A systems approach to accident causation in mining: An application of the HFACS method

This project aimed to provide a greater understanding of the systemic factors involved in mining accidents, and to examine those organisational and supervisory failures that are predictive of sub-standard performance at operator level. A sample of 263 significant mining incidents in Australia across 2007–2008 were analysed using the Human Factors Analysis and Classification System (HFACS). Two human factors specialists independently undertook the analysis. Incidents occurred more frequently in operations concerning the use of surface mobile equipment (38%) and working at heights (21%), however injury was more frequently associated with electrical operations and vehicles and machinery. Several HFACS categories appeared frequently: skill-based errors (64%) and violations (57%), issues with the physical environment (56%), and organisational processes (65%). Focussing on the overall system, several factors were found to predict the presence of failures in other parts of the system, including planned inappropriate operations and team resource management; inadequate supervision and team resource management; and organisational climate and inadequate supervision. It is recommended that these associations deserve greater attention in future attempts to develop accident countermeasures, although other significant associations should not be ignored. In accordance with findings from previous HFACS-based analyses of aviation and medical incidents, efforts to reduce the frequency of unsafe acts or operations should be directed to a few critical HFACS categories at the higher levels: organisational climate, planned inadequate operations, and inadequate supervision. While remedial strategies are proposed it is important that future efforts evaluate the utility of the measures proposed in studies of system safety.     

Safety certification of airborne software: An empirical study

Many safety-critical aircraft functions are software-enabled. Airborne software must be audited and approved by the aerospace certification authorities prior to deployment. The auditing process is time-consuming, and its outcome is unpredictable, due to the criticality and complex nature of airborne software. To ensure that the engineering of airborne software is systematically regulated and is auditable, certification authorities mandate compliance with safety standards that detail industrial best practice. This paper reviews existing practices in software safety certification. It also explores how software safety audits are performed in the civil aerospace domain. The paper then proposes a statistical method for supporting software safety audits by collecting and analysing data about the software throughout its lifecycle. This method is then empirically evaluated through an industrial case study based on data collected from 9 aerospace projects covering 58 software releases. The results of this case study show that our proposed method can help the certification authorities and the software and safety engineers to gain confidence in the certification readiness of airborne software and predict the likely outcome of the audits. The results also highlight some confidentiality issues concerning the management and retention of sensitive data generated from safety-critical projects.     

An empirical study on the impact of critical success factors on the balanced scorecard performance in Korean green supply chain management enterprises

Rapid industrial modernisation and economic reform have been features of the Korean economy since the 1990s, and have brought with it substantial environmental problems. In response to these problems, the Korean government has been developing approaches to promote cleaner production technologies. Green supply chain management (GSCM) is emerging to be an important approach for Korean enterprises to improve performance. The purpose of this study is to examine the impact of GSCM CSFs (critical success factors) on the BSC (balanced scorecard) performance by the structural equation modelling, using empirical results from 249 enterprise respondents involved in national GSCM business in Korea. Planning and implementation was a dominant antecedent factor in this study, followed by collaboration with partners and integration of infrastructure. However, activation of support was a negative impact to the finance performance, raising the costs and burdens. It was found out that there were important implications in the implementation of GSCM.     

Demographic factors, fatigue, and driving accidents: An examination of the published literature

This article reviews the literature pertaining to the association between demographic variables (e.g., age, sex, race, socio-economic status) with fatigue, and when feasible, accident risk. It also explores their potential influence and interaction with some working arrangements, commute time, personality characteristics, and circadian chronotype. Fatigue has been implicated in a range of impairments that can have detrimental effects on individuals, and it is differentially associated with conventional demographic variables. However, several major methodological limitations prevent clear conclusions. First, there is absence of a shared definition both within and across disciplines. Second, although fatigue has been investigated using a variety of diverse designs, they have either been too weak to substantiate causality or lacked ecological validity. Third, while both subjective and objective measures have been used as dependent variables, fatigue has been more often found to be more strongly linked with the former. Fourth, with the exception of age and sex, the influence of other demographic variables is unknown, since they have not yet been concomitantly assessed. In instances when they have been assessed and included in statistical analyses, they are considered as covariates or confounders; thus, their contribution to the outcome variable is controlled for, rather than being a planned aspect of investigation. Because the interaction of demographic factors with fatigue is largely a neglected area of study, we recommend greater interdisciplinary collaborations, incorporation of multiple demographic variables as independent factors, and use of within-participant analyses. These recommendations would provide meaningful results that may be used to inform public policy and preventive strategies.     

An empirical tool to evaluate the safety of cyclists: Community based,macro-level collision prediction models using negative binomial regression

Today, North American governments are more willing to consider compact neighborhoods with increased use of sustainable transportation modes. Bicycling, one of the most effective modes for short trips with distances less than 5 km is being encouraged. However, as vulnerable road users (VRUs), cyclists are more likely to be injured when involved in collisions. In order to create a safe road environment for them, evaluating cyclists’ road safety at a macro level in a proactive way is necessary. In this paper, different generalized linear regression methods for collision prediction model (CPM) development are reviewed and previous studies on micro-level and macro-level bicycle-related CPMs are summarized. On the basis of insights gained in the exploration stage, this paper also reports on efforts to develop negative binomial models for bicycle–auto collisions at a community-based, macro-level. Data came from the Central Okanagan Regional District (CORD), of British Columbia, Canada. The model results revealed two types of statistical associations between collisions and each explanatory variable: (1) An increase in bicycle–auto collisions is associated with an increase in total lane kilometers (TLKM), bicycle lane kilometers (BLKM), bus stops (BS), traffic signals (SIG), intersection density (INTD), and arterial–local intersection percentage (IALP). (2) A decrease in bicycle collisions was found to be associated with an increase in the number of drive commuters (DRIVE), and in the percentage of drive commuters (DRP). These results support our hypothesis that in North America, with its current low levels of bicycle use (<4%), we can initially expect to see an increase in bicycle collisions as cycle mode share increases. However, as bicycle mode share increases beyond some unknown ‘critical’ level, our hypothesis also predicts a net safety improvement. To test this hypothesis and to further explore the statistical relationships between bicycle mode split and overall road safety, future research needs to pursue further development and application of community-based, macro-level CPMs.     

The systematic integration of human factors into safety analyses: An integrated engineering approach

The performance of the human reliability analysis (HRA) and integration of its outcomes into quantitative risk assessment schemes remains quite a difficult and complex task to perform. Even worse is the assessment of organisational reliability assessment. The reasons of this difficulty mainly lay on the absence of a generically accepted paradigm that enables engineers to include systematically human and organisational factors (H&OF) into the analysis. Broadly speaking, engineering approaches very often account for error of omission forgetting the errors of commission (EOC), and, on top of that, they do not make any macro distinction between pre- and post-initiating human failures. This paper offers a paradigm on how to integrate H&OF into safety analysis by means of the recursive operability analysis (ROA), which has been adapted to accommodate H&OF, and renamed integrated recursive operability analysis (IROA). By means of a practical example, the method will illustrate how to account for H&OF in a systematic and consistent manner using an engineering approach. The paper will even provide a paradigm for the construction of integrated fault trees consistent with the IROA framework.     

A study on the critical factors of ISO 9001:2000 and organizational performance of Indian manufacturing firms

This study explores the critical factors of ISO 9001:2000 and investigates the effect of ISO certification on organizational performance, as perceived by the management. In order to gain more insight into the investigation, the study also analyses the relationship between the firm attributes and the critical factors, as well as the relationship between firm attributes and the indicators of organizational performance.     

The impact of physiographic factors upon the probability of slides occurrence: a case study from the Kaoping River Basin,Taiwan

This study has investigated the influence of physiographic factors upon the probability of slide occurrence in the Kaoping River Basin. According to previous literature, statistical tests, and physical mechanisms, three physiographic factors (slope steepness, the dip slope ratio, and the time-dependent landslide ratio) were significantly related to slide occurrence. These were combined with hydrological factors (cumulative rainfall) to establish an assessment model for estimating the probability of slide occurrence using logistic regression. The model’s overall accuracy in the training and validation stages was about 81%. Overall, 20 randomly selected historical rainfall events were employed for verification, including 10 events each with and without slide occurrence. The results showed that the model accuracy was approximately 80%, if the probability threshold P_sh is set to be 0.5.

This assessment model can assist in prediction of slide occurrence and the proposed subsequent engineering measures or vegetation restoration is often able to reduce the landslide ratio and the probability of slide occurrence. After landform changes, the model’s physiographic factors can be updated to adjust the rainfall threshold for slide occurrence. Given an appropriate cumulative rainfall and an acceptable risk of slide occurrence, the model can identify priority regions for slide prevention.