shot Crew (GMHS), quasi-military Wildland Fire Crew, died on the Yarnell Hill Fire in Arizona. Little has been done to dispel the September 2013 Serious Accident Investigation Team’s (SAIT) Serious Accident Investigation Report (SAIR) no fault conclusions. This infamous event defies reason. Newly revealed Public Records and Freedom of Information Act (FOIA) Requests evidence indicate the YH Fire “story” is inaccurate. These newly discovered records suggest (1) was there a rogue firing operation; (2) disparate treatment regarding Public Records; and (3) Agency employee “guidance” and direction to not discuss the YH Fire contradict professed “lessons learned” objectives. Attempts by so-called “leaders” to deter WFs from discussing and truth-seeking of this tragedy abound. The “wildfire fatalities are unavoidable” argument is contentious. The authors maintain that wildfire fatalities can be reduced notwithstanding that many naysayers continue to fervently disagree.

Within high-reliability industries, traditional approaches to safety behaviour change using conventional pedagogical methods of teaching often fail at achieving persistent and lasting results on the front-lines. A drastic step change is needed to address outdated practices for a group of industries beset with ‘safety fatigue’. By leveraging evidence-based countermeasures and tools developed in the military, sports and cognitive psychology, and other high-performance fields, safety becomes embedded within a self-improvement approach rather than an edictal and prescriptive introduction of procedures. The results of this approach from a number of high-reliability and high-risk companies demonstrate the effectiveness over traditional more prescriptive approaches to front-line behaviour change. This paper clearly demonstrates that by making safety a by-product of high-performance, presenting countermeasures as individual tools within an individual’s arsenal, and resonating with the target audience; persistent behaviour change in high-reliability industries can be achieved.

Although much research has concentrated on the forecast of efficient team performance and the variables that might detract or promote team efficiency, little research reviewed has assessed the multitude of individual characteristics their impact on collaborative problem solving (CPS). Much of the research investigates only a single individual characteristic and its effect on group performance. This research proposes to explore three individual attributes (interpersonal dependency, individual working memory capacity, and preferred learning style) on performance effectiveness in CPS. A wide range of fields including healthcare and the military has explored CPS; however, the bulk of teamwork research to date has dealt with behavioral coordination on a single feature. This study will explore the association between team-member attributes and CPS skills. Noteworthy interactions might be observed to demonstrate that there are mixtures of traits more (or less) productive than anticipated, indicating further evidence of how group composition influences group performance.

By investigating human errors occur in rocket’s fuel-filling mission, several important performance shaping factors (PSFs) which have great influence on human error are revealed. It is also found that among all error modes, timing errors (including action too late and action too early) and omissions (including omitting entire step and omitting operation in step) occur most frequently. Timing errors and omissions are both considered as human errors that fail the mission. This paper selects time of day and stress as two PSFs to study the effects of PSFs on human error probability (HEP). This paper also explores whether there is a coupling between the two PSFs.

As revealed by the mishap causal factor statistics, human errors pose more threats to the safe operation of Unmanned Aerial System (UAS). Moreover, the number of human error induced maintenance accident has risen to a comparable level as the accidents due to flight crew error, but little prior research on the causality analysis can be found, especially consider the organizational context of human performance shaping factors. Based on the System Dynamics approach, this study proposed hierarchical risk archetypes that model the interactions of organizational, human and physical system factors leading to maintenance accident of large UASs. The archetypes help to clarify why technical reliability improvement measures, career training and accident investigation always fail to gain expected safety benefits. As organizational risk assessment tools, more detailed quantitative SD model can be developed based on those archetypes to evaluate potential safety policy and management decisions in the field of large UAS maintenance.

This paper introduces a method for the simulator data collection and analysis that we have developed to generate a time-reliability correlation (TRC) for the human reliability analysis (HRA) of an advanced control room with digitalized human system interfaces. We provide guidance on the definition of TRC and the timing points to be collected, as well as the processing of collected data. An application study was carried out using a set of simulator records collected from a reference plant to confirm the suitability of the proposed method and to generate a preliminary TRC for the HRA of the reference plant.

We examined performance for a university population and military population in the Simulated Multiple Asset Routing Testbed (SMART). SMART is a testbed designed to be similar to the types of tasks future unmanned vehicle operators will perform. Specifically, participants were required to optimize route selections for unmanned aerial vehicles. Their goal was to obtain a maximum number of points, given the likelihood of finding their targets. Participants showed superior performance when provided with detailed icons that contained information relevant to the route selections, compared to a condition where this information was provided in a table format instead. Although the detailed icons improved performance, we found that working memory capacity (WMC) and numeracy were predictive of accuracy in SMART. These results suggest that individual differences in WMC and the ability to understand and manipulate numbers may play an important role in tasks that require one to weight and optimize multiple outcomes. We discuss the implications of these findings for tool design and job selection and training.

The present study investigates the link between time taken by a team to perform a spatial orientation task and the evaluation of spatial shared situational awareness (SSA). Paired in teams, volunteers have to collaborate to send a vehicle to a specific location on a computer simulation as quickly as they can. The roles and information they have to reach that goal are different. Every 45 s participants are asked to mark on their map the location they believe the vehicle to be. Along with its real position, these marks are used to objectively evaluate spatial SSA. First results allow us to divide participants into three groups in accordance with Endsley’s distinction of Shared SA evaluation. Interestingly, fastest teams were not the ones with the most accurate and shared spatial representation of the situation. Potential use of such indicators in team training is outlined.

This paper proposes a risk analysis method for human-machine interaction system (HMIS). There are five correlated risk factors being analyzed in the HMIS: human conditions, human decision processes, human behaviors, machine and environment. With the considering of the system hazards in three types of risk scenario, we put forward an evaluation method on human-machine interaction risk for the HMIS, which provides a formalized table and contains the interaction interfaces risk evaluation procedure. In the method, we use a fuzzy method to quantify the human-machine interaction risk. Finally, a case study of the unmanned aerial vehicle (UAV) control system is conducted to illustrate the effectiveness of the method, and some advices for human-machine design are given.

This study aims at performing Operating Experience Review (OER) and Functional Requirement Analysis (FRA) for human-system interface design of Severe Accident Management Support System (SAMSS) through Human Factors Engineering (HFE) program of NUREG-0711. The OER reviews human and organizational issues in Fukushima nuclear power plant (NPP) accident that is a severe accident. It also reviews the operator support system for severe accident management to identify design requirements for the SAMSS. The FRA identifies safety functions and systems required to manage and mitigate severe accident in NPPs. Especially, the safety functions and systems are modeled with the Multi-level Flow Modeling. The result of this study will be used as inputs to the design of SAMSS.

This paper proposed a framework called the “Error-Cognition-Design”, which studies the association between error factors, visual cognition and design information. We can combine extended operator’s cognitive behavior model with corresponding analytical model of error recognition, and further recognize the cognitive error of the interfacial task. According to the process of operator’s cognitive behavior, operator’s task, task function as well as task steps and structure are unfolded, corresponding with the analytical opinion of human reliability, which includes task analysis, objection analysis, operation analysis, planning analysis, error analysis, psychological error mechanism analysis, performance shaping factor analysis as well as human error identification in systems tool analysis. Based on the results, we proposed an optimization design scheme for the monitoring task interface. According to the reaction chain of error factors and information features, the avionics interface display can be optimized via the information symbols design and the information block layout.

CS25.1302 requires that the design of aircraft cockpit human-machine interface (HMI) shall have error management capability, thus human error analysis is a crucial part in the cockpit human factor design process. Focusing on potential pilot errors and observed pilot errors during human factor evaluation tests during the civil aircraft cockpit HMI design process, this paper proposed a practical pilot error analysis method which considers CREAM method as well as the characteristics of flight. This method analyzed the type of error, effects and criticality of the error on operation and safety, root cause of the error and existing safety strategy and means of risk mitigation.

Conventional military training might not fully prepare Soldiers for some of the physical and psychological skills vital to reducing stress as well as avoidable causalities in combat situations. The present study operationalized a complex Integrative Training Approach (ITA) [1, 2] to address cognitive-based gaps regarding First Responder actions and decisions. This approach included three live, scenario-based exercises calibrated with scenarios meant to elicit increasing psychophysiological pressure via combat stressors embedded within key events. The associated mental and physical arousal was recorded using subjective and objective measures during each scenario. Participants in the experimental condition were provided psychological training and practical application before proceeding to the live environment. This paper serves as the continuation of the 2016 Training and Readiness Resilience study, published in 2018 [2]. With the incorporation of additional data, we found continued reliability with previously reported results; indicating that training was a mitigator of measured stress, as compared to Control squads, who received no training.

Physical Readiness (PR) is essential to the U.S. Army’s ground fighting lethality and essential for combat medics trained to evacuate the sick and wounded from the battlefield. However, physical readiness, as measured by the Army Physical Fitness Test (APFT), may involve more than physical capabilities. The purpose of this study was to examine the relationships between APFT scores and self-reports of physical fitness, self-esteem, self-concept, and positive and negative self-talk among soldiers attending combat medic training (n = 473). Pearson Correlations with a p-value of .05, showed low to moderate associations between APFT scores and self-reports in each category of consideration (p < .05). These results suggest that physical readiness, as determined by APFT scores, is about more than physical performance, and previous research demonstrating the highest physical readiness is achieved among those with high physical, cognitive, and emotional performance. Findings also suggest the need for mental fitness training offered alongside physical training to build strong, resilient soldiers.

The purpose of this paper is to compare three mindfulness training delivery methods: 8 weekly classes delivered in-person (8-IP), 5 days of classes delivered in-person, 8 weekly classes delivered in a virtual world, and an 8 week wait-list control group. U.S. military service member and veteran volunteers completed pre- and post-assessments of self-reported anxiety, stress, positive and negative affect, and the Post Traumatic Stress Disorder (PTSD) Checklist – Military Version. Within group pre- to post-reductions in all measures occurred in the 8-IP group, with reductions in PTSD symptoms, anxiety, and negative affect reaching significance (p < .05). One group difference was seen - negative affect was reduced more in the 8-IP than in the other groups (p < .05). The results demonstrate that the delivery method has an impact on outcome. Future research should continue to address the effectiveness and feasibility of varied mindfulness programs.

Endsley (1995) systematically put forward the theory of Situation Awareness (SA). The theory emphasizes people’s perception and understanding of current operating environment information, and prediction of future state under certain time and space conditions. Endsley and Jones (2012) further proposed a SA-Oriented Design system. With the deepening of SA research, it has become the frontier of engineering psychology research. At present, Nuclear Power Plants (NPP) are highly computerized, the complexity of its main control room has increased, man-machine interaction is frequent, tasks are complex and changeable, time pressure is high, and cognitive load is heavy, so the workload of operators is greatly increased. In this complex technical system, the accuracy of Team Situation Awareness (TSA) of NPP is an important factor for high quality decision-making and efficient operation. If the problem of real-time and accurate SA measurement can be solved, it will be helpful to the design of Real-Time Adaptive man-machine interaction. Firstly, this paper analyses the elements and types of Team Situation Awareness of nuclear power plant, and develops a team SA measurement scale. Then, in different accident scenarios, the level of team SA of different types was measured by the simulation experiment, and the influencing factors were analyzed. These provide theoretical and experimental support for improving TSA of NPP.

Operator’s situation awareness (SA) issues are more prominent in digital nuclear power plants (NPPs). In order to identify the SA levels of operators and levels of team shared situation awareness (SSA), a SA measure method was developed based on Situation Awareness Global Assessment Technique (SAGAT). Furthermore, it was used to measure the SA levels of operators by simulation experiments and a method was established to determine the team SSA level. The experimental results showed that the individual SA level was related to the SSA level. The higher the individual SA level is, the higher the SSA level is. Furthermore, for different experimental scenarios, the SA level of operators and team SSA level is different, which means that the more obvious the symptoms of the risky scenarios are, the relatively higher the SA and SSA level are.

The reliability of human being has been paid increasing attention by engineers in recent years, which significantly increases the success of aerospace mission. Many Human Reliability Analysis methods, which are referred to HRA have been proposed to quantify Human Error Probability (namely HEP) in the past few decades. This paper takes crew human reliability into account and present its concept. Then, an assessment method for crew human reliability is proposed basing on Cognitive Reliability and Error Analysis Method, referred to as CREAM, and this assessment method mainly focuses on how to make accurate quantification model on crew errors. Finally, an example about the crew of fueling process in space launch is evaluated to show the usage of the model.

Organizational resilience defines the capability of how a nuclear power plant organization manages disturbances, both outside and inside a nuclear power plant. The paper specifies the organizational resilience on the basis of analyzing the disturbances of a nuclear power plant. These disturbances include internal incidents, accidents and transients as well as those caused by external environment. The paper tries to reveal the mechanism of how organizational resilience functions on the safety of a nuclear power plant. The paper assumes the taking place of an accident (Small Loss of Coolant) and analyzes how the plant organization responds to the accident to illustrate the mechanism.

This paper describes a human subject study that compared the limits at which humans could communicate information through pursuit tracking gestures versus pointing (i.e. tapping) gestures. These limits were measured by estimating the channel capacity of the human motor-control system for pursuit tracking versus pointing along a single axis. A human-computer interface was built for this purpose, consisting of a touch strip sensor co-located with a visual display. Bandwidth-limited Gaussian noise signals were used to create targets for subjects to follow, enabling estimation of the channel capacity at bandwidth limits ranging from 0.12 Hz to 12 Hz. Results indicate that for lower frequencies of movement (from 0.12 Hz to 1 Hz or 1.5 Hz), pointing gestures with such a sensor may tend to convey more information, whereas at higher frequencies (from 2.3 Hz or 2.9 Hz to as high as 12 Hz), pursuit tracking gestures will afford higher channel capacities. In this work, the direct comparison between pursuit tracking and pointing was made possible through application of the Nyquist sampling theorem. This study forms a methodological basis for comparing a wide range of continuous sensors and human capacities for controlling them. In this manner, the authors are aiming to eventually create knowledge useful for theorizing about and creating new kinds of computer-based musical instruments using diverse, ergonomic arrangements of continuous sensors.

An integrated methodology, that combines Hierarchical Task Analysis (HTA), Cognitive Task Analysis (CTA) and a modified Human Error Assessment and Reduction Technique (HEART), is proposed to identify safety-relevant human actions in innovative and advanced facilities. It is suggested to use in HEART the concept of linguistic expressions for proportion assessment factors. To prove its applicability, a case study is presented. The validation work has related to safety analyses of accidental events that can involve radiological over-exposure of patients during proton therapy treatments carried out by CATANA (Centro di AdroTerapia Applicazioni Nucleari Avanzate) centre, Italy. CATANA is the first Italian clinical facility that since 2002 used proton beams for ocular melanoma treatments. The results demonstrate the validity of the proposed integrated methodology as well as the versatility of HEART linguistic approach.

Latent Human Error information is gathered in companies, but there is a problem that it cannot be used well. The problem behind it is lack of knowledge on trouble analysis and insufficient analysis on text data. Therefore, in this research, we propose an information analysis system on latent human error. In the analysis system, the following three important elements are included. The first point is knowledge of Human Factors which is useful for trouble analysis. The second point is natural language processing technology which processes text information on trouble. The third point is statistics and DeepLearning technology using processed text information. Based on these factors, we aim to build an analysis support system that can be used by people who are not familiar with trouble analysis at the company site.

Reports on human error incidents contain crucial information to understand why and how incidents happened. There are huge numbers of documents that report industrial accidents or incidents. Instead of reading by humans, we can use document classification technique to find valuable knowledge hidden in the incident reports. Using the technique of document classification, we can detect group of frequent incident. First, the computer observes a set of words (so-called bag-of-word) which appear in each report. Second, the computer calculates similarities among reports. The report similarity is evaluated as agreement ratio of frequency of term appearances. Third, the computer builds the tree of report similarity: this tree holds group of similar reports on a branch. We find the typical patterns of incidents as branches of the tree. Fourth, the computer now calculates similarities of words, which are evaluated as ratio of word co-occurrence.

This paper considers human reliability analysis (HRA) for long-duration space missions. HRA has previously been used in the space program to support ground-based operations, Space Shuttle and International Space Station missions. New missions, such as a prospective mission to Mars, present new contexts for human spaceflight, including longer distances and durations, and different gravity levels. For HRA to be used to inform and prevent hazards, new research and data gathering are needed to understand the psychological and physiological aspects of astronautics. This paper outlines several areas of research that would support HRA for long-duration spaceflight. HRA methods must be adapted for space, which requires new data to inform and validate human error categorization and quantification.

The practice of resilience within many industries, especially aviation, oil, and nuclear power, focuses on practice at the individual, system, and organizational level. At the individual and system levels, near-miss events, mishaps, and incidents are investigated to determine causal factors to proactively rectify the problems. At the organizational level, resilient behavior begins with a strategic model that encompasses management commitment to safety. The field of resilience engineering has made great strides in understanding resilience at each of these levels. However, work in this field sometimes fails to consider additional perspectives provided by other fields that may fill gaps in our knowledge. The purpose of this paper is to consider how theories from management science may augment ideas in resilience engineering to allow for a more complete understanding of resilience as a multi-level phenomenon.

A Human-in-the-Loop (HITL) simulation was conducted to explore the impacts of various surface metering goals on operations and Ramp Controllers at Charlotte Douglas International Airport (CLT). Three conditions were compared: (1) Baseline, with no surface metering, (2) instructions to meet advisory times at the gate only, and (3) instructions to meet advisory times at the gate as well as the times at the scheduled taxiway spot, where aircraft are delivered to Air Traffic Control (ATC). Results showed increased compliance for taxiway spot times when compliance was first met for gate advisories. Instructing Ramp Controllers to meet advisory times at the gate improves spot time compliance and therefore surface scheduling predictability at CLT. Results also demonstrated there was increased compliance overall with gate and spot times in the second condition. This was likely due to higher Ramp Controller workload in the third condition.

This paper evaluates the safety risk of space launch site from the perspective of human reliability. Firstly, the risk causes are analyzed, and it is found that the main reason affecting the safety risk of space launch site is human error. Then, a modified CREAM is proposed to analyze the human reliability of risk events in space launch site. The method uses the fuzzy function to convert discrete CPCs and control modes into continuous, and apply Bayesian reasoning to obtain more accurate HEP. Finally, on the basis of HEP data, the Bayesian network of space launch site risk is constructed, and the risk probability of the overall system is evaluated and sensitivity analysis is carried out.