The Application of the Hermeneutic Process to Qualitative Safety Data: A Case Study using Data from the CIRAS project

This article describes the new qualitative methodology developed for use in CIRAS (Confidential Incident Reporting and Analysis System), the confidential database set up for the UK railways by the University of Strathclyde. CIRAS is a project in which qualitative safety data are disidentified and then stored and analysed in a central database. Due to the confidential nature of the data provided, conventional (positivist) methods of checking their accuracy are not applicable; therefore a new methodology was developed - the Applied Hermeneutic Methodology (AHM). Based on Paul Ricoeur's `hermeneutic arc', this methodology uses appropriate computer software to provide a method of analysis that can be shown to be reliable (in the sense that consensus in interpretations between different interpreters can be demonstrated). Moreover, given that the classifiers of the textual elements can be represented in numeric form, AHM crosses the `qualitative-quantitative divide'. It is suggested that this methodology is more rigorous and philosophically coherent than existing methodologies and that it has implications for all areas of the social sciences where qualitative texts are analysed

Identification of the human factors contributing to maintenance failures in a petroleum operation

Objective: This research aimed to identify the most frequently occurring human factors contributing to maintenance-related failures within a petroleum industry organization. Commonality between failures will assist in understanding reliability in maintenance processes, thereby preventing accidents in high-hazard domains. Background: Methods exist for understanding the human factors contributing to accidents. Their application in a maintenance context mainly has been advanced in aviation and nuclear power. Maintenance in the petroleum industry provides a different context for investigating the role that human factors play in influencing outcomes. It is therefore worth investigating the contributing human factors to improve our understanding of both human factors in reliability and the factors specific to this domain. Method: Detailed analyses were conducted of maintenance- related failures (N = 38) in a petroleum company using structured interviews with maintenance technicians. The interview structure was based on the Human Factor Investigation Tool (HFIT), which in turn was based on Rasmussen’s model of human malfunction .Results: A mean of 9.5 factors per incident was identified across the cases investigated. The three most frequent human factors contributing to the maintenance failures were found to be assumption (79% of cases), design and maintenance (71%), and communication (66%).Conclusion: HFIT proved to be a useful instrument for identifying the pattern of human factors that recurred most frequently in maintenance-related failures. Application: The high frequency of failures attributed to assumptions and communication demonstrated the importance of problem-solving abilities and organizational communication in a domain where maintenance personnel have a high degree of autonomy and a wide geographical distribution

Assessment of the Human Factors Analysis and Classification System (HFACS): Intra-rater and Inter-rater Reliability

Human error has been identified as the primary contributing cause for up to 80% of the accidents in complex, high risk systems such as aviation, oil and gas, mining and healthcare. Many models have been proposed to analyze these incidents and identify their causes, focusing on the human factor. One such safety model is the Human Factors Analysis and Classification System (HFACS), a comprehensive accident investigation and analysis tool which focuses not only on the act of the individual preceding the accident but on other contributing factors in the system as well. Since its development, HFACS has received substantial research attention; however, the literature on its reliability is limited. This study adds to past research by investigating the overall intra-rater and inter-rater reliability of HFACS in addition to the intra-rater and inter-rater reliability for each tier and category. For this investigation, 125 coders with similar HFACS training coded 95 causal factors extracted from actual incident/accident reports from several sectors. The overall intra-rater reliability was evaluated using percent agreement, Krippendorff\u27s Alpha, and Cohen\u27s Kappa, while the inter-rater was analyzed using percent agreement, Krippendorff\u27s Alpha, and Fleiss\u27 Kappa. Because of analytical limitations, only percent agreement and Krippendorff\u27s Alpha were used for the intra-rater evaluation at the individual tier and category level and Fleiss\u27 Kappa and Krippendorff\u27s Alpha, for the corresponding inter-rater evaluation. The overall intra-rater and inter-rater results for the tier level and the individual HFACS tiers achieved acceptable reliability levels with respect to all agreement coefficients. Although the overall intra-rater and inter-rater reliability results at the category level were lower than the tier level, both types of reliabilities achieved acceptable levels with inter-rater reliability being lower than intra-rater. In addition, the intra-rater and inter-rater results for the individual HFACS categories varied from achieving low reliability levels to being acceptable. Both the inter-rater and intra-rater results found that the same 5 categories among the 19 - Skill Based Error, Decision Error, Inadequate Supervision, Planned Inappropriate Operations, and Supervisory Violation - were lower than the required minimum reliability threshold. While the overall findings suggest that HFACS is reasonably reliable, the fact that there were 5 categories with low reliability levels requires further research on ways and methods to improve its reliability. One such method could be to focus on training by designing and developing a standard HFACS training program that improves its reliability, which will have the potential to enhance both the confidence in using it as an accident analysis tool and the effectiveness of the safety plans and strategies based on it

The relationship between human factors and plant maintenance reliability in a petroleum processing organisation

Despite the considerable emphasis on improving maintenance reliability in the petroleum industry by adopting an engineering approach (International Standards Organization, 2006b), production losses, ineffective maintenance, and major disasters continue to occur (Urbina, 2010; Pidgeon, 2000). Analyses of these events have indicated that a failure to consider the human factors in the design (Taylor, 2007), operation (Øien, 2001a), or maintenance (Bea, 1998) of hazardous process technologies is often an important contributor. Based on research to evaluate the influence of these human factors on organisational performance, various models (Rasmussen, 1982; Dekker 2005) and taxonomies (Reason, 1998) for analysing organisational processes at the individual-, group- and organisational-level have been developed.By using these models, the current research was designed to determine the influence of human factors on maintenance reliability in petroleum operations. Three studies were conducted in petroleum operations with the objective in the first two studies of identifying the most-frequent contributors to maintenance-related failures, and in the third study, determining if group differences between higher and lower reliability work areas could be differentiated on the basis of these human factors.In Study 1, the First Priority incident database of the target organisation was used to determine the most frequently reported human factors in maintenance-related, lost-production failures. The most-frequent factors in the incidents (N=194) were found to be Violations, Design & Maintenance, Detection, and Decision-making. These results accorded with earlier studies in the field of human factors (Hobbs & Williamson, 2003; Lawton 1998), which frequently identified human error and violations as the causes of failures. Study 2 provided a more rigorous investigation of the organisational contributors to failures through structured interviews with maintenance personnel. The results of these interviews (N=38) using the Human Factors Investigation Tool (HFIT) (Gordon, 2005) demonstrated that Assumption, Design & Maintenance, and Communication were the most frequent contributors to maintenance-related failures.Based on the predominant factors identified in Study 2, a survey of the perceptions of maintenance personnel (N=178) was conducted for Study 3. Scales measuring Problem-solving (Morgeson & Humphrey, 2006) and Vigilance (Mann, Burnett, Radford, & Ford, 1997) were used to measure the processes that provoke assumptions. Design & Maintenance items from HFIT (Gordon, 2001), and scales from Wiio’s (1978 a&b) Organisational Communication Development questionnaire (OCD/2) were used to test the factors identified in Study 2. Exploratory Factor Analysis indicated that the responses to the Design & Maintenance items loaded onto a single variable, while the Communication items loaded onto two variables, which were named Job-related feedback and Information about change.The perceptions of personnel in lower and higher reliability work areas across the target organisation were compared using these scales, with reliability level ranked according to the monthly Mean Time Between Deferments of petroleum production. Significant between-group differences were found between work areas on Design & Maintenance and Problem-solving. These results suggest that better maintainability in the design of plant is predictive of higher reliability level. In addition, greater requirements for Problem-solving were associated with lower reliability level. There were no significant effects of reliability on Vigilance or either communication measure.The quantitative data was triangulated with comments in response to an open-ended question asking about factors that help or hinder maintenance activities. Respondent’s comments indicated that Communication was not significantly associated with reliability at the group-level. The reason appeared to be that Communication was an organisation-level property of the employing company. Many comments indicated that access to information was difficult, explaining the high occurrence of assumptions reported in Study 2. In addition, although maintenance personnel generally agreed in the survey that they were vigilant in decision-making, personnel in lower reliability facilities provided a higher proportion of comments indicating that the decision-making of supervisors and management had a negative impact on their work.The results of the three studies support past research demonstrating that problem-solving skills (Tucker, 2002) and the design of socio-technical facilities (Reiman, Oedewald & Rollenhagen, 2005) have an important influence on organisational performance. The findings further extend research in the field of human factors by demonstrating a significant relationship between these two factors and group-level performance. The findings also demonstrated the importance of organisational communication, but as an organisational-level dimension that might not influence group-level measures. This research has implications for organisations that operate complex, hazardous technologies and that are attempting to improve organisational processes by utilising a human factors approach

The creation of a new minor event coding system

The present study began with an assessment of the reliability and usefulness of an existing minor event coding system in a British 'high-consequence' industry. It was discovered that despite the fact that the system produced replicable data, when tested in a reliability trial the causal inferences it was producing failed to meet the normal criteria for statistical reliability. It was therefore felt necessary to create a new model of the human factors component of action in this industry, from which a model of human factors error in the same industry could be inferred. A set of codes (to facilitate statistical analysis) were deduced from this last, which were then tested in a new reliability trial. The results from this trial were very encouraging, and after a six-month pilot study in which it demonstrated its usefulness as a trend and patterning tool, the system is now being phased in within this industry