원자력 발전소 주제어실 인터페이스 설계를 위한 인적오류 분석 기법의 보완

Nationally and internationally reported statistics on marine accidents show that 80% or more of all marine accidents are caused fully or in part by human error. According to the statistics of marine accident causes from Korean Maritime Safety Tribunal(KMST), operating errors are implicated in 78.7% of all marine accidents that occurred from 2002 to 2006. In the case of the collision accidents, about 95% of all collision accidents are caused by operating errors, and those human error related collision accidents are mostly caused by failure of maintaining proper lookout and breach of the regulations for preventing collision. One way of reducing the probability of occurrence of the human error related marine accidents effectively is by investigating and understanding the role of the human elements in accident causation. In this paper, causal factors/root causes classification systems for marine accident investigation were reviewed and some typical human error analysis methods used in shipping industry were described in detail. This paper also proposed a human error analysis method that contains a cognitive process model, a human error analysis technique(Maritime HFACS) and a marine accident causal chains, and then its application to the actual marine accident was provided as a case study in order to demonstrate the framework of the method.

This paper aims at performing a human reliability analysis using THERP (Technique for Human Error Prediction) and ATHEANA (Technique for Human Error Analysis) to develop a qualitative and quantitative analysis of the latent operator error in leaving EFW (emergency feed-water) valves closed in the TMI-2 accident. The accident analysis has revealed a series of unsafe actions that resulted in permanent loss of the unit. The integration between THERP and ATHEANA is developed in a way such as to allow a better understanding of the influence of operational context on human errors. This integration provides also, as a result, an intermediate method with the following features: (1) it allows the analysis of the action arising from the plant operational context upon the operator (as in ATHEANA), (2) it determines, as a consequence from the prior analysis, the aspects that most influence the context, and (3) it allows the change of these aspects into factors that adjust human error probabilities (as in THERP). This integration provides a more realistic and comprehensive modeling of accident sequences by considering preaccidental and postaccidental contexts, which, in turn, can contribute to more realistic PSA (Probabilistic Safety Assessment) evaluations and decision making.

Based on the present study of safety management in the aerodrome tower area and the theory of risk management, the characteristics of real time dynamic air traffic control in the airport tower area are analyzed. The dangerous incidents leading to accidents that happened are also classified. A mathematical model and system target are established, which would be used to estimate the risk of flight accidents caused by the normal operation and emergent response. Combined with the characteristics of dynamic air traffic control in the aerodrome tower scope, a technique for human error analysis (ATHEANA) is brought forward to realize the safety risk, including the definition and classification of unsafe action. Reliability theory is used to reckon the deterministic probability. Clustering analysis, classifying status and fuzzy similar matrix are adopted to calculate the loss of an aviation crash during the whole operational segment and procedure. The rules to estimate risk are set up. The systematic estimation method and measure to control risk are brought forward, which is helpful to improve the response ability to an emergency and promote and ensure the safety in the airport tower area. Simultaneously, combined with the example, the methods and target system would be test and verified.

This paper describes factors that cause the information complexity and how to measure the information complexity, and proposes solutions to design a human-machine interface to reduce the complexity of system information in nuclear power plants. The factors include nuclear power control system itself, an improper automation design, new technologies of fully digital instrumentation, control, and human-machine interface that has created tremendous functionality and the price of increased system complexity, and the ill-designed humancomputer user interface. The NASA-TLX and Task COMplexity (TACOM) were adopted to measure the information complexity of screen design and emergency procedure responses, respectively. An overview of the instrumentation and control system of the EPR (Evolutionary Power Reactor), an advanced pressurized-water reactor (PWR), is presented. Its information complexity is discussed and solutions are proposed according to the general principles of humanmachine interface design. We focus on two principles that direct the interface design for the EPR project. The first is to "provide information in a satisfactory manner" to the human operator. The second is to "provide adequate information" to the human operator. This paper is the preliminary report of part of the large multi-year project addressing information complexity problems and interface design in constructions of new nuclear power plants.

The improvement of Human-Machine Interface (HMI) design for control rooms on nuclear power plants (NPP) has been accomplished world wide, especially after the TMI-2 accident. The design process and guidelines are standardized in IEC60964 and supplemental standards as international standard. However, technological update is required due to the increased use of computerized control and monitoring equipment and systems in control rooms on NPP in recent years. Standards are becoming more important for computerized control rooms because there is more freedom to design than conventional hardware based system. For computerized control rooms, standards for hardware and software of HMI systems should be also considered. Standards and guidelines for computerized control rooms on NPP have been developed recently in each body such as IEC, ISO, and IEEE etc. Therefore, reviewing these standards and guidelines related to control rooms design of NPP can be useful not only for revision of the international standards such as IEC60964, but also for users of the standards and guidelines. In this paper, we reviewed the international standards related to the design for control rooms, in the two aspects of HMI design and hardware and software design, considering the undergoing revision work and their application.

As a high-tech industry, civil aviation industry should focus on technology, but accident reports show that at least 3/4 of the accidents are caused by human error. Therefore, in ATM system, human error is a potential weak link. We must take measures to minimize human error and its impact, and optimize the quality of human operation for error detection and recovery. The ultimate goal of the research on human errors in air traffic control is to take protective measures and means against human unsafe behaviors, so the identification and analysis of human errors in air traffic control is very important.KeywordsAir traffic controlHuman errorKnowledge representation frameworkOntologyRule reasoning

Most of the current aviation accidents are caused by human errors. Analyzing the types of human errors, causes, etc. is the important basis for finding out the defects in the system and making the prevention measures. The prior classification generally classifies the human errors or analyzes the causes from the engineering or human ability and status, and has big defect and difficulty for the active identification of the errors in human’s cognition process stage. Based on the HFACS error analysis model and CREAM reliability analysis method and combining with a great amount of flight accident data of the international modern fighter planes, the paper analyzes the human error causes in the flight accidents of the fighter planes and proposes the relevant measures for reducing human errors according to the analysis results. The method can be used for directing the monitoring and analysis of the human error events in the daily flight of the air force and improving the safety level of the flight stage.

Main control room (MCR) man-machine interface (MMI) design of advanced nuclear power plants (NPPs) such as APR (advanced power reactor)-1400 can be validated through performance-based tests to determine whether it acceptably supports safe operation of the plant. In this paper, plant performance, personnel task performance, situation awareness, workload, teamwork, and anthropometric/physiological factor are considered for the human performance evaluation. For the development of human performance measures, attention is paid to considerations and constraints such as the changed environment in an advanced MCR, needs for a practical and economic evaluation, and suitability of evaluation criteria. Measures generally used in various industries and empirically proven to be useful are adopted as the main measures with some modifications. In addition, complementary measures are developed to overcome some of the limitations associated with the main measures. The development of the measures is addressed based on theoretical and empirical background. Finally we discuss the way in which the measures can be effectively integrated. The HUPESS (HUman Performance Evaluation Support System) which is in development is also briefly introduced.

In order to deal with the increased traffic levels, the Air Traffic Management (ATM) system must take advantages of new technologies and procedures which will aid the Air Traffic Control Operators (ATCOs) in their complex job. New allocation of spacing tasks between controller and flight crew is envisaged as one possible option to improve air traffic management. Safety assurance requires full analysis of the possible consequences of new procedures; one method for achieving this is through Human Error Analysis (HEA). In order to carry out such a HEA, the spacing task had to be captured within a Task Analysis (TA) model. This paper covers the evaluation of three TA techniques that can be used as a precursor to HEA analysis—Hierarchical Task Analysis (HTA), STATEMATE and Integration Definition for Function Modelling (IDEF0).

Fault diagnosis occurrence and its precise prediction in nuclear power plants are extremely important in avoiding disastrous consequences. The inherent limitations of the current fault diagnosis methods make machine learning techniques and their hybrid methodologies possible solutions to remedy this challenge. This study sought to develop, examine, compare, and contrast three robust machine learning methodologies of adaptive neurofuzzy inference system, long short-term memory, and radial basis function network by modeling the loss of feed water event using RELAP5. The performance indices of residual plots, mean absolute percentage error, root mean squared error, and coefficient of determination were used to determine the most suitable algorithms for accurately diagnosing the loss of feed water transient signatures. The study found out that the adaptive neurofuzzy inference system model outperformed the other schemes when predicting the temperature of the steam generator tubes, the radial basis function network scheme was best suited in forecasting the mass flow rate at the core inlet, while the long short-term memory algorithm was best suited for the estimation of the severities of the loss of the feed water fault.

Dear Editor-in-ChiefNurses spend much more time dealing with patients compared with other healthcare personnel. This group has a significant role in identification of threatening complexities of patients, removing medical errors and in keeping patients safe, on the other hand, a considerable amount of human errors is committed by nurses (1). Therefore, nurses have to face with many occupational risks compared with other jobs and may suits relating to occupational negligence (1). Human errors associated with nursing duties; in particular, medication error has been identified as a central concern for the nursing profession (1). As the result of such events, patient is hurt unwantedly and staff suffers a great deal of damage. These events often result from the change of systemic specifications in duties, group, work environment, and organization (3).The present study was a cross sectional research aimed at comparing two human error identification and assessment methods, SPAR-H and CREAM, in nursing practice at a hospital in Iran. We investigated 31 duties according to job description announced by Iran Nursing Organization and professors of nursing.In the first step, we analyzed occupational duties using Hierarchical Task Analysis (HTA) method (4). Next, different tasks are executed for each sub task. After completing CREAM and SPAR-H worksheets, we first grouped the worksheets for each duty and analyzed total error probability and error risk using SPSS-16 (Chicago, IL, USA). In order to compare the two techniques based on multivariable decision making, we used analytical hierarchy process (5).The findings of demonstrated that, the estimated human error probability by SPAR-H was higher than those estimated by CREAM, but the most critical task, taking initial measures for cardiopulmonary resuscitation until the arrival of resuscitation team, was the same in both techniques. Moreover, it was determined that both techniques have similar results in identifying and assessing critical tasks with high probability of human error (Table 1). Furthermore, there was more difference between these two techniques in ranking potential errors with low probabilities; for instance, preparing bed before arrival of patient have the rank of 27 when we used SPAR-H technique 27, while its rank using CREAM technique was determined at 10 (Table 1).Based on previous studies in this field and also eliciting domain expert knowledge, seven criteria were selected for comparing two techniques with each other (6). …

The current paper presents the results of the evaluation of a novel human machine interface for supervision and guidance of multiple highly automated unmanned aircraft. Accidents of unmanned aircraft are often related to deficiencies in the design of the human machine interface. Many of these deficiencies are a consequence of insufficient consideration of human factors engineering principles in the early stages of system development. Therefore, in the design of the current human machine interface, empirically validated human factors methods were applied in order to optimally support a remote pilot in supervising and guiding multiple highly automated unmanned aircraft. An information management concept was developed that allows for an increase in the number of UAS that are being supervised without considerably increasing display complexity. In order to evaluate the human machine interface, two within-subj ect simulation studies were conducted. In both studies, pilots were asked to supervise and guide a varying number of UAS in several experimental scenarios using the new human machine interface. Following the experimental scenarios, a structured interview regarding the design of the human machine interface was conducted. The objective of the first study was to gather initial data on the general usability of the interface. The aim of the second simulation study was to investigate how increasing the number of UAS from one up to five affects the time that a pilot needs to acquire and change specific system parameters of any UAS under supervision. Further, the impact of increasing the number of UAS on pilot workload and situation awareness was assessed. The results of the interviews suggest that the design concept of the human machine interface is feasible and easy to understand. The information management concept was described as reasonable and logical. Important information was accessible quickly and (critical) system states could easily be identified. No significant effects of increasing the number of UASs to be supervised on reaction, workload or situation awareness were observed. The findings suggest that the information management concept is reasonable and usable.

The authors propose a new method to evaluate the human interface design of nuclear power plant equipment from the viewpoint of human error. Their system, called DIAS, is implemented on a workstation and consists of a maintenance personnel model and an equipment interface model. The maintenance personnel model stores the standard maintenance procedures which are represented by the augmented Petri net model. The authors consider the visual field, walking speed and the focal/peripheral working memory in the maintenance personnel model. DIAS analyzes the potential human errors of each task in the simulation results by using the human-error-mechanism knowledge base combined with a quantitative human error rate prediction technique. The equipment interface model can be easily redesigned on the graphical editor, which enables the analyst to evaluate alternative designs. They applied this system to evaluate the interface design of the actual GIS protection relay panels and their layout in the nuclear power plant.

Human error is the most-frequently ascribed contributor to incidents and accidents at electric utility generating sites. Such error often reveals the presence of latent errors in the organization or workplace. Identification of the antecedent conditions for human error is expected to help management to select and design effective safety programs and interventions in advance, rather than waiting to implement corrective action after incidents have occurred. The search for these antecedent conditions requires combining error and incident reports with a wide variety of background data sources.

ADVANCED MMIS TOWARD SUBSTANTIAL REDUCTION IN HUMAN ERRORS IN NPPS