Quantification of human error in maintenance using graph theory and matrix approach

Assessment of human error in maintenance requires identification of the contributing factors that lead to human error(s). These factors are called human error inducing factors (HEIFs), which take into consideration both the active and latent error contributing aspects related to man, machine and environment. A systems approach of the Graph Theory is applied in this paper for quantifying human error in maintenance activities that models the identified factors and their interactions/interrelationships in terms of human error digraph. The nodes in the digraph represent the HEIFs and the edges represent their interrelationships. The digraph is converted into an equivalent matrix and an expression based on this is developed, which is characteristic of the human error in maintenance. This expression is used to evaluate a human error index by substituting the numerical value of the factors and their interrelations. The index is a measure of the human error potential involved in the maintenance of systems. A higher value of index indicates that the error likelihood is more for the associated tasks, and more efforts are required to make the system less prone to human error. The proposed methodology is illustrated using a case study. The approach is anticipated to play a significant role in identifying sources of human errors and predicting their impact; and will help to integrate human factors during design stage with the objective of reducing human error in maintenance. Copyright © 2011 John Wiley & Sons, Ltd.     

Risk analysis of human error in interaction design by using a hybrid approach based on FMEA,SHERPA, and fuzzy TOPSIS

User experience is the focus of interaction design, and designing for errors is crucial for improving user experience. One method of designing for errors is to identify human errors and then initiate corrective actions on high-risk errors to reduce their adverse effects. In this study, we proposed a hybrid approach for risk analysis of human error concerning user experience of interactive systems. In this approach, systematic human error reduction and prediction approach (SHERPA) is first adopted to identify human error concerning user experience. Subsequently, failure mode and effect analysis (FMEA) is used to analyze the risk factors of the error, including occurrence, severity, and detection. Fuzzy technique for order preference by similarity to ideal solution (TOPSIS) is then used to calculate the risk priority number to rank the errors. Finally, corrective actions for high-risk errors are recommended. An in-vehicle information system was used to demonstrate the proposed approach. The results indicated that the proposed approach can effectively analyze the risk of human error concerning user experience and be used as a universal reliability approach for improving user experience in interaction design.     

脉冲调宽乘法器在交流应用下的误差及标准功率、电压、电流测量仪的研制

本文讨论了脉冲调宽乘法器用于交流测量时交直流变换误差与时分割频率的关系，提出了一种新的准确计算方法，并对相移误差等因素作了分析，给出了减小误差的措施。最后介绍了基于上述分析而设计研制的标准功率、电压、电流测量仪，其测量功率、电压、电流的误差均小于００１％     

Reliability of railway traffic personnel

The paper describes an analysis of reliability of railway traffic personnel. The human tasks critical to system safety are identified. Human error probability is chosen as a measure of human reliability in performing these tasks. The probabilities of some critical errors are estimated using the field data collected in the Slovenian railway traffic system. As stress conditions strongly affect the human performance, a simple model of the dependence of human error probability on stress levels is proposed.     

On the comparison of bilinear, cubic spline, and fuzzy interpolation techniques for robotic position measurements

This paper describes a novel technique for position error compensations of robots based on a fuzzy error interpolation method. A traditional robot calibration implements either model or modelless methods. The compensation of position error in a model-less method is to move the robot's end-effector to a target position in the robot workspace, and to find the target position error online based on the measured neighboring four-point errors around the target position. For this purpose, a stereo camera or other measurement device can be used to measure offline the position errors of the robot's end-effector at predefined grid points. By using the proposed fuzzy error interpolation technique, the accuracy of the position error compensation can be greatly improved, which is confirmed by the simulation results given in this paper. A comparison study among various interpolation methods, such as bilinear, cubic spline, and the fuzzy error interpolation technique is also made via simulation. The simulation results show that more accurate compensation results can be achieved using the fuzzy error interpolation technique compared with its bilinear and cubic spline counterparts.     

A method of human reliability analysis and quantification for space missions based on a Bayesian network and the cognitive reliability and error analysis method

Analyses of human reliability during manned spaceflight are crucial because human error can easily arise in the extreme environment of space and may pose a great potential risk to the mission. Although various approaches exist for human reliability analysis (HRA), all these approaches are based on human behavior on the ground. Thus, to appropriately analyze human reliability during spaceflight, this paper proposes a space‐based HRA method of quantifying the human error probability (HEP) for space missions. Instead of ground‐based performance shaping factors (PSFs), this study addresses PSFs specific to the space environment, and a corresponding evaluation system is integrated into the proposed approach to fully consider space mission characteristics. A Bayesian network is constructed based on the cognitive reliability and error analysis method (CREAM) to model these space‐based PSFs and their dependencies. By incorporating the Bayesian network, the proposed approach transforms the HEP estimation procedure into a probabilistic calculation, thereby overcoming the shortcomings of traditional HRA methods in addressing the uncertainty of the complex space environment. More importantly, by acquiring more information, the HEP estimates can be dynamically updated by means of this probabilistic calculation. By studying 2 examples and evaluating the HEPs for an International Space Station ingress procedure, the feasibility and superiority of the developed approach are validated both mathematically and in a practical scenario.     

Conversion of a mainframe simulation for maintenance performance to a PC environment

This paper presents a brief review of a mainframe version of a computer code for simulating maintenance crew performance crew and introduces advantages realized with the recent implementation of a personal computer (PC) version. The basic computer model—the maintenance personnel performance simulation (MAPPS)—has been developed and validated by the US nuclear Regulatory Commission (NRC) in order to improve maintenance practices and procedures at nuclear power plants. The simulation model is stochastically based, and users are able to model 2 to 15 person crews. Maintenance crew performance is varied as a function of task, environment, and personnel factors. MAPPS produces human error probabilities (HEPs) suitable for use in probabilistic risk assessments. These HEPs are also a potentially important source of information for risk management data bases such as the NRC sponsored Nuclear Computerized Library for Assessing Reactor Reliability (NUCLARR).     

A node enrichment adaptive refinement in Discrete Least Squares Meshless method for solution of elasticity problems

In this paper, an adaptive refinement procedure is proposed to be used with Discrete Least Squares Meshless (DLSM) method for accurate solution of planar elasticity problems. DLSM method is a newly introduced meshless method based on the least squares concept. The method is based on the minimization of a least squares functional defined as the weighted summation of the squared residual of the governing differential equation and its boundary conditions at nodal points used to discretize the domain and its boundaries. A Moving Least Square (MLS) method is used to construct the shape function making the approach a fully least squares based approach. An error estimate and adaptive refinement strategy is proposed in this paper to increase the efficiency of the DLSM method. For this, a residual based error estimator is introduced and used to discover the region of higher errors. The proposed error estimator has the advantages of being available at the end of each analysis contributing to the efficiency of the proposed method. An enrichment method is then used by adding more nodes to the area of higher errors as indicated by the error estimator. A Voronoi diagram is used to locate the position of the nodes to be added to the current nodal configuration. Efficiency and effectiveness of the proposed procedure is examined by adaptively solving two benchmark problems. The results show the ability of the proposed strategy for accurate simulation of elasticity problems.     

Virtual simulation of five-axis machine tool with consideration of CNC interpolation,servo dynamics,friction, and geometric errors

Abstract

A virtual machine tool (VMT) simulation system which considers tool center point (TCP) interpolation, geometric errors, servo dynamics, and friction effects for a five-axis machine tool is developed in this paper. A novel five-axis interpolation method is proposed to ensure that maximum velocity constraints for each axis can be satisfied. The geometric error model, including lead screw, straightness, angular and squareness errors is built to analyze the volumetric errors within the working space. The model which includes rigid body motion, friction model and servo control loops is utilized to evaluate servo dynamics and non-linear effects. The errors caused by the locations, servo dynamics, and friction effects are integrated into the VMT simulation program. Simulation results of TCP trajectory are represented by small line segments to generate NC codes. Then the NC codes are fed into VERICUT software to perform virtual cutting. To evaluate the interpolation design, cutting experiments are carried out on the five-axis engraving machine with a PC-based controller. The performances using the proposed interpolation method are comparable with the commercial CNC controller from Heidenhain. The effects of different error sources on the surface are demonstrated by cutting the sculpture of a human face. Path overcut caused by servo dynamics is found at sharp corners, and volumetric errors cause obvious tool marks and poor surface roughness. The proposed methodology can serve as a useful tool in evaluating the behaviors of error sources during the design stage.     

基于行为形成因子相关性的人因失误影响研究

生产过程中,行为形成因子会对人因失误产生不可忽略的作用。在行为形成因子诱发人因失误的过程中,其他行为形成因子也会对诱发过程产生影响。本文基于这种影响作用,对行为形成因子影响人因失误的程度进行了量化,求解得出了人因失误的概率,并进行了实验验证。     

A new model to optimize the human reliability based on CREAM and group decision making

The Cognitive Reliability and Error Analysis Method (CREAM) represents one of the second-generation approaches to human reliability assessment, taking into account the influence of environmental conditions on human error probability (HEP). In the context of CREAM, the Common Performance Conditions (CPCs) influence error probabilities. Since not all CPCs have equal impacts, this study employs the Bayesian Best Worst Method (BWM), a novel approach in group decision-making, to assign weights to these factors. Subsequently, two techniques based on basic CREAM are proposed. The current control mode is determined in the first technique according to the experts' opinions. Then the probability of human error is calculated based on the amount of control. It is possible to provide solutions for improving control mode, based on obtained results. Therefore, in this study, the second method has been used to make suggestions to enhance human reliability. For this purpose, in the second technique, an optimization problem is formulated to select the best applicable programs for managers to enhance human reliability. The proposed bi-objective model tries to increase the reliability of human resources by reducing human error and costs. The proposed bi-objective model seeks to bolster the reliability of human resources by concurrently minimizing HEP and associated costs. The efficiency of the presented methods is verified through a case study in the control room of the cement factory. The results of the first technique reveal an opportunistic control mode with a corresponding HEP of 0.0198. On the other hand, the outcomes of our proposed model underscore the greater impact of improving CPC levels in reducing the probability of human error. Ultimately, the practical programs derived from our mathematical model provide decision-makers with valuable insights to reduce the probability of human error to a mere 0.000172 through the transition from opportunistic to strategic control.     

Study on the thermally inducedspindle angular errors of a five-axis CNC machine tool

Thermally induced spindle angular errors of a machine tool are important factors that affect the machining accuracy of parts. It is critical to develop models with good generalization abilities to control these angular thermal errors. However, the current studies mainly focus on the modeling of linear thermal errors, and an angular thermal error model applicable to different working conditions has rarely been investigated. Furthermore, the formation mechanism of the angular thermal error remains to be studied. In this study, an analytical modeling method was proposed by analyzing the formation and propagation chain of the spindle angular thermal errors of a five-axis computer numerical control (CNC) machine tool. The effects of the machine tool structure and position were considered in the modeling process. The angular thermal error equations were obtained by analyzing the spatial thermoelastic deformation states. An analytical model of the spindle angular thermal error was established based on the geometric relation between thermal deformations. The model parameters were identified using the trust region least squares method. The results showed that the proposed analytical model exhibited good generalization ability in predicting spindle pitch angular thermal errors under different working conditions with variable spindle rotational speeds, spindle positions, and environmental temperatures in different seasons. The average mean absolute error (MAE), root mean square error (RMSE) and R² in twelve different experiments were 4.7 μrad, 5.6 μrad and 0.95, respectively. This study provides an effective method for revealing the formation mechanism and controlling the spindle angular thermal errors of a CNC machine tool. The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00409-x     

The application of the loglinear model to quantify human errors

This paper concentrates on using a quantitative method, the loglinear model, to investigate human error under a state of emergency. The loglinear model provides a systematic approach to find out the factors which lead to occurrences of human errors. The external performance shaping factor (PSF), internal PSF, and stressor PSF were found to be the statistically significant factors of human errors. In addition, the first-order interaction between external PSF and stressor PSF, as well as the second-order interaction of these three factors, were also verified as important parts of the human error model. Furthermore, the maximum likelihood which predicts human error probabilities could be obtained from the selected loglinear model.     

Human factors, human reliability and risk assessment in license renewal of a nuclear power plant

This paper describes human factors and human reliability assessments carried out as a part of operating license renewal of a nuclear power plant. The structure and contents of human factors assessments, the source material and the role of probabilistic safety assessment are described. Similar evaluations are recommended as an integral part of periodic safety reviews of regulated industrial facilities.The qualitative part of the human factors review is structured according to an international guide. The assessments are here enhanced with operating experience evaluations, measured by quantitative statistical data obtained from inspections and assessments made by plant safety and quality assurance personnel, by regulatory authorities and by peer reviews.The quantitative assessment is based on the roles and contributions of human errors in the accident risk of the target plant. The assessment uses importance measures quantified in probabilistic risk assessment. The scope and the quality of the risk assessment and the scope and the quality of human reliability assessments are also taken into account. Furthermore, the assessment describes how risk assessment can be used to reduce errors and improve human factors. The results tend to be very plant-specific, and the errors have very different importances in different operating states and for different initiating event categories. The results are useful for planning preventive actions, i.e. for preventing errors by developing and prioritizing human factors improvement activities.     

Failure analysis of power transformer for effective maintenance planning in electric utilities

In this paper, power transformer failures are analyzed and their root causes are systematically investigated in Tamil Nadu Transmission Corporation Limited (TANTRANSCO)/Tamil Nadu Generation and Distribution Corporation Limited (TANGEDCO) electric utilities, based on 196 failure cases from the year 2009–2013. Failure analysis is conducted in two phases. Initially, voltage level, geographical zone and power transformer components based failure analysis are performed through statistical analysis. Secondly, the most significant factors that cause power transformer failures are identified by using root cause analysis (RCA). Finally, current maintenance practice is reviewed and an effective maintenance planning has been proposed for implementation in order to prevent these failures and to maintain the power transformers in good operating condition during their life cycle. This study provides a practical guidance to help maintenance personnel for the best utilization of the power transformer in electric utilities.     

Reliability of drivers in urban intersections

The concept of human reliability has been widely used in industrial settings by human factors experts to optimise the person-task fit. Reliability is estimated by the probability that a task will successfully be completed by personnel in a given stage of system operation. Human Reliability Analysis (HRA) is a technique used to calculate human error probabilities as the ratio of errors committed to the number of opportunities for that error. To transfer this notion to the measurement of car driver reliability the following components are necessary: a taxonomy of driving tasks, a definition of correct behaviour in each of these tasks, a list of errors as deviations from the correct actions and an adequate observation method to register errors and opportunities for these errors. Use of the SAFE-task analysis procedure recently made it possible to derive driver errors directly from the normative analysis of behavioural requirements. Driver reliability estimates could be used to compare groups of tasks (e.g. different types of intersections with their respective regulations) as well as groups of drivers’ or individual drivers’ aptitudes. This approach was tested in a field study with 62 drivers of different age groups. The subjects drove an instrumented car and had to complete an urban test route, the main features of which were 18 intersections representing six different driving tasks. The subjects were accompanied by two trained observers who recorded driver errors using standardized observation sheets. Results indicate that error indices often vary between both the age group of drivers and the type of driving task. The highest error indices occurred in the non-signalised intersection tasks and the roundabout, which exactly equals the corresponding ratings of task complexity from the SAFE analysis. A comparison of age groups clearly shows the disadvantage of older drivers, whose error indices in nearly all tasks are significantly higher than those of the other groups. The vast majority of these errors could be explained by high task load in the intersections, as they represent difficult tasks. The discussion shows how reliability estimates can be used in a constructive way to propose changes in car design, intersection layout and regulation as well as driver training.     

A Review of Cognitive Models in Human Reliability Analysis

Human error behavior is determined by both environmental and human factors. In particular, psychological and spiritual factors have a decisive impact on human errors. The human cognitive model not only makes a sound exposition of the generation process and mechanism of human erroneous actions but also improves the accuracy and credibility of human reliability analysis (HRA). Therefore, it helps effectively avoid and prevent human errors in industrial fields. This paper highlights the significant role that the cognitive model has played in HRA. Then, based on an analysis of the nature of human behavior and the classifications of common human errors, several typical cognitive models are summarized in the areas of ergonomics, behavioral science, and cognitive engineering, including a cognitive model related to process, an information‐processing model, a decision‐making and problem‐solving process model, and a cognitive simulation model based on computer technology. Then, cognitive models and the corresponding HRA methods that are applied in the fields of reliability engineering, safety engineering, and risk assessment are reviewed. Finally, some directions and challenges are proposed for the future research of cognitive models applied in HRA methods based on the discussion of current cognitive models used in HRA methods. Copyright © 2016 John Wiley & Sons, Ltd.     

基于时延估计的海底线阵阵形估计方法研究

阵形估计是水听器阵列应用中的关键问题,基于时延估计的阵形估计方法比基于传感器测量和基于匹配场处理的方法具有更强的适应性和较高的精度。针对浅海水听器阵列中水平长线阵存在的纵向相关振荡现象引起的不能简单以某一阵元为基准求相对时延的问题,充分利用了阵元信号的高相关性,提出了基于子阵时延的阵形估计方法,针对子阵间时延估计误差向阵端累积的问题,该方法以时延估计的克拉美罗界为依据提出了合理的子阵方式,在一定程度上减小了误差传递。对已有海试数据阵形估计处理的结果表明,相对于单源固定间距方法和未分子阵的双源时延估计方法,基于子阵时延的阵形估计方法满足阵元间距的约束,有较好的空间谱特性,减小了阵形估计误差,对长水听器阵列的应用及阵形估计具有较大应用价值。     

人的可靠性综合分析模式及应用

提高系统可靠性的关键步骤是提高系统中人的可靠性,这需要对人的可靠性进行分析。当前分析人的可靠性主要依靠运用各类HRA模型,这些模型各有优缺点。为了研究航空人为差错,选取了具有代表性的3个HRA模型,对人的可靠性分析模型THERP（technique for human error rate prediction)、CREAM（cognitive reliability and error analysis method)、IDAC(information decision and action)进行了分析。将3种模型进行比较,找出它们的优劣之处,结合3种模型的优点,建立了以THERP模型、CREAM模型以及IDAC模型为主体的人的可靠性综合分析模式,并将该分析模式在航空人为差错分析上进行了应用,并给出实例说明该分析模式的应用。     

Calibration method for high-accuracy measurement of long focal length with Talbot interferometry

In this paper, a new calibration method for accurate long focal-length measurements, based on Talbot interferometry, is presented. Error analysis is derived in detail by the numerical method, and an effective way to improve the accuracy is proposed. By this method, the systematic errors that are the main factors effecting accuracy are calibrated and reduced. Both simulation and experiments have been carried out to prove the effectiveness and advantages of the proposed method as compared to conventional approaches. The experimental results reveal that the relative error is lower than 0.02%, and the repeatability is better than 0.05%. This method is especially useful for measuring long focal-length lenses.