Predicting pilot error on the flight deck: Validation of a new methodology and a multiple methods and analysts approach to enhancing error prediction sensitivity

The Human Error Template (HET) is a recently developed methodology for predicting designed induced pilot error. This article describes a validation study undertaken to compare the performance of HET against three contemporary Human Error Identification (HEI) approaches when used to predict pilot errors for an approach and landing task and also to compare individual analyst error predictions to an approach to enhancing error prediction sensitivity: the multiple analysts and methods approach, whereby multiple analyst predictions using a range of HEI technique are pooled. The findings indicate that, of the four methodologies used in isolation, analysts using the HET methodology offered the most accurate error predictions, and also that the multiple analysts and methods approach was more successful overall in terms of error prediction sensitivity than the three other methods but not the HET approach. The results suggest that when predicting design induced error, it is appropriate to use domain specific approaches and also a toolkit of different HEI approaches and multiple analysts in order to heighten error prediction sensitivity

Preliminary human safety assessment (PHSA) for the improvement of the behavioral aspects of safety climate in the construction industry

Occupational safety in the construction industry still represents a relevant problem at a global level. In fact, the complexity of working activities in this sector requires a comprehensive approach that goes beyond normative compliance to guarantee safer working conditions. In particular, empirical research on the factors influencing the unsafe behavior of workers needs to be augmented. Thus, the relationship between human factors and safety management issues following a bottom-up approach was investigated. In particular, an easy-to-use procedure that can be used to better address workers' safety needs augmenting the company's safety climate and supporting safety management issues was developed. Such an approach, based on the assessment of human reliability factors, was verified in a real case study concerning the users of concrete mixer trucks. The results showed that the majority of human failures were action and retrieval errors, underlining the importance of theoretical and practical training programs as a means to improve safety behavior. In such a context, information and communication activities also resulted beneficially to augment the company's safety climate. The proposed approach, despite its qualitative nature, allows a clearer understanding of workers' perceptions of hazards and their risk-taking behavior, providing practical cues to monitor and improve the behavioral aspects of safety climate. Hence, these first results can contribute to augmenting safety knowledge in the construction industry, providing a basis for further investigations on the causalities related to human performances, which are considered a key element in the prevention of accidents

HUMAN ERROR IDENTIFICATION IN BUS DRIVER WORK USING SHERPA AND HEART

Traffic accidents, especially with a large capacity such as bus, can be caused by several factors. According to the Indonesian Directorate General of Land Transportation of the Ministry of Transportation in 2012, the factors causing traffic accidents in Indonesia are a human factor of 93.52%, vehicle factor by 2.76%, road factor 3.23%, and environmental factor by 0.49%. Therefore, research is needed to identify which human error has the greatest probability of accident cause using Systematic Human Error Reduction and Prediction Approach (SHERPA) method to identify job desk using Hierarchical Task Analysis (HTA) and Human Error Assessment Reduction Technique (HEART) method to calculate Human Error Probability (HEP). Based on the calculation of Human Error Probability value known the highest HEP value is not running the vehicle in accordance with the provisions of the speed that has been set with 0.375. Next is not to record or forget to record the damage that occurred during the trip with a value of 0.21. It did not check Bus equipment with a HEP value of 0.19, did not report when there was a problem on the street with a HEP value of 0.18 and did not break for the next preparation for departure with a HEP value of 0.1

A taxonomy of performance shaping factors for human reliability analysis in industrial maintenance

Purpose: Human factors play an inevitable role in maintenance activities, and the occurrence of Human Errors (HEs) affects system reliability and safety, equipment performance and economic results. The high HE rate increased researchers’ attention towards Human Reliability Analysis (HRA) and HE assessment approaches. In these approaches, various environmental and individual factors influence the performance of maintenance operators affecting Human Error Probability (HEP) with a consequent variability in the success of intervention. However, a deep analysis of such factors in the maintenance field, often called Performance Shaping Factors (PSFs), is still missing. This has led the authors to systematically evaluate the literature on Human Error in Maintenance (HEM) and on the PSFs, in order to provide a shared PSF taxonomy. Design/methodology/approach: A Systematic Literature Review (SLR) was conducted to identify and select peer-reviewed papers that provided evidence on the relationship between maintenance activities and human performance. The obtained results provided a wide overview in the field of interest, shedding light on three main research areas of investigation: methodologies for human error analysis in maintenance, performance shaping factors and maintenance error consequences. In particular, papers belonging to the area of PSFs were analysed in-depth in order to identify and classify the PSFs, with the aim of achieving the PSF taxonomy for maintenance activities. The effects of each PSF on human reliability were defined and detailed. Findings: A total of 63 studies were selected and then analysed through a systematic methodology. 46% of these studies presented a qualitative/quantitative assessment of PSFs through application in different maintenance activities. Starting from the findings of the aforementioned papers, a PSF taxonomy specific for maintenance activities was proposed. This taxonomy represents an important contribution for researchers and practitioners towards the improvement of HRA methods and their applications in industrial maintenance. Originality/value: The analysis outlines the relevance of considering HEM because different error types occur during the maintenance process with non-negligible effects on the system. Despite a growing interest in HE assessment in maintenance, a deep analysis of PSFs in this field and a shared PSF taxonomy are missing. This paper fills the gap in the literature with the creation of a PSF taxonomy in industrial maintenance. The proposed taxonomy is a valuable contribution for growing the awareness of researchers and practitioners about factors influencing maintainers’ performance.Peer Reviewe

Quantitative Evaluation of NDE Reliability

A comprehensive reliability programme is being performed by the UKAEA and CEGB which is studying aspects such as inspection procedures, equipment, and data interpretation and reporting(1). The influence of management and organisational aspects, and psychological and environmental factors are also being investigated, and the importance of these aspects has recently been highlighted by Behravesh et al(2). The information produced will enable recommendations to be made on methods of eliminating or controlling potential errors. These recommendations should, when coupled with a demonstration of the capability of the procedures, lead to objective and auditable assurance of the overall reliability of the inspection

Development of a Human Reliability Analysis (HRA) model for break scheduling management in human-intensive working activities

2016 - 2017Human factors play an inevitable role in working contexts and the occurrence of human errors impacts on system reliability and safety, equipment performance and economic results. If human fallibility contributes to majority of incidents and accidents in high-risk systems, it mainly affects the quality and productivity in low-risk systems. Due to the prevalence of human error and the huge and often costly consequences, a considerable effort has been made in the field of Human Reliability Analysis (HRA), thus arriving to develop methods with the common purpose to predict the human error probability (HEP) and to enable safer and more productive designs. The purpose of each HRA method should be the HEP quantification to reduce and prevent possible conditions of error in a working context. However, existing HRA methods do not always pursue this aim in an efficient way, focusing on the qualitative error evaluation and on high-risk contexts. Moreover, several working aspects have been considered to prevent accidents and improve human performance in human-intensive working contexts, as for example the selection of adequate work-rest policies. It is well-known that introducing breaks is a key intervention to provide recovery after fatiguing physical work, prevent the growth of accident risks, and improve human reliability and productivity for individuals engaged in either mental or physical tasks. This is a very efficient approach even if it is not widely applied. ... [edited by Author]XXX cicl

Improving Human Reliability Analysis for Railway Systems Using Fuzzy Logic

The International Union of Railway provides an annually safety report highlighting that human factor is one of the main causes of railway accidents every year. Consequently, the study of human reliability is fundamental, and it must be included within a complete reliability assessment for every railway-related system. However, currently RARA (Railway Action Reliability Assessment) is the only approach available in literature that considers human task specifically customized for railway applications. The main disadvantages of RARA are the impact of expert’s subjectivity and the difficulty of a numerical assessment for the model parameters in absence of an exhaustive error and accident database. This manuscript introduces an innovative fuzzy method for the assessment of human factor in safety-critical systems for railway applications to address the problems highlighted above. Fuzzy logic allows to simplify the assessment of the model parameters by means of linguistic variables more resemblant to human cognitive process. Moreover, it deals with uncertain and incomplete data much better than classical deterministic approach and it minimizes the subjectivity of the analyst evaluation. The output of the proposed algorithm is the result of a fuzzy interval arithmetic, $\alpha$ -cut theory and centroid defuzzification procedure. The proposed method has been applied to the human operations carried out on a railway signaling system. Four human tasks and two scenarios have been simulated to analyze the performance of the proposed algorithm. Finally, the results of the method are compared with the classical RARA procedure underline compliant results obtain with a simpler, less complex and more intuitive approach