An inter-method comparison of four Human Reliability Assessment models

Setayesh, Azin; Pasquale, Valentina Di; Neumann, Patrick

doi:10.1016/j.apergo.2022.103750

Cited by 10 publications

(6 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Factors that contribute to human error include at least those related to the person, task-related, man–machine interface, environment, and interactions between people in the organization. Through the study of existing behavior formation factor classification methods, such as 67 PSFs provided by THERP, 9 CPCs by CREAM, 8 PSFs by SPAR-H 42 , 43 and others, the behavior formation factors that may lead to human-caused errors are summarized by combining the characteristics of man–machine interaction operations of intelligent coal mine hoists, as shown in Table 1 .…”

Section: Methodsmentioning

confidence: 99%

Human reliability assessment of intelligent coal mine hoist system based on Bayesian network

Sun

Wang

et al. 2022

Sci Rep

View full text Add to dashboard Cite

The human reliability of intelligent coal mine hoist operation system is affected by many factors, in order to reduce the occurrence of human error in the hoist system and improve the reliability of the system. The characteristics of phased-mission task operation of hoists is combined, the phase dependence of human cognitive errors is considered and, a new human reliability evaluation method is proposed with the help of Bayesian network (BN) model in this paper. Firstly, the phase dependence of human cognitive errors was analyzed based on the cognitive behavior model. Then the human error analysis in the hoist system was carried out, and several main performance shaping factors are selected. Secondly, BN was used to build the human reliability model of the hoist system at each stage. Finally, it is found that the phase dependence of cognitive errors has a negative impact on the human reliability of the hoist system through the case analysis. At the same time, several main performance shaping factors (PSFs)were quantitatively analyzed by using the reverse reasoning ability of BN, which proves the effectiveness of the proposed method, and provides a scientific and reasonable theoretical basis for the development of effective human error prevention measures for the operation of intelligent coal mine hoists.

show abstract

Section: Methodsmentioning

confidence: 99%

Human reliability assessment of intelligent coal mine hoist system based on Bayesian network

Sun

Wang

et al. 2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…After entering into the DSM and improving their arrangement and after the second interview with the expert team, sub-tasks 53, 48, 38,32,18,16,42,41,40,25,24,23,22,11,10, and 52 have had fewer errors, which indicates the reduced human error and increased reliability.…”

Section: Step 7 Recalculating the Error Of Terminal Conductor Tasks A...mentioning

confidence: 99%

“…Wodajeneh et al 21 investigated the impact of ergonomics on reducing human error and found that the work environment safety as well as the individual productivity can be increased by compliance with human factors engineering principles. Setayesh, Pasquale and Neumann 22 studied the effect of design and human-system interaction on improving human reliability, and in this regard, proposed a qualitative method to help designers and managers to predict manpower problems in interacting with different products and systems which reveal themselves as human errors.…”

Section: Introductionmentioning

confidence: 99%

Developing a new method for improving the human resource reliability using the hybrid approach of SPAR‐H and DSM in the urban railway

Fakharzadeh,

Fakoor Saghih,

Bohlouri

et al. 2024

Quality & Reliability Eng

View full text Add to dashboard Cite

As one of the most important reasons of irreparable losses at work, human error is still a significant problem in spite of the rapid technological advancement and reduced role of humans in the systems set up and control. Therefore, with the aim of reducing human error, this study presents a new method to improve human reliability using the hybrid approach of SPAR‐H and DSM. For this purpose, the number of 53 tasks was specified for the terminal conductor using Hierarchical Task Analysis (HTA). Then, the error related to each task was calculated utilizing the Standardized Plant Analysis‐Risk Human (SPAR‐H) method, and based on the expert team's opinion. Next, the terminal conductor's tasks were entered into the DSM along with the error numbers and dependencies between tasks, and the most optimal arrangement of tasks was obtained by coding in MATLAB software. Finally, by using the SPAR‐H method, the error of the terminal conductor was calculated based on the new tasks arrangement and compared with the primary state. Based on the obtained results, the 30% increase in reliability shows the significant contribution of the optimal arrangement of tasks in reducing human error. The proposed method of this study helps managers to reviewing the task structure in high‐risk processes as an effective strategy to reduce human error.

show abstract

“…adopted by numerous studies (Setayesh et al, 2022;Di Pasquale et al, 2015a, 2015b. Additionally, some research has expanded on the standard PSF categories to include various subcategories or more nuanced, open-ended PSFs (Aju Kumar et al, 2015;Besco, 2004;Velmurugan et al, 2022).…”

Section: The State Of the Art In Psf Taxonomy (Rq1)mentioning

confidence: 99%

Taxonomy of performance shaping factors in manufacturing: A systematic literature review

Jha,

Di Pasquale,

Saleem

et al. 2024

Hum Ftrs & Erg Mfg Svc

Self Cite

View full text Add to dashboard Cite

Human error in manufacturing can have substantial consequences, including loss of life, injuries, productivity, and financial losses. Human reliability analysis (HRA) methods can be used to evaluate the likelihood of human error in manufacturing tasks and identify potential sources of error. Performance shaping factors (PSFs) are internal and external factors that influence human performance and can affect the likelihood of human reliability estimates in HRA methods. Understanding the impact of PSFs on human performance in manufacturing is essential for developing effective strategies to minimize the likelihood of human error and improve the safety and efficiency of manufacturing processes. This systematic review scrutinizes the literature on PSFs within manufacturing, highlighting HRA applications. Using the PRISMA protocol, studies from 2000 to 2024 across engineering and psychology were examined, culminating in the analysis of 35 pertinent works. The review identifies and contrasts various PSF taxonomies from established HRA methods like SPAR‐H, HEART, CREAM, and THERP, revealing their diverse applications in different manufacturing settings. The review also uncovers a tendency to devise taxonomies through the lens of experts' domain knowledge, particularly tailored to discrete manufacturing contexts. A critical gap is observed in the lack of a uniform PSF framework, with the current literature reflecting a disparate understanding of PSFs' roles, definitions, and interrelations. This absence is further pronounced by the inadequate integration of human factors in the dialogue surrounding Industry 4.0. The analysis points to the necessity of harmonizing PSFs to better assess human reliability amid technological integration. The findings emphasize the need for an industry‐specific PSF framework that aligns with the intricacies of manufacturing operations, thus enabling more accurate HRA outcomes and informing strategies for error reduction and process optimization.

show abstract

An inter-method comparison of four Human Reliability Assessment models

Cited by 10 publications

References 63 publications

Human reliability assessment of intelligent coal mine hoist system based on Bayesian network

Human reliability assessment of intelligent coal mine hoist system based on Bayesian network

Developing a new method for improving the human resource reliability using the hybrid approach of SPAR‐H and DSM in the urban railway

Taxonomy of performance shaping factors in manufacturing: A systematic literature review

Contact Info

Product

Resources

About