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

Smart operators: How Industry 4.0 is affecting the worker's performance in manufacturing contexts

Abstract The fourth industrial revolution is affecting the workforce at strategical, tactical, and operational levels and it is leading to the development of new careers with precise and specific skills and competence. The implementation of enabling technologies in the industrial context involves new types of interactions between operators and machines, interactions that transform the industrial workforce and have significant implications for the nature of the work. The incoming generation of Smart Operators 4.0 is characterised by intelligent and qualified operators who perform the work with the support of machines, interact with collaborative robots and advanced systems, use technologies such as wearable devices and augmented and virtual reality. The correct interaction between the workforce and the various enabling technologies of the 4.0 paradigm represents a crucial aspect of the success of the smart factory. However, this interaction is affected by the variability of human behaviour and its reliability, which can strongly influence the quality, safety, and productivity standards. For this reason, this paper aims to provide a clear and complete analysis of the different types of smart operators and the impact of 4.0 enabling technologies on the performance of operators, evaluating the stakeholders involved, the type of interaction, the changes required for operators in terms of added and removed work, and the new performance achieved by workers

Smart operators: How augmented and virtual technologies are affecting the worker's performance in manufacturing contexts

Purpose: The correct interaction between the workforce and augmented, virtual, and mixed reality technologies represents a crucial aspect of the success of the smart factory. This interaction is, indeed, affected by the variability of human behavior and its reliability, which can strongly influence the quality, safety, and productivity standards. For this reason, this paper aims to provide a clear and complete analysis of the impacts of these technologies on the performance of operators. Design/methodology/approach: A Systematic Literature Review (SLR) was conducted to identify peer-reviewed papers that focused on the implementation of augmented and virtual technologies in manufacturing systems and their effects on human performance. Findings: In total, 61 papers were selected and thoroughly analyzed. The findings of this study reveal that Augmented, Virtual and Mixed Reality can be applied for several applications in manufacturing systems with different types of devices, that involve various advantages and disadvantages. The worker’s performance that are influencing by the use of these technologies are above all time to complete a task, error rate and mental and physical workload. Originality/value: Over the years Augmented, Virtual and Mixed Reality technologies in manufacturing systems have been investigated by researchers. Several studies mostly focused on technological issues, have been conducted. The role of the operator, whose tasks may be influenced positively or negatively by the use of new devices, has been hardly ever analyzed and a deep analysis of human performance affected by these technologies is missing. This study represents a preliminary analysis to fill this gap. The results obtained from the SLR allowed us to develop a conceptual framework that investigates the current state-of-the-art knowledge about the topic and highlights gaps in the current researchPeer Reviewe

Digital Twin Models in Industrial Operations: A Systematic Literature Review

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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

An Overview of Human Reliability Analysis Techniques in Manufacturing Operations

In recent years, there has been a decrease in accidents due to technical failures through technological developments of redundancy and protection, which have made systems more reliable. However, it is not possible to talk about system reliability without addressing the failure rate of all its components; among these components, "man" – because his rate of error changes the rate of failure of components with which he interacts. It is clear that the contribution of the human factor in the dynamics of accidents – both statistically and in terms of severity of consequences – is high [2]. Although valid values are difficult to obtain, estimates agree that errors committed by man are responsible for 60–90% of the accidents; the remainder of accidents are attributable to technical deficiencies [2,3,4]. The incidents are, of course, the most obvious human errors in industrial systems, but minor faults can seriously reduce the operations performances, in terms of productivity and efficiency. In fact, human error has a direct impact on productivity because errors affect the rates of rejection of the product, thereby increasing the cost of production and possibly reduce subsequent sales. Therefore, there is need to assess human reliability to reduce the likely causes of errors [1]. The starting point of this work was to study the framework of today’s methods of human reliability analysis (HRA): those quantitative of the first generation (as THERP and HCR), those qualitative of second (as CREAM and SPAR-H), and new dynamic HRA methods and recent improvements of individual phases of HRA approaches. These methods have, in fact, the purpose of assessing the likelihood of human error – in industrial systems, for a given operation, in a certain interval of time and in a particular context – on the basis of models that describe, in a more or less simplistic way, the complex mechanism that lies behind the single human action that is potentially subject to error [1]. The concern in safety and reliability analyses is whether an operator is likely to make an incorrect action and which type of action is most likely [5]. The goals defined by Swain and Guttmann (1983) in discussing the THERP approach, one of the first HRA methods developed, are still valid: The objective of a human reliability analysis is ‘to evaluate the operator’s contribution to system reliability’ and, more precisely, ‘to predict human error rates and to evaluate the degradation to human–machine systems likely to be caused by human errors in association with equipment functioning, operational procedures and practices, and other system and human characteristics which influence the system behavior’ [7]. The different HRA methods analysed allowed us to identify guidelines for determining the likelihood of human error and the assessment of contextual factors. The first step is to identify a probability of human error for the operation to be performed, while the second consists of the evaluation through appropriate multipliers, the impact of environmental, and the behavioural factors of this probability [1]. The most important objective of the work will be to provide a simulation module for the evaluation of human reliability that must be able to be used in a dual manner [1]: In the preventive phase, as an analysis of the possible situation that may occur and as evaluation of the percentage of pieces discarded by the effect of human error; In post-production, to understand what are the factors that influence human performance so they can reduce errors. The tool will also provide for the possibility of determining the optimal configuration of breaks through use of a methodology that, with assessments of an economic nature, allow identification of conditions that, in turn, is required for the suspension of work for psychophysical recovery of the operator and then for the restoration of acceptable values of reliability [1]

Special Issue: Smart manufacturing forsustainability: Trends and research challenges

Peer Reviewe

Encuesta iberoamericana sobre Rutinas Laborales y Cotidianas en Tiempos de COVID-19. Principales resultados

La Red TRAGEVIC publica el Informe "Rutinas laborales y cotidianas en tiempos de COVID-19" elaborado a partir de una encuesta online administrada durante el periodo de confinamiento en varios países iberoamericanos. El objetivo de la encuesta fue identificar los cambios en las rutinas cotidianas, de trabajo y de estudio generados por las medidas de aislamiento social implementadas por los gobiernos de los países iberoamericanos desde la irrupción de la pandemia del COVID-19. El informe presenta los principales resultados obtenidos.Fil: Viego, Valentina. UNS/IIESS; Argentina.Fil: Actis Di Pasquale, Eugenio. Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales; Argentina

Teletrabajo y cuidados en Argentina. Las desigualdades de género a la luz de las restricciones impuestas por la COVID-19

La pandemia por la COVID-19 y las medidas de aislamiento aplicadas en Argentina durante 2020 afectaron a toda la población ocupada, aunque de distinta manera. En esta ponencia nos centramos en quienes tuvieron que trabajar desde el hogar y determinamos el impacto diferencial entre mujeres y varones sobre la cantidad, calidad y condiciones de trabajo remunerado y la organización de los cuidados. Además, destacamos las brechas que se presentan en ambientes donde las tareas de cuidado se encuentran incrementadas por la presencia de niños y niñas (NNyNN) y/o adultos dependientes.Fil: Actis Di Pasquale, Eugenio. Universidad Nacional de Mar del Plata. Facultad de Ciencias Económicas y Sociales; Argentina.Fil: Viego, Valentina. Universidad Nacional del Sur. Departamento de Economía; Argentina