Risk identification and safety assessment of human-computer interaction in integrated avionics based on STAMP

To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA)and cognitive reliability and error analysis method(CREAM)is proposed.STPACREAM can identify unsafe control actions and find the causal path during the interaction of avionics systems and pilot with the help of formal verification tools automatically.The common performance conditions(CPC)of avionics systems in the aviation environment is established and a quantitative analysis of human failure is carried out.Taking the head-up display(HUD)system interaction process as an example,a case analysis is carried out,the layered safety control structure and formal model of the HUD interaction process are established.For the interactive behavior“Pilots approaching with HUD”,four unsafe control actions and35 causal scenarios are identified and the impact of common performance conditions at different levels on the pilot decision model are analyzed.The results show that HUD's HCI level gradually improves as the scores of CPC increase,and the quality of crew member cooperation and time sufficiency of the task is the key to its HCI.Through case analysis,it is shown that STPACREAM can quantitatively assess the hazards in HCI and identify the key factors that impact safety.

The Analysis of Human Behaviour and Evacuation in a Fire Situation in a Building for Higher Education

The paper presents the analysis of a human evacuation from a higher education building located in Iassy,Romania,by means of engineering techniques to approach fire safety.Because in Romania(as in other European countries)fire safety design of buildings is prescriptive and not performance-based,a fire safety engineering approach arouse great interest in many countries such as the U.S.A.,Australia,New Zealand,England,Sweden,Finland,etc.This paper is based on the assumption of starting a fire in the space of a hall for festivities,located on the ground floor of the building,near two human evacuation routes;We consider two building evacuation scenarios:two exits and,respectively,just one exit(assuming that the second would be accidentally blocked).

Handling Uncertainty in Human Cognitive Reliability Method for Safety Assessment Based on DSET

Human Reliability Analysis(HRA)is an important part in safety assessment of a large complex system.Human Cognitive Reliability(HCR)model is a method of evaluating the probability that operators fail to complete during diagnostic decision making within a limited time,which is widely used in HRA.In the application of this method,cognitive patterns of humans are required to be considered and classified,and this process often relies on the evaluation opinions of experts which is highly subjective and uncertain.How to effectively express and process this uncertain and subjective information plays a critical role in improving the accuracy and applicability of HCR.In this paper,a new model was proposed to deal with the uncertain information which exists in the processes of cognitive pattern classification in HCR.First,an evaluation panel was constructed based on expert opinions and processing including setting corresponding anchor points and qualitative indicators of different cognitive patterns,and mapping them to fuzzy numbers and unit intervals.Second,based on the evaluation panel,different analysts judge the cognitive pattern types of actual specific events and provide the level of confidence he or she has in the judgments.Finally,the evaluation opinions of multiple analysts were expressed and fused based on the Dempster-Shafer Evidence Theory(DSET),and the fused results were applied to the HCR model to obtain the Human Error Probability(HEP).A case study was used to demonstrate the procedure and effectiveness of the proposed method.

Human Error Model and Definition of Human Reliability

Aim A model of human errors is given. His reliability of action is also determined. Safety countermeasures to prevent human errors are put forward. Methods\ Human system is regarded as a maintainable Markov system. On the basis of Markov method, the deduction and calculation in practice are made. Results\ Human errors are the chief factors leading to accidents, and may appear in different models. There are two kinds of states the normal and error state in a process of work. The process of state transfer human system is a Markov process. Human action reliability will be decreased with the continuation of time. Conclusion\ Human errors are described in the quantified form. It will have some significance in terms of theory in the study of the relationship between human action and accidents. Thus helping us in the preven tion of accident occurrence. The safety of a system can be improved in this way.

Promoting Clinician Well-Being and Patient Safety Using Human Factors Science: Reducing Unnecessary Occupational Stress

Our healthcare delivery system has accumulated complexity of payment, regulation systems, expectations and requirements. Often these are not designed to align with clinical thinking process flow of patient care. As a result, clinicians are utilizing enormous mental (cognitive) resource to comply with these complexities, over and above the baseline mental effort required to give good care to the patient. Recent studies suggest a significant number of physicians, advanced practice providers and nurses no longer want to stay in healthcare due to difficult work expectations and conditions that have become unreasonable. Technology has benefitted healthcare delivery, but also is a conduit of many expectations that have been grafted upon clinician workloads, exceeding the resources provided to accomplish them. Cognitive load is a measure of mental effort and is divided into Intrinsic, Germane and Extraneous Cognitive Load. Extraneous Cognitive Load (ECL) is what is not necessary and can be removed by better design. High cognitive load is associated with increased risk of both medical error and clinician burnout. Chronic high level occupational stress occurs from dealing with this job/resource imbalance and is showing serious personal health impact upon clinicians and the quality of the work they can provide for patients. Since organizational systems have become more complex, leadership methods, clinician wellbeing and patient safety efforts need to adjust to adapt and succeed. Safety efforts have tended to predominantly follow methods of a few decades ago with predominant focus upon how things go wrong (Safety I) but are now being encouraged to include more of the study of how things go right (Safety II). Human Factors/Ergonomics (HFE) science has been used in many industries to preserve worker wellbeing and improve system performance. Patient safety is a product of good system performance. HFE science helps inform mechanisms behind Safety I and II approach. HFE concepts augment existing burnout and safety interventions by providing a conceptual roadmap to follow that can inform how to improve the multiple human/technology, human/system, and human/work environment interfaces that comprise healthcare delivery. Healthcare leaders, by their influence over culture, resource allocation, and implementation of requirements and workflows are uniquely poised to be effective mitigators of the conditions leading to clinician burnout and latent medical error. Basic knowledge of HFE science is a strategic advantage to leaders and individuals tasked with achieving quality of care, controlling costs, and improving the experiences of receiving and providing care.

Statistical Analysis of Human Reliability of Armored Equipment

Human errors of seven types of armored equipment, which occur during the course of field test, are statistically analyzed. The human error-to-armored equipment failure ratio is obtained. The causes of human errors are analyzed. The distribution law of human errors is acquired. The ratio of human errors and human reliability index are also calculated.

An Evaluation of Human Error Probabilities for Critical Failures in Auxiliary Systems of Marine Diesel Engines

Human error,an important factor,may lead to serious results in various operational fields.The human factor plays a critical role in the risks and hazards of the maritime industry.A ship can achieve safe navigation when all operations in the engine room are conducted vigilantly.This paper presents a systematic evaluation of 20 failures in auxiliary systems of marine diesel engines that may be caused by human error.The Cognitive Reliability Error Analysis Method(CREAM)is used to determine the potentiality of human errors in the failures implied thanks to the answers of experts.Using this method,the probabilities of human error on failures were evaluated and the critical ones were emphasized.The measures to be taken for these results will make significant contributions not only to the seafarers but also to the ship owners.

Quantitative Human Reliability Analysis for Crew During Shipping Operation

A simplified bi-variable human error probability calculation method is developed by incorporating two common performance condition( CPC) factors, which are modified from factors employed in cognitive reliability and error analysis method(CREAM) to take into account the characteristics of shipping operations. After the influencing factors are identified, Markov method is used to calculate the values of human reliability. The proposed method does not rely on the involvement of experts in the field of human factor nor depend on historical accidents or human error statistics. It is applied to the case of the crew on board of an ocean going dry bulk carrier. The caculated results agree with the actual case, which verifies the validity of the model.

APPLICATION OF HUMAN COGNITIVE MODEL FOR TIME DEPENDENT OPERATOR BEHAVIOR IN CHINESE NPP

This paper discusses some issues on human reliability model of time dependent human behavior. Some results of the crew reliability experiment on Tsinghua training simulator in China are given, Meanwhile, a case of calculation for human error probability during anticipated transient without scram (ATWS) based on the data drew from the recent experiment is offered.

Engineering approach for human error probability quantification

A novel approach for engineering application to human error probability quantification is presented based on an overview of the existing human reliability analysis methods. The set of performance shaping factors is classified as two subsets of dominant factors and adjusting factors respectively. Firstly, the dominant factors are used to determine the probabilities of three behavior modes. The basic probability and its interval of human error for each behavior mode are given. Secondly, the basic probability and its interval are modified by the adjusting factors, and the total probability of human error is calculated by a total probability formula. Finally, a simple example is introduced, and the consistency and validity of the presented approach are illustrated.

Human Factor Based Leadership: Critical Leadership Tools to Reduce Burnout and Latent Error in a Time of Accelerating Change

The majority of errors in healthcare are from systems factors that create the latent conditions for error to occur. The majority of occupational stressors causing burnout are also the result of systemic factors. Advances in technology create new levels of stress and expectations on healthcare workers (HCW) with an endless infusion of requirements from multiple authoritative sources that are tracked and monitored. The quality of care and safety of patients is affected by the wellbeing of HCWs who now practice in an environment that has become more complex to navigate, often expending limited neural resource (brainpower) on classifying, organizing, constantly making decisions on how and when they can accomplish what is required(extraneous cognitive load) in addition to direct patient care. New information demonstrates profound biological impact on the brains of those who have burnout in areas that affect the quality and safety of the decisions they make-which affects risk to patients in healthcare. Healthcare administration curriculum currently does not include ways to address these stress-induced problems in healthcare delivery. The science of human factors and ergonomics (HFE) promotes system performance and worker wellbeing. Patient safety is one component of system performance. Since many requirements come without resource to accomplish them, it becomes incumbent upon health system leadership to organize the means for completion of these to minimize the needless loss of brain power diverted away from the delivery of patient care. Human Factor-Based Leadership (HFBL) is an interactive, problem solving seminar series designed for healthcare leaders. The purpose is to provide relevant human factor science to integrate into their leadership and management decisions to make HCWs occupational environment more manageable and sustainable-which makes safer conditions for clinician wellbeing and patient care. After learning the content, a cohort of healthcare leaders believed that adequately addressing HFE in healthcare delivery would significantly reduce clinician burnout and risk of latent errors from upstream leadership decisions. An overview of the content of the seminars is described. Leadership feedback on usability of these seminars is reported. Three HFBL seminars described are Human Factor Relevance in Leadership, Biopsychosocial Approach to Wellness and Burnout, Human Factor Based Leadership: Examples and Applications.

Bayesian estimator of human error probability based on human performance data

A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data and prior information about human performance together,a more accurate and specific HEP estimation can be achieved.For the time-unrelated task without rigorous time restriction,the HEP estimated by the common-used human reliability analysis（HRA） methods or expert judgments is collected as the source of prior information.And for the time-related task with rigorous time restriction,the human error is expressed as non-response making.Therefore,HEP is the time curve of non-response probability（NRP）.The prior information is collected from system safety and reliability specifications or by expert judgments.The（joint） posterior distribution of HEP or NRP-related parameter（s） is constructed after prior information has been collected.Based on the posterior distribution,the point or interval estimation of HEP/NRP is obtained.Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach.

Human factors in anaesthetic crisis

This paper discusses some of the key aspects of human factors in anaesthesia for the improvement of patient safety. Medical errors have emerged as a serious issue in healthcare delivery. There has been new interest in human factors as a means of reducing these errors. Human factors are important contributors to critical incidents and crises in anaesthesia. It has been shown that the prevalence of human factors in anaesthesia can be as high as 83%. Cognitive thinking process and biases involved are important in understanding human factors. Errors of cognition linked with human factors lead to anaesthetic errors and crisis. Multiple errors in the cognitive thinking process, known as "Cognitive dispositions to respond" have been identified leading to errors. These errors classified into latent or active can be easily identified in the clinical vignettes of serious medical errors. Application of the knowledge on human factors and use of cognitive de-biasing strategies can avoid human errors. These strategies could involve use of checklists, strategies to cope with stress and fatigue and the use of standard operating procedures. A safety culture and health care model designed to promote patient safety can compliment this further. Incorporation of these strategies strengthens the defence layers against the "Swiss Cheese" models, which exist in the health care industry.

Human behaviour detection dataset (HBDset) using computer vision for evacuation safety and emergency management

During emergency evacuation,it is crucial to accurately detect and classify different groups of evacuees based on their behaviours using computer vision.Traditional object detection models trained on standard image databases often fail to recognise individuals in specific groups such as the elderly,disabled individuals and pregnant women,who require additional assistance during emergencies.To address this limitation,this study proposes a novel image dataset called the Human Behaviour Detection Dataset(HBDset),specifically collected and anno-tated for public safety and emergency response purposes.This dataset contains eight types of human behaviour categories,i.e.the normal adult,child,holding a crutch,holding a baby,using a wheelchair,pregnant woman,lugging luggage and using a mobile phone.The dataset comprises more than 1,5o0 images collected from various public scenarios,with more than 2,9oo bounding box annotations.The images were carefully selected,cleaned and subsequently manually annotated using the Labellmg tool.To demonstrate the effectiveness of the dataset,classical object detection algorithms were trained and tested based on the HBDset,and the average detection accuracy exceeds 90%,highlighting the robustness and universality of the dataset.The developed open HBDset has the potential to enhance public safety,provide early disaster warnings and prioritise the needs of vulnerable individuals during emergency evacuation.

Human Reliability Analysis Method on Armored Vehicle System Considering Error Correction

Human reliability analysis(HRA) is an expansion of man-machine engineering. It is also a new multidisciplinary based on behavioral science, cognitive science, information processing, system analysis and probability statistics in order to analyze, predict, reduce and prevent human errors. Firstly, the quantitative analysis model of HRA is proposed based on Markov process theory by using human error probability(HEP) and error correction cycle(ECC) as parameters. And human reliability evaluation criterion is built. Then, the HRA process considering error correction is proposed based on cognitive reliability and error analysis method(CREAM). Finally, according to the characteristics of armored vehicle system, common performance condition(CPC) in CREAM is improved.A reliability impact index is characterized by the overall contexts of tasks. Human reliability evaluation criterion of armored vehicle system is formulated. And the result of HRA is obtained based on the method presented in this paper. In addition, the relative weights are estimated by combining scale of 10/10—18/2 and analytical hierarchy process(AHP), and the triangular fuzzy number considering confidence factor and optimism index is adopted in order to reduce the subjectivity. The analysis results show that the method presented in this paper is reasonable and feasible. Meantime, the method can provide guidance for human reliability analysis of other weapon systems.

Method of Estimating Human Error Probabilities in Construction for Structural Reliability Analysis Based on Analytic Hierarchy Process and Failure Likelihood Index Method

Human error(HE) is the most important factor influencing on structural safety because its effect often exceeds the random deviation.Large numbers of facts have shown that structural failures may be caused by the gross error due to HE.So it is essential to analyze HE in construction.The crucial work of human error analysis(HEA) is the estimation of human error probability(HEP) in construction.The method for estimating HEP,analytic hierarchy process and failure likelihood index method(AHP-FLIM),is introduced in this paper.The method also uses the process of expert judgment within the failure likelihood index method(FLIM).A numerical example shows the effectiveness of the methods proposed.

改进贝叶斯网络模型在起重作业人机交互差错风险分析中的应用

为量化分析起重作业人机交互差错风险,根据安全工效学原理及安全技术规范将起重作业人、机、环相关影响因素作为根节点,按照事故致因层次关联关系确定子节点,构建起重作业人机交互差错的3层级贝叶斯网络模型(Bayesian Network, BN);基于模糊集理论,采用认知可靠性与失误分析方法(Cognitive Reliability and Error Analysis Method, CREAM),厘定贝叶斯网络父节点失效概率以及中间节点条件概率;利用逆向推理仿真技术分析起重作业人机交互差错发生的因果链,探究起重伤害事故发生的人机交互差错风险。结果表明:起重作业人机交互差错最可能致因链为起重设备安全检查不到位→管理人员失误→人员操作失误→起重伤害事故发生;单因素失效条件下,起重作业人机交互差错风险概率呈线性增长趋势;在多因素失效条件下,一级节点因素失效概率愈大则人机交互差错效应愈显著,且呈现非线性增长态势。

智能煤矿下操作人员情境意识影响因素的多面分析

为了探究智能煤矿中导致操作人员情境意识失效的关键因素,构建智能煤矿操作人员情境意识影响因素理论模型。基于428名被试的问卷调查和数据分析,探讨注意力、记忆、环境特性和任务复杂度对情境意识的影响。研究结果表明:注意力资源和工作记忆对情境意识具有直接而显著的影响,而环境特性和任务复杂性则对情境意识有间接影响,总体而言,注意力资源是智能煤矿人因失误风险防范的关键。这些发现可为提高操作人员的情境意识、预防人因失误提供理论依据,有助于指导智能煤矿企业人员培训和系统优化设计。

基于CREAM方法的海上风机安装人因可靠性评估

采用认知可靠性和差错分析法(Cognitive Reliability and Error Analysis Method,CREAM)对固定式海上风机安装作业的人因可靠性进行评估,并引入结构熵权法和马尔可夫方法对传统CREAM进行改进,实现人因差错概率、平均人为差错时间等人因可靠性指标的定量计算。在充分结合现实条件的情况下,考虑海上风机安装的天气、海浪和操作水平等环境和人为因素的影响,针对固定式海上风机安装作业的要求和特点,结合作业人员可靠性评估结果,从操作素质、组织管理、环境改善等方面提出发展建议。