Uses of Risk Analyses

Several different expressions of risk may be quoted in an analysis, e.g., a risk averaged ov a whole population, an age-spedfic risk, or a risk for a particularly susceptible individual or subgroup. Such an individual or subgroup might be more susceptible because of genetic predisposition, exposine to another risk factor, e.g., cigarette smoke, or other reasons. 

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Norwegian Petroleum Directorate (1990) Regulations Concerning Implementation and Use of Risk Analyses in thePpetroleum Activities withGguidelines. Norwegian Petroleum Directorate, Stavanger, Norway. 

The Chemical Process Industry (CPI) uses various quantitative and qualitative techniques to assess the reliability and risk of process equipment, process systems, and chemical manufacturing operations. These techniques identify the interactions of equipment, systems, and persons that have potentially undesirable consequences. In the case of reliability analyses, the undesirable consequences (e.g., plant shutdown, excessive downtime, or production of off-specification product) are those incidents which reduce system profitability through loss of production and increased maintenance costs. In the case of risk analyses, the primary concerns are human injuries, environmental impacts, and system damage caused by occurrence of fires, explosions, toxic material releases, and related hazards. Quantification of risk in terms of the severity of the consequences and the likelihood of occurrence provides the manager of the system with an important decisionmaking tool. By using the results of a quantitative risk analysis, we are better able to answer such questions as, Which of several candidate systems poses the least risk Are risk reduction modifications necessary and What modifications would be most effective in reducing risk ... 

Though this procedure does not allow continuos monitoring, samples can be withdrawn continuously without any risk of inducing anaemia (which may otherwise occur with the use of benchtop analysers), since no blood loss results from such paracorporeal system. 

In general, hazard identification criterion represents the deviation of one or more measured variables from specified values. This is the basis upon which a significant percentage of risk analyses are done. For a chemical process, a number of measurable variables, physical properties, and states or positions of various parts of the overall equipment, e.g., pumps, valves, and motors, can be specified for every time or phase of the process. Certain deviations from the "standard" recipe or settings can then be defined in advance as hazardous, and thus can be used for initiation of an alarm at the early stage of a runaway or upset condition. 

An overview is provided of ongoing risk assessments on halogenated phosphate ester flame retardants in Europe. On the basis of the so-called second and fourth Priority lists on Existing Chemicals (Council Regulation No793/93) three chlorinated phosphate ester flame retardants are selected. The selection is based on their hazard profile, volume and use pattern. The three substances involved are TCPP, TDCP and TCEP (Antiblaze V6 from Albemarle is also involved but, due to confidentiality, is not discussed. An outline is provided from a European point of view on topics such as methodology of risk analyses, data-gaps and worst case approach, industry involvement, downstream participation and possible impact of final report on industry. 2 refs. 

These tools can be used to evaluate the risk associated with specific chemical events. Real-world events can also then be used as a check on the analyses, enabling revision of risk analyses to include new classes of events when surprises occur. 

One of the major benefits of a semi-quantitative risk analysis is that the technique can be applied and results understood by a wide range of stakeholders in the transportation field. Unlike full quantitative approaches, these types of risk analyses do not require specialized risk management experts. Even with the ease of application, however, personnel involved in these activities need to be knowledgeable in the operations under evaluation and the use of semi-quantitative... 

As one can see from the preeeding examples, PSA s inspections were conducted using a broad range of approaches. In several cases the main focus was purely on questions of the working environment. Other inspections were more focussed on questions of safety alone. Instead of focussing on technical details, however, these inspections were also targeted at the eompany s safety management systems. A common thread was the identification of an absence of risk analyses from the company s side. 

To analyse regulatory risk, all types of risk analyses is applicable from simplified standard risk analyses, to highly detailed analyses using simulations to investigate the effects of various future scenarios on the company situation in changing regulatory frameworks -e.g. through data envelopment analysis (DEA), etc. 

Selected industry-average information from various sources can be directly used in risk analyses. Due to the large variability in actual experience from facility to facility and from company to company, extreme caution should be exercised in use of such industry-average data. Use of facility-specific data in combination with fault and event trees is recommended wherever possible. 

Government of Canada Accident Data. Various government agencies in Canada collect and report information on accidents. These provide country-wide incident information on a yearly basis but are not directly useful in risk analyses because they do not include appropriate divisor data (see above. Historical Data Analysis). These include the following ... 

The Railway Inspectorate has also been criticized for its use of risk assessment. The main criticism was an insufficient emphasis upon risk assessment procedures, for example, in its data collection and analysis and also in its approach to safety cases (HSE, 2000 t). The validity of this criticism is borne out by recent events. The Southall and Ladbroke Grove accidents demonstrate how cautiously we should approach railway statistics because of their vulnerability to major disasters. Related to this should be some caution in basing future predictions on past performance and most particularly in using this as a basis for arguing against effecting improvements. So it is important that these analyses... 

Many methods and techniques can be used to assist threat identification and risk analysis (Table 5.1.). They should be selected on the basis of the type of risk analysed. Also, the nature of risk should be taken into accoimt whether it is positive or negative. When assessing risk, information is of high value. The knowledge and expertise of operational and top executive staff are the main source of relevant information. External statistics also play an important role (the central statistical office, the national laboirr inspectorate, the police), as well as historical data on companies. The same applies to any and all regulations and requirements. 

Because the revised Chapter 2, Consequence Analysis, of the CPQRA Guidelines, 2nd Edition represents an important topic in process safety, CCPS decided to publish the material as a separate book. This will make the material on consequence analysis more readily and economically available to a broader audience, which uses incident consequence analysis evaluation tools, but does not use quantitative risk analyses. This book includes all of the material in Chapter 2, Consequence Analysis, of the CPQRA Guidelines, 2nd Edition, re-formatted as a stand alone book. All worked examples and spreadsheet problem solutions are included. All of this material will also be published in the CPQRA Guidelines, 2nd Edition. 

Since the program is still under development, these results are preliminary. That means that the results in this paper are used to demonstrate how the results that Platypus yields and how they can be used for risk-analyses of process plants. The results should not be interpreted as exact. 

An associated term is feed forward. Anticipation is the heart of the feedforward mechanism. Here, the information used as input to control the system is not obtained directly by measuring system performance but indirectly through anticipation. One typical example is when we introduce control measures on the basis of results of risk analyses. 

Probit models have been found generally useful to describe the effects of incident outcome cases on people or property for more complex risk analyses. At the other end of the sc e, the estimation of a distance within which the population would be exposed to a concentration of ERPG-2 or higher may be sufficient to describe the impact of a simple risk analysis. 

The case studies that follow have mainly come from live product development projects in industry. Whilst not all case studies require the methodology to predict an absolute capability, a common way of applying CA is by evaluating and comparing a number of design schemes and selecting the one with the most acceptable performance measure, either estimated Cp, assembly risk or failure cost. In some cases, commercial confidence precludes the inclusion of detailed drawings of the components used in the analyses. CA has been used in industry in a number of different ways. Some of these are discussed below ... 

The doeumentation of the risks for eaeh eomponent and assembly operation follows the determination of the assembly sequenee diagram, if appropriate, when the produet eonsists of more than a single eomponent. Every eritieal eomponent eharaeteristie or assembly stage is analysed through the use of the variability risks table. An assembly risk analysis will be performed during several of the ease studies presented later. 

The previous seetions have illustrated the use of the various proeess risk eharts and tables to obtain variability indiees assoeiated with the manufaeture and assembly of produets. It is important to be systematie with the applieation of the methodology and the reeording of any produet analyses, espeeially as produets often eontain many parts. It is also important to first deelare a sequenee of assembly for the individual eomponents before proeeeding with an analysis. 

The life cycle cost of a process is the net total of all expenses incurred over the entire lifetime of a process. The choice of process chemistry can dramatically affect this life cycle cost. A quantitative life cycle cost cannot be estimated with sufficient accuracy to be of practical value. There is benefit, however, in making a qualitative estimate of the life cycle costs of competing chemistries. Implicit in any estimate of life cycle cost is the estimate of risk. One alternative may seem more attractive than another until the risks associated with product liability issues, environmental concerns, and process hazards are given due consideration. Value of life concepts and cost-benefit analyses (CCPS, 1995a, pp. 23-27 and Chapter 8) are useful in predicting and comparing the life cycle costs of alternatives. 

The SPEAR framework to be described in subsequent sections is designed to be used either as a stand-alone methodology, to provide an evaluation of the human sources of risk in a plant, or in conjunction with hardware orientated analyses to provide an overall system safety assessment. The overall structure of the framework is set out in Figure 5.4. 

Titles of potential resourees were obtained by eonducting a literature search and an industry survey. Simultaneous literature searches were condueted by CCPS and SAIC. CCPS eoneentrated on obtaining CPI data resources while SAIC used a literature search conducted for the nuclear power reliability eommunity. These literature searches used in-house eompany, engineering, and public libraries and recommendations from members of the user eommunity. At the same time, a questionnaire was sent to professionals who eonduct CPQRAs. The survey requested information on the data resourees used by the companies and whether they had plant-speeific data that could be used by CCPS. Members of the CCPS Equipment Reliability Data Subcommittee were also asked to eompile lists of data resources with which they were familiar and which they had used for reliability or risk analyses. As a result, an extensive but not necessarily eomplete list of data resource titles was assembled. Any resources uncovered after the publisher s eutoff date and not reviewed have been included in Appendix D. 

Quantitative risk analyses usually produces single-number estimates. These may be used to compare one risk with another in a quantitative sense or occasionally employed in an absolute sense. One of the most popular risk policies employed by industry is tlie FAR Concept (Fatal Accident Rate). FAR represents tlie number of fatal accidents per 1,000 workers in a working lifetime (10 lir), where a working lifetime is assumed to be approximately lO lirs. An acceptable FAR (by industries standards) is 4.0. 

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