Assuring quality of the human–computer interface

The issue of human–computer interface quality has been brought currently into focus due to (a) a change in the character of users who dominate the computer market, (b) the availability of expertise in design for usability and its assurance, and (c) the finally recognized business benefits for vendors of user friendly equipment. Because the underlying human factors expertise belongs to the category of enabling generic quality assurance technologies, the quality management and engineering communities must master this new issue, and related knowledge and methods. The objective of this review article is to aid the quality professionals to respond successfully to this challenge by presenting the fundamentals of human factors engineering, its role in the design for usability process, and the associated methods of assuring quality of the human–computer interface.     

Accident sequence analysis of human–computer interface design

It is important to predict potential accident sequences of human–computer interaction in a safety-critical computing system so that vulnerable points can be disclosed and removed. We address this issue by proposing a Multi-Context human–computer interaction Model along with its analysis techniques, an Augmented Fault Tree Analysis, and a Concurrent Event Tree Analysis. The proposed augmented fault tree can identify the potential weak points in software design that may induce unintended software functions or erroneous human procedures. The concurrent event tree can enumerate possible accident sequences due to these weak points.     

Development of an advanced human–machine interface for next generation nuclear power plants

An advanced human–machine interface (HMI) has been developed to enhance the safety and availability of a nuclear power plant (NPP) by improving operational reliability. The key elements of the proposed HMI are the large display panels which present synopsis of plant status and the compact, computer-based work stations for monitoring, control and protection functions. The work station consists of four consoles such as a dynamic alarm console (DAC), a system information console (SIC), a computerized operating-procedure console (COC), and a safety system information console (SSIC). The DAC provides clean alarm pictures, in which information overlapping is excluded and alarm impacts are discriminated, for quick situation awareness. The SIC supports a normal operation by offering all necessary system information and control functions over non-safety systems. In addition, it is closely linked to the other consoles in order to automatically display related system information according to situations of the DAC and the COC. The COC aids operators with proper operating procedures during normal plant startup and shutdown or after a plant trip, and it also reduces their physical/mental burden through soft automation. The SSIC continuously displays safety system status and enables operators to control safety systems. The proposed HMI has been evaluated using the checklists that are extracted from various human factors guidelines. From the evaluation results, it can be concluded that the HMI is so designed as to address the human factors issues reasonably. After sufficient validation, the concept and the design features of the proposed HMI will be reflected in the design of the main control room of the Korean Next Generation Reactor (KNGR).     

核电厂系统人因工程学的应用研究

文章阐述了核电厂人因工程学应用现状，并介绍了应用在核电厂的人的可靠性分析的方法，提出了应用人因工程学改进核电厂可靠性与安全性的一些建议。     

The human error rate assessment and optimizing system HEROS — a new procedure for evaluating and optimizing the man–machine interface in PSA

A new procedure allowing the probabilistic evaluation and optimization of the man–machine system is presented. This procedure and the resulting expert system HEROS, which is an acronym for Human Error Rate Assessment and Optimizing System, is based on the fuzzy set theory. Most of the well-known procedures employed for the probabilistic evaluation of human factors involve the use of vague linguistic statements on performance shaping factors to select and to modify basic human error probabilities from the associated databases. This implies a large portion of subjectivity. Vague statements are expressed here in terms of fuzzy numbers or intervals which allow mathematical operations to be performed on them. A model of the man–machine system is the basis of the procedure. A fuzzy rule-based expert system was derived from ergonomic and psychological studies. Hence, it does not rely on a database, whose transferability to situations different from its origin is questionable. In this way, subjective elements are eliminated to a large extent. HEROS facilitates the importance analysis for the evaluation of human factors, which is necessary for optimizing the man–machine system. HEROS is applied to the analysis of a simple diagnosis of task of the operating personnel in a nuclear power plant.     

An analysis of maintenance failures at a nuclear power plant

In this paper, a study of faults caused by maintenance activities is presented. The objective of the study was to draw conclusions on the unplanned effects of maintenance on nuclear power plant (NPP) safety and system availability. More than 4400 maintenance history reports from the years 1992–1994 of Olkiluoto BWR NPP were analysed together with the maintenance personnel. The human action induced faults were classified, e.g. according to their multiplicity and effects. This paper presents and discusses the results of a statistical analysis of the data. Instrumentation and electrical components appeared to be especially prone to human failures. Many human failures were found in safety related systems. Several failures also remained latent from outages to power operation. However, the safety significance of failures was generally small. Modifications were an important source of multiple human failures. Plant maintenance data is a good source of human reliability data and it should be used more in the future.     

Development of a path model for human‐induced unplanned reactor trips in nuclear power plants

A simple path model for human‐induced unplanned reactor trips in nuclear power plants (NPPs) is proposed. The path model consists of four plant states and seven transitions between the four plant states, and describes how NPPs in the normal operation state result in unplanned reactor trips due to human errors. By applying the simple path model to historic unplanned reactor trip data, it is found that two out of five paths take more than 80% of the human‐induced unplanned reactor trips. The proposed path model for human‐induced unplanned reactor trips in NPPs is expected to provide insights into how human‐induced unplanned reactor trips can be reduced by cutting the critical paths to human‐induced unplanned reactor trips. Copyright © 2010 John Wiley & Sons, Ltd.     

An analytic model for situation assessment of nuclear power plant operators based on Bayesian inference

Simulation-based human reliability analysis (HRA) methods such as IDAC seem to provide a new direction for the development of advanced HRA methods. In such simulation-based HRA methods, the simulation model for the situation assessment of nuclear power plant (NPP) operators is essential, especially for addressing the issue of errors-of-commission (EOCs). Therefore, we propose an analytic model for the situation assessment of NPP operators based on Bayesian inference. The proposed model is found to be able to address several important features of the situation assessment of NPP operators, and is expected to provide good approximations to some parts of the situation assessment. A comparison with an existing model and identification of several other features of the situation assessment of NPP operators that should be further addressed are also provided.     

A computational model for knowledge-driven monitoring of nuclear power plant operators based on information theory

To develop operator behavior models such as IDAC, quantitative models for the cognitive activities of nuclear power plant (NPP) operators in abnormal situations are essential. Among them, only few quantitative models for the monitoring and detection have been developed. In this paper, we propose a computational model for the knowledge-driven monitoring, which is also known as model-driven monitoring, of NPP operators in abnormal situations, based on the information theory. The basic assumption of the proposed model is that the probability that an operator shifts his or her attention to an information source is proportional to the expected information from the information source. A small experiment performed to evaluate the feasibility of the proposed model shows that the predictions made by the proposed model have high correlations with the experimental results. Even though it has been argued that heuristics might play an important role on human reasoning, we believe that the proposed model can provide part of the mathematical basis for developing quantitative models for knowledge-driven monitoring of NPP operators when NPP operators are assumed to behave very logically.     

Interface‐reduction for the Craig–Bampton and Rubin method applied to FE–BE coupling with a large fluid–structure interface

Component mode‐based model‐order reduction (MOR) methods like the Craig–Bampton method or the Rubin method are known to be limited to structures with small coupling interfaces. This paper investigates two interface‐reduction methods for application of MOR to systems with large coupling interfaces: for the Craig–Bampton method a direct reduction method based on strain energy considerations is investigated. Additionally, for the Rubin method an iterative reduction scheme is proposed, which incrementally constructs the reduction basis. Hereby, attachment modes are tested if they sufficiently enlarge the spanned subspace of the current reduction basis. If so, the m‐orthogonal part is used to augment the basis. The methods are applied to FE–BE coupled systems in order to predict the vibro‐acoustic behavior of structures, which are partly immersed in water. Hereby, a strong coupling scheme is employed, since for dense fluids the feedback of the acoustic pressure onto the structure is not negligible. For two example structures, the efficiency of the reduction methods with respect to numerical effort, memory consumption and computation time is compared with the exact full‐order solution. Copyright © 2008 John Wiley & Sons, Ltd.     

A method for identifying instrument faults in nuclear power plants possibly leading to wrong situation assessment

In this paper, we propose a method for identifying instrument faults that could potentially affect an operators’ situation assessment capability in nuclear power plants (NPPs), an issue which has received a lot of attention recently. In the proposed method, patterns of selected plant parameter trends in selected plant states and NPP operators’ patterns of selected plant parameter trends in selected plant states are analyzed, and a comparison between the two kinds of patterns is performed to identify instrument faults which could potentially affect a NPP operators’ capability to correctly assess a plant's conditions. An example application is presented to demonstrate how the proposed method can be used to identify the possibilities of operators’ developing a wrong situation assessment because of instrument faults and to identify the corresponding safety concerns. We conclude that in order to get more accurate results, an analysis with a full-scope NPP simulator and interviews with NPP operators will be necessary.     

A computational model for evaluating the effects of attention, memory, and mental models on situation assessment of nuclear power plant operators

Operators in nuclear power plants have to acquire information from human system interfaces (HSIs) and the environment in order to create, update, and confirm their understanding of a plant state, as failures of situation assessment may cause wrong decisions for process control and finally errors of commission in nuclear power plants. A few computational models that can be used to predict and quantify the situation awareness of operators have been suggested. However, these models do not sufficiently consider human characteristics for nuclear power plant operators.In this paper, we propose a computational model for situation assessment of nuclear power plant operators using a Bayesian network. This model incorporates human factors significantly affecting operators’ situation assessment, such as attention, working memory decay, and mental model.As this proposed model provides quantitative results of situation assessment and diagnostic performance, we expect that this model can be used in the design and evaluation of human system interfaces as well as the prediction of situation awareness errors in the human reliability analysis.     

Human error risk management for engineering systems: a methodology for design, safety assessment, accident investigation and training

The objective of this paper is to tackle methodological issues associated with the inclusion of cognitive and dynamic considerations into Human Reliability methods. A methodology called Human Error Risk Management for Engineering Systems is presented that offers a ‘roadmap’ for selecting and consistently applying Human Factors approaches in different areas of application and contains also a ‘body’ of possible methods and techniques of its own. Two types of possible application are discussed to demonstrate practical applications of the methodology. Specific attention is dedicated to the issue of data collection and definition from specific field assessment.     

Analysis of operators' performance under emergencies using a training simulator of the nuclear power plant

It is well known that there are many factors that affect the reliability of nuclear power plants (NPPs). Among them, human reliability has been considered one of the most important factors. Thus, not only in order to quantify human reliability but also to identify main causes that can degrade human reliability, various kinds of human reliability analysis (HRA) methods have been suggested and utilized in many countries. However, to perform HRA more appropriately, it is necessary to collect plant-specific or domain-specific human performance data: especially for emergencies: because they can be used to generate requisite information for HRA. From this point of view, simulator studies under emergencies may be considered important sources for obtaining human performance data.In this study, the performance data of operating crews in coping with emergencies of the reference NPP have been collected and analyzed to develop human performance database (HPDB). Since the number of collected records is 112, it can be said that extracted/analyzed results included in HPDB are statistically meaningful. Therefore, HPDB can be used not only for HRA input data but also for multiple purposes such as improving emergency operating procedures and developing advanced HRA methods.     

A rheological interface model and its space–time finite element formulation for fluid–structure interaction

This contribution discusses extended physical interface models for fluid–structure interaction problems and investigates their phenomenological effects on the behavior of coupled systems by numerical simulation. Besides the various types of friction at the fluid–structure interface the most interesting phenomena are related to effects due to additional interface stiffness and damping. The paper introduces extended models at the fluid–structure interface on the basis of rheological devices (Hooke, Newton, Kelvin, Maxwell, Zener). The interface is decomposed into a Lagrangian layer for the solid‐like part and an Eulerian layer for the fluid‐like part. The mechanical model for fluid–structure interaction is based on the equations of rigid body dynamics for the structural part and the incompressible Navier–Stokes equations for viscous flow. The resulting weighted residual form uses the interface velocity and interface tractions in both layers in addition to the field variables for fluid and structure. The weak formulation of the whole coupled system is discretized using space–time finite elements with a discontinuous Galerkin method for time‐integration leading to a monolithic algebraic system. The deforming fluid domain is taken into account by deformable space–time finite elements and a pseudo‐structure approach for mesh motion. The sensitivity of coupled systems to modification of the interface model and its parameters is investigated by numerical simulation of flow induced vibrations of a spring supported fluid‐immersed cylinder. It is shown that the presented rheological interface model allows to influence flow‐induced vibrations. Copyright © 2010 John Wiley & Sons, Ltd.     

A study on the development of a task complexity measure for emergency operating procedures of nuclear power plants

In this study, a measure called task complexity (TACOM) that can quantify the complexity of tasks stipulated in emergency operating procedures of nuclear power plants is developed. The TACOM measure consists of five sub-measures that can cover remarkable complexity factors: (1) amount of information to be managed by operators, (2) logical entanglement due to the logical sequence of the required actions, (3) amount of actions to be accomplished by operators, (4) amount of system knowledge in recognizing the problem space, and (5) amount of cognitive resources in establishing an appropriate decision criterion. The appropriateness of the TACOM measure is investigated by comparing task performance time data with the associated TACOM scores. As a result, it is observed that there is a significant correlation between TACOM scores and task performance time data. Therefore, it is reasonable to expect that the TACOM measure can be used as a meaningful tool to quantify the complexity of tasks.     

A study on the systematic framework to develop effective diagnosis procedures of nuclear power plants

In complex systems such as the nuclear and chemical industry, the importance of a diagnosis procedure has been well recognized, since identifying the nature of an on-going event should be preceded to determine successful countermeasures or remedial actions. Unfortunately, a systematic framework that can suggest a unified and consistent process for constructing useful diagnosis procedures seems to be scant.In this paper, the systematic framework that can provide a sound way in constructing a diagnosis procedure is suggested based on two kinds of technical bases, such as the decision-making strategies of human and the test sequencing technique. To demonstrate the appropriateness of suggested framework, the diagnosis procedure of the reference nuclear power plant is reformed based on it. Subjective ratings are conducted to compare reformed procedure with the original one, and results support that operators' performance in an event diagnosis could be improved. Thus, although well designed experiments are needed to draw a reliable conclusion, it is expected that suggested framework could be applied to provide a consistent process in constructing useful diagnosis procedures.     

Identifying cognitive complexity factors affecting the complexity of procedural steps in emergency operating procedures of a nuclear power plant

In complex systems such as a nuclear and chemical plant, it is well known that the provision of understandable procedures that allow operators to clarify what needs to be done and how to do it is one of the requisites to secure their safety.As a previous study in providing understandable procedures, the step complexity (SC) measure that can quantify the complexity of procedural steps in emergency operating procedures (EOPs) of a nuclear power plant (NPP) was suggested. However, the necessity of additional complexity factors that can consider a cognitive aspect in evaluating the complexity of procedural steps is raised.To this end, the comparisons between operators' performance data measured by the form of a step performance time with their behavior in carrying out the prescribed activities of procedural steps are conducted in this study. As a result, two kinds of complexity factors (the abstraction level of knowledge and the level of engineering decision) that could affect an operator's cognitive burden are identified.Although a well-designed experiment is indispensable for confirming the appropriateness of the additional complexity factors, it is strongly believed that the change of operators' performance data can be more authentically explained if the additional complexity factors are taken into consideration.     

A model-based framework for the analysis of team communication in nuclear power plants

Advanced human-machine interfaces are rapidly changing the interaction between humans and systems, with the level of abstraction of the presented information, the human task characteristics, and the modes of communication all affected. To accommodate the changes in the human/system co-working environment, an extended communication analysis framework is needed that can describe and relate the tasks, verbal exchanges, and information interface. This paper proposes an extended analytic framework, referred to as the H-H-S (human-human-system) communication analysis framework, which can model the changes in team communication that are emerging in these new working environments. The stage-specific decision-making model and analysis tool of the proposed framework make the analysis of team communication easier by providing visual clues. The usefulness of the proposed framework is demonstrated with an in-depth comparison of the characteristics of communication in the conventional and advanced main control rooms of nuclear power plants.