A simplified CREAM prospective quantification process and its application

He, Xiao-Song; Wang, Yao; Shen, Zupei; Xiang-rui, Huang

doi:10.1016/j.ress.2006.10.026

Cited by 117 publications

(69 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The notation can be taken into consideration to calculate the total HEP value of the whole tasks. Table 3 shows the notation in line of the rules to find the total HEP values (He et al, 2008).…”

Section: Ahp Methodologymentioning

confidence: 99%

A methodological extension to human reliability analysis for cargo tank cleaning operation on board chemical tanker ships

Akyüz

Celik

2015

Safety Science

View full text Add to dashboard Cite

Section: Ahp Methodologymentioning

confidence: 99%

A methodological extension to human reliability analysis for cargo tank cleaning operation on board chemical tanker ships

Akyüz

Celik

2015

Safety Science

View full text Add to dashboard Cite

“…This value can be calculated by deducting the number of reduced CPCs from improved CPCs which is depicted in Eq. (1) where X denotes the number of reduced CPCs and Y denotes the number of improved CPCs (He et al, 2008).…”

Section: Design a Risk-based Methodologymentioning

confidence: 99%

Quantification of human error probability towards the gas inerting process on-board crude oil tankers

Akyüz

2015

Safety Science

View full text Add to dashboard Cite

“…us, if a particular industry wants to understand its specific problems, it must collect data from scratch [34]. (2) Over-reliance on expert judgment: In the existing HRA method, the evaluation of factors that influence human errors (performance-shaping factors (PSFs)) and the probability of occurrence rely mainly on the subjective judgment of experts, which can easily cause a large random error [20,31,35,36] Despite these gaps, Liao et al [37] had proposed a human error model based on the CREAM that includes more variables that capture the characteristics of construction projects.…”

Section: Challenges Of Human Reliabilitymentioning

confidence: 99%

Estimating the Influence of Improper Workplace Environment on Human Error: Posterior Predictive Analysis

Liu

Shi

et al. 2018

Advances in Civil Engineering

View full text Add to dashboard Cite

A model for identifying, analyzing, and quantifying the mechanisms for the influence of improper workplace environment on human error in elevator installation is proposed in this study. By combining a modification of a human error model with realworld inspection data collected by an elevator installation company, the influence paths of improper workplace environment on the conditional probability of human error were quantified using a Bayesian network parameter-learning estimation method and posterior predictive simulation. Under the condition of an improper workplace environment, the probability of human error increased by 80% of its original value, a factor much higher than that resulting from improper management. e most probable influence was found to be improper workmanship and changes in the information required by the worker, thus triggering cognitive failure and consequent unsafe actions by workers. e proposed methodology (posterior predictive simulation) provides a new approach in construction studies for quantifying the probabilistic levels of various causal paths, and the results show the key mechanism for the influence of improper workplace environment on human error using real-world mechanical installation data.

show abstract

A simplified CREAM prospective quantification process and its application

Cited by 117 publications

References 6 publications

A methodological extension to human reliability analysis for cargo tank cleaning operation on board chemical tanker ships

A methodological extension to human reliability analysis for cargo tank cleaning operation on board chemical tanker ships

Quantification of human error probability towards the gas inerting process on-board crude oil tankers

Estimating the Influence of Improper Workplace Environment on Human Error: Posterior Predictive Analysis

Contact Info

Product

Resources

About