Accident categories

ABSTRACT Four hundred and sixty seven coal gas explosion accidents that occurred in China between the years of 1950 and 2000 were investigated through statistical methods so as to review the overall situation and provide quantitative information on coal gas explosion accidents. Statistical characteristics about accident-related factors such as space, time, gas accumulation reasons, gas grade, ignition sources, accidents categories, and accident economic loss were analyzed. Some special conclusions have been achieved. For example, most gas explosion accidents were found to have concentricity on the space-time and hazard characteristics. Such results may be helpful to prevent coal gas explosion accidents. Moreover, comments were made on APS (Accident Prevention System) and safety culture. In conclusion, countermeasures were proposed in accordance with the results of statistical studies, including the change of safety check time. 

A good knowledge of statistical features of certain accidents, therefore, is the basic requirement to implement APS. In other words, major hazard identification must be performed. Statistical study on accident cases would be a powerful tool to meet this requirement. For this purpose, we collected all the related coal gas explosion accidents that analyzed in China s Coal Mine Accident and Expert Comments Set from the years of 1950-2000 (Jiefan Wang Wenjun Li 2001). The research focused on statistical features such as space, time and gas accumulation reasons, gas grade, ignition sources, accidents categories, and accident economic loss. Through this research, certain model and representativeness results will be drawn. 

Based on the above analysis, the paper give a new definition for accidents category, that is. All coal mine accidents can be divided into 4 categories, that is, accident is directly caused by human error, we called it A class accident accident is caused by human error and object misconduct, we called it B class accident accident is caused by human error and environment degradation, we called it C class accident accident is caused by human error, object misconduct, environment degradation in the same time, we called it D class accident. So, we can say, human error is the ultimate reason of all accidents, and it is the essence of coal mine accident human error model. 

Not only have many safety practitioners used the 300 29 1 ratios in their statistical presentations, but they have also misconstrued what Heinrich intended with respect to the terms major injury, minor injury, and no-injury accidents. In each edition, Heinrich gave nearly identical definitions of the accident categories to which the 300 29 1 ratios apply. This is how the definition reads in the fourth edition. 

At least one bounding accident from each of the major types has been selected unless the bounding consequences are low. Accident categories are internally initiated operational accidents (fires, explosions, spills, and criticality) natural phenomena events for the site (e.g. earthquakes, tornadoes) that could affect the facilify and externally initiated, man-made events (e.g. airplane crashes, transportation accidents, and adjacent facility events). Criticality assessments have indicated that criticality is an incredible event for isotope processing operations. Based on these evaluations, criticality has not been included in the hazard analysis and will not be included in the accident analysis. 

IMO does not require submissions of reports into serious and less serious accidents. Member States are free in their decision to submit such reports. IMO encourages submissions if important lessons can be learnt from such accident reports. However, individual member States have their own national pohcies as to when and how accident reports are submitted to IMO. In the absence of more specific guidance concerning structure, contents, and analysis of accidents, such differences are pre-programmed. This, however, is not very helpful when an in-depth review of reports about a specific accident category is undertaken. 

Engine-room and machinery space fires and explosions might represent an accident category that is less affected by organizational factors, and... 

One possible explanation for the large number of unsafe acts and preconditions for unsafe acts mentioned earher was that machinery space fires and explosions could be less likely to be affected by organizational factors. This explanation can be dismissed easily. First, similar studies with HFACS on other accident categories in other industries revealed similar problems (Thaden et al., 2004). At the same time HFACS is considered as a method that can provide appropriate results, meaning that the method itself does not lead to an overrepresentation of unsafe acts and preconditions of unsafe acts alone. 

For an offshore drilling rig, it is required that the frequency of loss of defined main safety functions on the rig shall be lower than l-10 peryearper safety function and per accident category, see Table 1. 

Table 1. Accident categories and main safety functions.

Problem definition and setting of boundaries Ship category ship systems and ftmctions, ship operation, external influences of ship, accident categories, risks associated with consequences Defining scope of assessment and system border Describing system IdentiAing relevant stakeholders Defining risk acceptance criteria V.4R, S.4R. tolerance for disturbance... 

Performing JSAs is a complex process. To better understand the importance of this analysis tool, figure 9-7 shows a completed JSA for hydraulic line replacement. Please note accident categories described in the potential hazards section. These potential hazards will aid in determining what safety measures and personal protective equipment are necessary for a given job. 

The general scope of safety analysis for HWRs, covering the accident categories considered, safety barriers challenged, and the technical disciplines involved are summarized in Table 4.2. Failures in safety support systems (such as instrument air) are addressed in the PSA. 

Accident Category Barriers Challenged Technical Discipline... 

Chapter 9 presents a new kind of comprehensive data on all injurious accidents (10-year time span) involving employees n = 13,000) of two large workplaces in Finland. This study mainly aims to clarify and assess the significance of risks among employees in different lost-time injury (LTI) accident categories, namely accidents at work, at home and during leisure lime, as well as when commuting to or from the work site. 

Figures 1, 2, 3 and Table 1 show the basic results of metal processing by year, and accident category. Figures 4, 5 and Table 2 show the basic results of municipality. The remaining tables show more detailed analysis of metal processing.

Fig. 3 Avtaage absence days per one accident caused by different accident categories of metal processing, years 2001-2013...

Data concerning accident categories during each year... 

All accident categories were compared in a paired fashion. The contingency tables (cross tabulation), tables in a matrix format that displays the frequency distribution of the variables, were the following (Tables 3,4 and 5). The analyses show that in the... 

The total risk to passengers, staff and members of the public from the 122 hazardous events modelled within the SRM with TPWS but excluding suicides, is predicted to be 203 equivalent fatalities per year. A breakdown of the total risk by accident category is shown in Table 2 ... 

Table 2 Total risk by accident category (excluding suicides)...

There are several categories of accident and each has a particuiar significance in the construction industry. Aii of these accident categories are discussed in consider-abie detaii in iater chapters. The principai categories are as foiiows ... 

In addition to the integration into a system safety performance model , it was concluded that grouping all the similar consequences together into a so called virtual consequence would be very useful if the virtual consequences correspond to accident categories collated by industry or regulatory bodies since these can be used to calibrate the model against the historical data. 

Another application of this approach is the derivation of typical accident categories for use in semi-quantitative risk analyses. We use accident data collected by the European railways over the last decade as a basis for illustrative examples. 

A statistical analysis on containership accidents is also carried out. The result indicates that containership accident categories differ from other types of ships. Like fishing vessels, there is also a lack of proper reporting of accidents/incidents for containerships. 

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