A Hybrid Model for Human Error Probability Analysis

Felice, Fabio De; Petrillo, Antonella; Zomparelli, Federico

doi:10.1016/j.ifacol.2016.07.821

Cited by 17 publications

(10 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, Systematic Human Error Reduction and Prediction Analysis (SHERPA) [27] is a qualitative probabilistic human error analysis with a task-analytic direction which contains several failure modes: action errors, control errors, recovery errors, communication errors, choice errors. De Felice et al [28] propose a combination of CREAM and SHERPA that uses empirical data to assign probabilities to each mode; therefore, the results are strongly dependent on the case study domain and the reliability and amount of data.…”

Section: Probabilistic Human Modellingmentioning

confidence: 99%

How to Formally Model Human in Collaborative Robotics

Askarpour

2020

Electron. Proc. Theor. Comput. Sci.

View full text Add to dashboard Cite

Human-robot collaboration (HRC) is an emerging trend of robotics that promotes the co-presence and cooperation of humans and robots in common workspaces. Physical vicinity and interaction between humans and robots, combined with the uncertainty of human behaviour, could lead to undesired situations where humans are injured. Thus, safety is a priority for HRC applications. Safety analysis via formal modelling and verification techniques could considerably avoid dangerous consequences, but only if the models of HRC systems are comprehensive and realistic, which requires reasonably realistic models of human behaviour. This paper explores state-of-the-art solutions for modelling human and discusses which ones are suitable for HRC scenarios.

show abstract

Section: Probabilistic Human Modellingmentioning

confidence: 99%

How to Formally Model Human in Collaborative Robotics

Askarpour

2020

Electron. Proc. Theor. Comput. Sci.

View full text Add to dashboard Cite

show abstract

“…The SPAR-H methodology estimates probability of human error using predefined expression based on PSF composite. The value of HEP depends on the PSFs levels (P (error | PSF [1][2][3][4][5][6][7][8]. Considering this, to develop a CPT the number of probabilities will increase exponentially according to the number of parent nodes (45).…”

Section: Cpt Of An Error Nodementioning

confidence: 99%

“…The safety of all industries was examined by a group of continuous and systematic infrastructures, which are specified as "Critical Infrastructures" (1). These infrastructures can be systems, resources, a process, or a combination of these elements; the failure or unavailability of these infrastructures can interrupt the normal operation and safety of an industry (1). Maintenance procedures in complex industries are vulnerable to human performance (2,3).…”

Section: Introductionmentioning

confidence: 99%

Human Reliability Analysis (HRA) Using Standardized Plant Analysis Risk-Human (SPAR-H) and Bayesian Network (BN) for Pipeline Inspection Gauges (PIG) Operation: A Case Study in a Gas Transmission Plant

et al. 2019

View full text Add to dashboard Cite

Background: Pigging operation is one of the maintenance activities that is used to check pipeline functionality in operational conditions using a PIG device and high pressure of liquid/gas, which is potentially hazardous. Objectives: The present study aimed at customizing SPAR-H methodology for the pigging operation using Bayesian networks (BNs). It also aimed at identifying and analyzing human errors in pigging operation in a gas transmission company. Methods: The current article was composed of two main steps. In the first step, the SPAR-H BN model was developed using expertelicited prior probabilities of pigging operation applied to Bayesian network. In this step, CPTs of PSF nodes are constructed using prior probabilities, which are achieved from expert opinion. The CPT of error node is developed using coding process of SPAR-H formula in a simulation node. In the second step, a descriptive study was carried out to estimate the probability of human errors in pigging operation in a gas transmission plant in Iran. First, hierarchical task analysis (HTA) was conducted by walking through the pigging operation and interviews with workers. Next, the SPAR-H BN model was utilized for estimation of human error probability. Results: The developed model was tested on the pigging operation subtasks. In the considered case study, the mean probability of human error was estimated as 0.184. The highest probability of human error was related to "opening the kicker valve for enhancing pressure" subtask. Conclusions: The BNs were helpful to adapt the SPAR-H methodology to the pigging operation using dedicated prior probabilities. Beside that, the probabilities of human error can be updated taking into account the more realistic operational and environmental conditions.

show abstract

“…There exist several techniques of predictive nature (Baber and Stanton, 2002;Center for Chemical Process Safety CCPS, 2004;De Felice et al, 2016;Shorrock and Kirwan, 2002) or of prospective nature (Funk, 2009;Leveson, 2003Leveson, , 2004, but none of them has these characteristics or proposes a human error analysis based on the type of information that the operator gets from the process.…”

Section: Strong Dependence On Expert Judgment In Selecting Performancementioning

confidence: 99%

A novel qualitative prospective methodology to assess human error during accident sequences

2018

View full text Add to dashboard Cite

Numerous theoretical models and techniques to assess human error were developed since the 60's. Most of these models were developed for the nuclear, military, and aviation sectors. These methods have the following weaknesses that limit their use in industry: the lack of analysis of underlying causal cognitive mechanisms, need of retrospective data for implementation, strong dependence on expert judgment, focus on a particular type of error, and/or analysis of operator behaviour and decision-making without considering the role of the system in such decisions. The purpose of the present research is to develop a qualitative prospective methodology that does not depend exclusively on retrospective information, that does not require expert judgment for implementation and that allows predicting potential sequences of accidents before they occur. It has been proposed for new (or existent) small and medium-scale facilities, whose processes are simple. To the best of our knowledge, a methodology that meets these requirements has not been reported in literature thus far. The methodology proposed in this study was applied to the methanol storage area of a biodiesel facility. It could predict potential sequences of accidents, through the analysis of information provided by different system devices and the study of the possible deviations of operators in decision-making. It also enabled the identification of the shortcomings in the human-machine interface and proposed an optimization of the current configuration.

show abstract

A Hybrid Model for Human Error Probability Analysis

Cited by 17 publications

References 7 publications

How to Formally Model Human in Collaborative Robotics

How to Formally Model Human in Collaborative Robotics

Human Reliability Analysis (HRA) Using Standardized Plant Analysis Risk-Human (SPAR-H) and Bayesian Network (BN) for Pipeline Inspection Gauges (PIG) Operation: A Case Study in a Gas Transmission Plant

A novel qualitative prospective methodology to assess human error during accident sequences

Contact Info

Product

Resources

About