Accidents control charts

Control Charts When sampling events, there is random variation in events in sampling periods. For example, the number of accidents for a company will vary each month. A problem is knowing whether the variation is strictly random or whether some program or control has produced desired results. Control charts help answer that question. 

Figure 37-6 illustrates the idea of a control chart. An analyst plots the number of accidents per month for a company over a two-year, twenty-four-month period. Horizontal lines represent upper and lower bounds compared to the mean number of accidents per month for the two years. There is an upper control limit and a lower control limit. The limits represent 95% (two standard deviations from the... 

The accurate use of control charts depends on the distribution of data being similar to the statistical normal distribution. Statistical assumptions are not valid unless there is a sufficient sample size (accident cases per month) and there are factors that cause a sudden change in data. To assure a control chart s vahdity, there should be about 60 sampling periods (typically months). 

Attribute charts are used when the data being measured meet certain conditions or attributes. Attributes are involved when the safety measures are categorical (Griffin 2000,434). Examples of categorical data include the departments in which accidents are occurring, the job classification of the injured employee, and the type of injury sustained. The type of attribute control chart used depends on the data format of the specific attribute measured. The attribute charts covered in this chapter are... 

Data were collected for a 12-month period from accident reports. The safety manager wished to construct a control chart depicting the frequency of back injuries reported each month. The following table was constructed ... 

Once the plan has been formulated, it becomes necessary to establish procedures in a clear and concise manner. Such procedures should include a general policy on security, an organisation chart indicating levels of responsibility for security, employment practices for the hiring of security staff, including detailed job descriptions and the duties and responsibilities of such staff, such as arrest and search powers. Detailed systems should also be developed to ensure the security of premises, protection of property, control of persormel and vehicles, including traffic control, security liaison with the fire control function, accident control and first aid to the injured. 

HGURE 4.1 Univeisal Copper and Metals Mine accident frequency rate control chart... 

The square root of 2.0 is 1.40. Two times this is 2.8. Therefore 2.8 plus 2.1 (the base rate) is 4.9 and 2.0 minus 2.8 is a negative 0.8. The upper control limit is 4.9 and the lower control limit is 0, since it is impossible to have a negative accident rate. Figure 4.1 iUustrates what this control chart would look like. The points have been added to iUustrate the current year s monthly frequency rates. 

This is a very basic method for calculating upper and lower control limits. Other methods can also be used to calculate these hmits. To ensure that the statistical control charts are as reliable as practical, keep several guidelines in mind. First, use accident rates that have as many sets of data as possible. For example, an aU injury/iUness frequency rate works better than a lost time frequency rate. Second, try to use at least twenty sets of data in calculating the base rate or average. In our example we only used five data points for practical purposes. However, they represented 60 individual monthly frequency rates. 

Interpreting statistical control charts properly helps to reduce the over-reaction to accident rates that are not statistically valid. Figure 4.2 lists several guideUnes to help you interpret the data provided by statistical control charts. 

Miner s safety performance recognition, circa 1920s 20 The systems model of health and safety management 24 The size of mobile mine equipment continues to increase 27 Simple model of outcomes dependent on culture and systems 32 Statistical control chart with incident rate variation 33 Universal Copper and Metals Mine accident frequency rate control chart 55... 

In most of the plants we have studied, the safety process is stable. Although accident rates vary from month to month, there is usually no statistical trend. Trends, or their absence, must be determined through the use of control charts, which we will describe further in Chapter 4. 

Close inspection of the control chart can reveal shifts in the process of accident prevention and can also reveal manipulation of the recording process. 

Example An aluminium plant has 2000 employees and each employee works 1800 hours a year. During the last ten years, an average of 35 losttime accidents per year was registered. For a control chart with a periodicity of one year, we calculate the following ... 

Start establishing the control chart only when at least 100 accidents have been registered. Do not use data of more than five years of age. 

Use the control chart on a routine basis to evaluate the SHE performance for new periods. Keep the control limits updated with accident and exposure data until the period before the last period. Avoid using data for more than five years back in time, or from earlier periods that for some specific reason are not representative of the current situation. 

We will regard five accidents per period as a minimum number in order to produce meaningful control charts. Figure 17.4 shows the minimum period length for a given number of employees that follows from this figure. 

Management also wants to follow-up on the developments in the risk of major accidents as well. A new high-potential incident rate is introduced. It is calculated as the number of such incidents per quarter year and is displayed in a control chart. Incidents involving gas leakage, overflow of tanks, fires and dropped objects inside process areas are considered as potentially serious. Figure 20.1 shows a display of the results for the first ten quarters. 

The periodic summaries on accident statistics are distributed quarterly. They provide feedback on SHE performance to line management and the SHE organisation. Ymer s quarterly report contains control charts on the accumulated LTl-rate and the TRI-rate since the start of the year, distribution of accidents by accident type, injured part of body, etc. An edited summary of each accident case is also presented. The database helps in the production of standard reports and makes it possible to tailor these to the needs of each department. 

These conditions, known as dendritics, may become hazards and could result in an accident or occupational disease. Continuous safety sampling methodology performs a random sampling for the occurrence of these dendritics. The collected data are then used to generate a control chart. Based on the pattern of the control chart, a system under control is not disturbed whereas a system out of control is investigated for potential conditions becoming hazardous. Appropriate steps are then taken to eliminate or control these conditions to maintain a desired safe system. 

During the two decades since Bill Johnson introduced the original MORT chart, several modifications have been made by the Systems Safety Development Center. Prior to 1983, the first-tier events under accident on the specific control factors side of the chart were as depicted in Figure 18-7. 

Red—event or factor less than adequate (LTA). Any event, factor, or block of events or factors, that, after thorough examination, has been determined to have less than adequate controls or barriers to prevent a transfer of hazardous energy is colored red on the MORT chart. Caution in the use of this color is warranted since any system elements labeled LTA must be well documented and a recommended course of action provided in the hnal accident investigation report to management. 

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