Assessment of Human Factor Performance Using Bayesian Inference and Inherent Safety

2013 ◽  
Vol 845 ◽  
pp. 658-662
Author(s):  
Nor Diana A. Wahab ◽  
Risza Rusli ◽  
Azmi Mohd Shariff ◽  
Azizul Buang ◽  
N. A. Wahab
Keyword(s):  
Bayesian Inference ◽  
Human Factors ◽  
Failure Probability ◽  
Human Error ◽  
Human Performance ◽  
Human Factor ◽  
Preventive Measure ◽  
Inherent Safety ◽  
Predictive Tool ◽  
Ability To Act

Simply attributing incidents to human error is not adequate; human factors aspects should be investigated such that lessons are learnt and the true root causes are established in order to prevent recurrence. Whilst many petroleum and allied industry businesses have investigated and analyzed incidents – whether with major hazards or occupational injuries potential – human factors aspects are rarely addressed sufficiently. Therefore, this paper presents a hybrid methodology that combines a conventional Swiss Cheese model with Bayesian inference to predict the failure probability of human factors. An inherent safety concept associated with human factor is proposed and utilized as preventive measures to overcome the identified root causes. This approach is then applied to offshore safety assessment study. As a result, the failure probability of human factor can be monitored with time and the best preventive measure can be prioritized once human performance is degraded. It is proven that the approach has the ability to act as predictive tool that provides early warnings toward human deficiency. A preventive measure can then be taken to enhance the overall human performance and ultimately to reduce the likelihood of major incidents.

Human Factor Risk Assessment During Emergency Condition in Harsh Environment

2013 ◽  
Author(s):  
Mashrura Musharraf ◽  
Faisal Khan ◽  
Brian Veitch ◽  
Scott MacKinnon ◽  
Syed Imtiaz
Keyword(s):  
Risk Assessment ◽  
Human Factors ◽  
Human Error ◽  
Human Performance ◽  
Human Factor ◽  
Expert Judgment ◽  
Harsh Environment ◽  
Unrealistic Assumption ◽  
Error Probabilities ◽  
Human Error Probability

This paper presents a quantitative approach to human factors risk analysis during emergency conditions on an offshore petroleum facility located in a harsh environment. Due to the lack of human factors data for emergency conditions, most of the available human factors risk assessment methodologies are based on expert judgment techniques. Expert judgment is a valuable technique, however, it suffers from vagueness, subjectivity and incompleteness due to a lack of supporting empirical evidence. These weaknesses are often not accounted for in conventional human factors risk assessment. The available approaches also suffer from the unrealistic assumption of independence of the human performance shaping (HPS) factors and actions. The focus of this paper is to address the issue of handling uncertainty associated with expert judgments and to account for the dependency among the HPS factors and actions. These outcomes are achieved by integrating Bayesian Networks with Fuzzy and Evidence theories to estimate human error probabilities during different phases of an emergency. To test the applicability of the approach, results are compared with an analytical approach. The study demonstrates that the proposed approach is effective in assessing human error probability, which in turn improves reliability and auditability of human factors risk assessment.

HUMAN FACTOR ANALYSIS OF CONTAINER VESSEL’S GROUNDING ACCIDENTS

2021 ◽  
Vol 159 (A1) ◽  
Author(s):  
U Yildirim ◽  
O Ugurlu ◽  
E Basar ◽  
E Yuksekyildiz
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Human Error ◽  
Human Performance ◽  
Human Factor ◽  
Study Data ◽  
Team Management ◽  
Contribution Rate ◽  
Physical Problems ◽  
Mental Problems

Investigation on maritime accidents is a very important tool in identifying human factor-related problems. This study examines the causes of accidents, in particular the reasons for the grounding of container ships. These are analysed and evaluation according to the contribution rate using the Monte Carlo simulation. The OpenFTA program is used to run the simulation. The study data are obtained from 46 accident reports from 1993 to 2011. The data were prepared by the International Maritime Organization (IMO) Global Integrated Shipping Information System (GISIS). The GISIS is one of the organizations that investigate reported accidents in an international framework and in national shipping companies. The Monte Carlo simulation determined a total of 23.96% human error mental problems, 26.04% physical problems, 38.58% voyage management errors, and 11.42% team management error causes. Consequently, 50% of the human error is attributable to human performance disorders, while 50% team failure has been found.

Based on Human Behavior Process of Human Error Defensive Management Research for NPP

2017 ◽  
Author(s):  
Shen Yang ◽  
Geng Bo ◽  
Li Dan
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Control Chart ◽  
Human Behavior ◽  
Nuclear Power ◽  
Human Error ◽  
Human Performance ◽  
Human Factor ◽  
Error Management ◽  
Root Cause

According to the research of nuclear power plant human error management, it is found that the traditional human error management are mainly based on the result of human behavior, the event as the point cut of management, there are some drawbacks. In this paper, based on the concept of the human performance management, establish the defensive human error management model, the innovation point is human behavior as the point cut, to reduce the human errors and accomplish a nip in the bud. Based on the model, on the one hand, combined with observation and coach card, to strengthen the human behavior standards expected while acquiring structured behavior data from the nuclear power plant production process; on the other hand, combined with root cause analysis method, obtained structured behavior data from the human factor event, thus forming a human behavior database that show the human performance state picture. According to the data of human behavior, by taking quantitative trending analysis method, the P control chart of observation item and the C control chart of human factor event is set up by Shewhart control chart, to achieve real-time monitoring of the process and result of behavior. At the same time, development Key Performance Indicators timely detection of the worsening trend of human behavior and organizational management. For the human behavior deviation and management issues, carry out the root cause analysis, to take appropriate corrective action or management improvement measures, so as to realize the defense of human error, reduce human factor event probability and improve the performance level of nuclear power plant.

scholarly journals Влияние человеческого фактора при создании авиационных двигателей

2021 ◽  
pp. 5-10
Author(s):  
Виктория Викторовна Кокотина ◽  
Лариса Анатольевна Лесная ◽  
Виталий Григорьевич Харченко
Keyword(s):  
Human Error ◽  
Human Performance ◽  
Human Factor ◽  
Causative Factor ◽  
Civil Aviation ◽  
Modern World ◽  
Destructive Testing ◽  
Effective Prevention ◽  
A Chain

Ensuring the safety of the civil aviation system is the main goal of the International Civil Aviation Organization (ICAO) activities and the "human factor" was define as a priority in the field of flight safety. Given the variety of factors potentially affecting human performance, it is not surprising, that human error has been recognized as a major causative factor in virtually all air crashes and accidents since the inception of aviation. The reliability and safety of flights are influenced by: the quality of preparation of aviation equipment for flight, the quality of manufacture, assembly, acceptance, and pre-flight tests, the quality of design of aircraft and engines. The quality of workmanship is confirmed by the execution of control at each stage of manufacture. In any activity, the "human factor" is manifested by mistakes, oversights, and omissions, or miscalculations that a person makes when doing his job under certain conditions. The theory of the occurrence and prevention of errors associated with human physiology and the environment were described by H. Heinrich's "domino theory". Human errors form sequences in which the first error causes a chain of subsequent ones, keeping one of the dominoes standing behind each other, it is possible to prevent the consequences of an accident in the form of material damage or an accident. Human physiological features such as vision can be one of the dominoes and lead to erroneous actions. In the modern world, non-destructive testing methods are relevant and the role of a defectoscopistꞌs in determining the nature of a defect is quite large. Regular monitoring of vision (prophylactic examination) allows you to identify potential vision problems with a specialist, which can lead to erroneous actions. Human factors research is fundamental to understanding the context in which normal, healthy, skilled, well-equipped and reasonably motivated personnel make mistakes, some of which are fatal and, if the causes of human error are correctly understood, it will be possible to develop more effective prevention strategies errors, their control, and safe elimination.

Human Factor Modelling in the Pipeline Industry

2012 ◽  
Author(s):  
Susan Urra ◽  
Jessica Green
Keyword(s):  
Risk Assessment ◽  
Human Factors ◽  
Human Error ◽  
Human Factor ◽  
Assessment Model ◽  
Pipeline System ◽  
Risk Assessment Model ◽  
Control Room ◽  
Pipeline Failure ◽  
Error Potential

Most pipeline leaks and ruptures can be attributed to some degree to human factors. Therefore, identifying, measuring and improving areas of potential human factor issues can greatly decrease the risk of pipeline failure. ‘Human factors’ refers to the study of various aspects of human characteristics and job experience, job and task design, tools and equipment design, and work environment which can affect pipeline operations and overall system performance. Enbridge Pipelines has developed a risk assessment model that assesses the risk of human factors along the company’s nationwide liquid pipeline system. The Human Factors Risk Assessment Model generates a risk score for each aspect of the pipeline as well as an overall risk score which highlights the business areas of highest concern. The implementation of the model included the execution of a pilot study to calibrate the model. To perform the pilot, data was collected from the control center, field and office locations through different methodologies such as survey, interview and databases available. The results from the control room operation surveys indicate that the main areas of human error potential in the control room can be mitigated by decreasing the number of manual calculations the operators have to complete and ensuring operators aren’t taking on extra work that should be completed by other areas. These workload improvements would decrease the chance of an operator having to complete two or more control operations at the same time. Lastly, controlling the amount of phone activities that interfere with monitoring and control operations also gives an opportunity to reduce the potential for human error in the control room. Improvements that can be made in the office to reduce human error potential include the development of a human factors standard and improving the critical procedure observation and management of change systems. Measuring, acknowledging and mitigating human factor risks at Enbridge will yield a decrease in the risk of pipeline failure across the entire liquid pipeline system.

Human Error in Health Care Delivery: Cases, Causes and Correction

1993 ◽  
Vol 37 (11) ◽  
pp. 846-848 ◽  
Author(s):  
Harold P. Van Cott
Keyword(s):  
Health Care ◽  
Human Factors ◽  
Health Care Delivery ◽  
Human Error ◽  
Human Performance ◽  
Care Delivery ◽  
Human Errors ◽  
Improve Reliability ◽  
Intensive System

Health care delivery is viewed as a complex, people-intensive system whose reliability depends on human performance. Examples of the human errors that occur in health care are described, and human factors interventions and remedies that might be taken to improve reliability and safety are suggested.

The Systematic Consideration of Human Factors in Vessel Collision Investigations

2012 ◽  
Vol 46 (6) ◽  
pp. 142-159 ◽  
Author(s):  
Bryan R. Emond
Keyword(s):  
Human Factors ◽  
Human Error ◽  
Human Factor ◽  
Causal Chain ◽  
Historical Events ◽  
Vast Number ◽  
Available Information

AbstractHistorically, human factors have caused or contributed to the cause of nearly every vessel collision. However, given the vast number and type of human factors that can possibly be involved, the typical marine investigator risks either considering these factors only superficially or becoming bogged down in an academic exercise. Beyond just saying the collision was caused by “human error,” the marine investigator should understand the role of human factors in the causal chain of events. Some human factor issues can be difficult to parse from the available information. This is particularly the case for historical events but is also true even where witnesses are available. Nonetheless, there are a number of key areas where hard facts can reveal human factor issues that directly caused or contributed to the collision or somehow exacerbate the results. This paper divides that consideration into three parts, (1) human factors that affect the risk of the collision occurring, (2) human factors that affect the response once risk of collision is perceived, and (3) human factors that affect witness perception and recollection after the accident. The construct described in this paper can be used by the investigator to ensure a systematic consideration of key human factors relevant to a collision.

Human factors in maintenance: a review

2016 ◽  
Vol 22 (3) ◽  
pp. 218-237 ◽  
Author(s):  
Mohammad Sheikhalishahi ◽  
Liliane Pintelon ◽  
Ali Azadeh
Keyword(s):  
Decision Making ◽  
Human Factors ◽  
Human Error ◽  
Human Performance ◽  
Decision Makers ◽  
Content Type ◽  
Swiss Cheese Model ◽  
Maintenance Decision ◽  
Cheese Model ◽  
Review Current

Purpose – The purpose of this paper is to review current literature analyzing human factors in maintenance, and areas in need of further research are suggested. Design/methodology/approach – The review applies a novel framework for systematically categorizing human factors in maintenance into three major categories: human error/reliability calculation, workplace design/macro-ergonomics and human resource management. The framework further incorporates two well-known human factor frameworks, i.e., the Swiss Cheese model and the ergonomic domains framework. Findings – Human factors in maintenance is a pressing problem. The framework yields important insights regarding the influence of human factors in maintenance decision making. By incorporating various approaches, a robust framework for analyzing human factors in maintenance is derived. Originality/value – The framework assists decision makers and maintenance practitioners to evaluate the influence of human factors from different perspectives, e.g. human error, macro-ergonomics, work planning and human performance. Moreover, the review addresses an important subject in maintenance decision making more so in view of few human error reviews in maintenance literature.

Human Factor Analysis of Container Vessel's Grounding Accidents

2017 ◽  
Vol Vol 159 (A1) ◽  
Author(s):  
U Yildirim ◽  
O Ugurlu ◽  
E Basar ◽  
E Yuksekyildiz
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Human Error ◽  
Human Performance ◽  
Human Factor ◽  
Study Data ◽  
Team Management ◽  
Contribution Rate ◽  
Physical Problems ◽  
Mental Problems

Investigation on maritime accidents is a very important tool in identifying human factor-related problems. This study examines the causes of accidents, in particular the reasons for the grounding of container ships. These are analysed and evaluation according to the contribution rate using the Monte Carlo simulation. The OpenFTA program is used to run the simulation. The study data are obtained from 46 accident reports from 1993 to 2011. The data were prepared by the International Maritime Organization (IMO) Global Integrated Shipping Information System (GISIS). The GISIS is one of the organizations that investigate reported accidents in an international framework and in national shipping companies. The Monte Carlo simulation determined a total of 23.96% human error mental problems, 26.04% physical problems, 38.58% voyage management errors, and 11.42% team management error causes. Consequently, 50% of the human error is attributable to human performance disorders, while 50% team failure has been found.

Evaluation of human factor engineering influence in nuclear safety using probabilistic safety assessment techniques

Kerntechnik ◽  
2021 ◽  
Vol 86 (6) ◽  
pp. 470-477
Author(s):  
M. Farcasiu ◽  
C. Constantinescu
Keyword(s):  
Reliability Analysis ◽  
Error Rate ◽  
Error Detection ◽  
Human Error ◽  
Human Performance ◽  
Human Factor ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Human Factor Engineering ◽  
Rate Prediction

Abstract This paper provides the empirical basis to support predictions of the Human Factor Engineering (HFE) influences in Human Reliability Analysis (HRA). A few methods were analyzed to identify HFE concepts in approaches of Performance Shaping Factors (PSFs): Technique for Human Error Rate Prediction (THERP), Human Cognitive Reliability (HCR) and Cognitive Reliability and Error Analysis Method (CREAM), Success Likelihood Index Method (SLIM) Plant Analysis Risk – Human Reliability Analysis (SPAR-H), A Technique for Human Error Rate Prediction (ATHEANA) and Man-Machine-Organization System Analysis (MMOSA). Also, in order to identify other necessary PSFs in HFE, an additional investigation process of human performance (HPIP) in event occurrences was used. Thus, the human error probability could be reduced and its evaluating can give out the information for error detection and recovery. The HFE analysis model developed using BHEP values (maximum and pessimistic) is based on the simplifying assumption that all specific circumstances of HFE characteristics are equal in importance and have the same value of influence on human performance. This model is incorporated into the PSA through the HRA methodology. Finally, a clarification of the relationships between task analysis and the HFE is performed, ie between potential human errors and design requirements.

Sign in / Sign up

Export Citation Format

Share Document