J Carrillo-Castrillo

Causation of Severe and Fatal Accidents in the Manufacturing Sector

The main purpose of this paper is to identify the most frequent causes of accidents in the manufacturing sector in Andalusia, Spain, to help safety practitioners in the task of prioritizing preventive actions. Official accident investigation reports are analyzed. A causation pattern is identified with the proportion of causes of each of the different possible groups of causes. We found evidence of a differential causation between slight and non-slight accidents. We have also found significant differences in accident causation depending on the mechanism of the accident. These results can be used to prioritize preventive actions to combat the most likely causes of each accident mechanism. We have also done research on the associations of certain latent causes with specific active (immediate) causes. These relationships show how organizational and safety management can contribute to the prevention of active failures.

Risk assessment of maintenance operations: the analysis of performing task and accident mechanism

Maintenance operations cover a great number of occupations. Most small and medium-sized enterprises lack the appropriate information to conduct risk assessments of maintenance operations. The objective of this research is to provide a method based on the concepts of task and accident mechanisms for an initial risk assessment by taking into consideration the prevalence and severity of the maintenance accidents reported. Data were gathered from 11,190 reported accidents in maintenance operations in the manufacturing sector of Andalusia from 2003 to 2012. By using a semi-quantitative methodology, likelihood and severity were evaluated based on the actual distribution of accident mechanisms in each of the tasks. Accident mechanisms and tasks were identified by using those variables included in the European Statistics of Accidents at Work methodology. As main results, the estimated risk of the most frequent accident mechanisms identified for each of the analysed tasks is low and the only accident mechanisms with medium risk are accidents when lifting or pushing with physical stress on the musculoskeletal system in tasks involving carrying, and impacts against objects after slipping or stumbling for tasks involving movements. The prioritisation of public preventive actions for the accident mechanisms with a higher estimated risk is highly recommended.

Construction accidents: identification of the main associations between causes, mechanisms and stages of the construction process

Objective. To identify the most frequent causes of accidents in the construction sector in order to help safety practitioners in the task of prioritizing preventive actions depending on the stage of construction. Methods. Official accident investigation reports are analysed. A causation pattern is identified with the proportion of causes in each of the different possible groups of causes. Results. Significant associations of the types of causes with accident mechanisms and construction stages have been identified. Conclusions. Significant differences have been found in accident causation depending on the mechanism of the accident and the construction stage ongoing. These results should be used to prioritize preventive actions to combat the most likely causes for each accident mechanism and construction stage.

Framework for the use of official occupational accident investigations as a learning tool: analysis of a public programme for accident investigation in the manufacturing sector

Accident investigation is a useful tool for safety science. The use of accident investigation as a learning tool at the macro level necessitates specific requirements quite different from the usual needs at the company level. A proper codification system and information on the accident scenarios are needed to let safety practitioners identify if the information is useful for the organisations they are assessing. In the same way epidemiological tools have been applied to the analysis of circumstances of accidents, the epidemiological statistical tools can help to draw conclusions for a set of investigated accidents. Our case study includes the description of the dataset used in a programme for learning from accidents in Andalusia: ‘Pudo haberse evitado’ (this can be translated as ‘This could have been prevented’). This paper covers the requisites for a macro-level learning programme and the possibilities of analysis of the dataset in a ‘research to practice approach’.

Prevention of falls to a lower level: Evaluation of an occupational health and safety intervention via subsidies for the replacement of scaffolding

The objective of this study is to evaluate the impact of a subsidy policy for construction companies in Andalusia (Spain), which enables them to acquire new scaffolds. The rate of falls from scaffolds within the Andalusian construction sector in the period 2009–2011 was analysed. A randomised controlled trial was not possible as the subsidy was granted according to a public and competitive call. A quasi-experimental design based on an intervention group (subsidised companies) and a control group was chosen. Companies in the control group were selected from the social security census of companies in order to avoid selection bias. The subsidy policy has led to an overall 71% decrease in the rate of accident involving falls to a lower level in the companies that received grants in the period 2009–2011. The confidence interval for the comparison for the before–after difference in rates between the intervention group and the control group is found significant (confidence 95%, p = 0.05). The improvement of scaffolds was effective in reducing rates of accident with falls to a lower level. This intervention should be a priority in public policies. The process of standardisation of equipment with high accident risk should be developed further.

Neural Network Application for Risk Factors Estimation in Manufacturing Accidents

In occupational safety, when a neural network is trained, it is possible to predict the outcome given a combination of risk factors. Risk assessment is probably the most important issue in occupational safety. Risk assessment facilitates the design and prioritization of effective prevention measures. Neural network were applied for predicting the severity of accidents, which is important to assess risks. Data sets were obtained from the official accident notifications in the manufacturing sector of Andalusia in 2011. The results confirm that neural networks are useful in risk factor estimation. Association analysis was used to identify the most important risk factors within the predicting variables. Diagnostic array analyses show that for preventive purposes it is better to use a reduced data set with a case-control approach in order to improve the specificity and the sensitivity.

Effectiveness of Construction Safety Programme Elements

Occupational health and safety levels in construction continue to be an international cause of concern because of high accident rates in the sector. In order to reduce negative incident rates in the industry, construction companies implement safety programmes that include different elements. In current research, an expert panel of 8 members was selected with the aim to quantify the effectiveness of the essential safety program elements using staticized groups methodology. Results showed that effectiveness of Job hazard analyses and communication, and upper management support as safety program elements, obtained the best scores by the experts. These results can be used to prioritize the most effective safety elements for construction projects in order to control construction safety risk.