Equipment Failure Rate Data

To properly use failure rate data, the engineer or risk analyst must have an understanding of failure rates, their origin and limitations. This chapter discusses the types and source of failure rate data, the failure model used in computations, the confidence, tolerance and uncertainties in the development of failure rates and taxonomies which can store the data and influence their derivation. 

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Once the fault tree is constructed, quantitative failure rate and probability data must be obtained for all basic causes. A number of equipment failure rate databases are available for general use. However, specific equipment failure rate data is generally lacking and. 

This chapter introduces the need for process equipment failure rate data, defines the scope and organization of this book and the data it contains, and explains how to the use the book. 

Appendix A—CCPS Taxonomy The full CCPS Taxonomy for process equipment failure rate data. 

Equipment failure rate data points carry varying degrees of uncertainty expressed by two measures, confidence and tolerance. Confidence, the statistical measurement of uncertainty, expresses how well the experimentally measured parameter represents the actual parameter. Confidence in the data increases as the sample size is increased. 

This chapter provides summaries of seleeted data resourees available to the CPQRA praetitioner. These resourees are summarized in a eonsistent format that allows them to be easily reviewed and eompared. Those resources whieh are available to CCPS and contain equipment failure rate data of suffieient quality are used for the data tables in Seetion 5.5. 

Subcommittee members selected those resources for further study whieh had titles suggesting that the resouree might contain equipment failure rate data. Copies of these resourees were then obtained and read. 

This chapter contains tables of generic equipment failure rate data for some of the CPI equipment types listed in Appendix A, the CCPS Taxonomy, or in Appendix B, the Equipment Index. Section 5.1 on data selection explains how data were selected from resources and lists which resources in Chapter 4 were used to provide data. 

It is important to distinguish the types of time-related and demand-related equipment failure rate data that can be found and used in afire risk assessment. Basically, four types of data and corresponding data sources provide both time-related and demand-related failure data as shown in Table 6-3 and discussed in the following sections. 

Increasing attention is being given to developing methods to predict failure rate data for process equipment and systems. Such methods are beginning to appear in published literature. These methods include correlations, factored estimation procedures, and analogies to predict equipment failure rates. They are desirable because they offer efficient means of providing equipment failure rate data for risk assessments, and they can be conveniently incorporated into computer software. 

Where the expert opinion equipment failure rate data is derived using a group of individuals with experience with similar equipment, operating under similar conditions, it may be more accurate than generic data. 

Table 3 lists typical failure rate data for a variety of types of process equipment. Large variations between these numbers and specific equipment can be expected. However, this table demonstrates a very fundamental principle the more compHcated the device, the higher the failure rate. Thus switches and thermocouples have low failure rates gas—Hquid chromatographs have high failure rates. 

The numbers computed usiag this approach are only as good as the failure rate data for the specific equipment. Frequendy, failure rate data are difficult to acquire. For this case, the numbers computed only have relative value, that is, they are useful for determining which configuration shows iacreased reUabiUty. 

The nuclear equipment failure rate database has not changed markedly since the RSS and chemical process data contains information for non-chemical process equipment in a more benign environment. Uncertainty in the database results from the statistical sample, heterogeneity, incompleteness, and unrepresentative environment, operation, and maintenance. Some PSA.s use extensive studies of plant-specific data to augment the generic database by Bayesian methods and others do not. No standard guidance is available for when to use which and the improvement in accuracy that is achieved thereby. Improvements in the database and in the treatment of data requires, uhstaiui.il indu.sinal support but it is expensive. 

Chapter 5—CCPS Generic Failure Rate Data Base Contains tables of generic process equipment reliability data that are structured by the CCPS Taxonomy. The data are extracted from data resources in Chapter 4. The chapter includes a discussion of the selection, treatment, and presentation of the data in the Tables. 

It is recommended as a first step that the user of the book review the entire volume to become familiar with the various aspects of equipment failure rates that are presented. This can provide a better understanding of the derivation, value, and limitations of generic data. Beyond this, the volume is structured to assist the reader in one or more of three basic tasks. These tasks are ... 

Both of the sources above contain tWo types of failure rate data used in CPQRAs time-related failure rates and demand-related failure rates. Time-related failure rates, presented as failures per 10 hours, are for equipment that is normally functioning, for example, a running pump, or a temperature transmitter. Data are collected to reflect the number of equipment failures per operating hour or per calendar hour. 

Tolerance uncertainty arises from the physical and the environmental differences among members of differing equipment samples when failure rate data are aggregated to produce a final generic data set. Increasing the number of sources used to obtain the final data set will most likely increase the tolerance uncertainty. 

However, the data that are contributed to a generic failure rate data base are rarely for identical equipment and may represent many different circumstances. Generic data must be chosen carefully because aggregating generic and plant-specific data may not improve the statistical uncertainty associated with the final data point, owing to change in tolerance. 

When using failure rate data for a CPQRA, the ideal situation is to have valid historical data from the identical equipment in the same application. In most cases, plant-specific data are unavailable or may carry a level of confidence that is too low to allow those data to be used without corroborating data. Risk analysts often overcome these problems by using generic failure rate data as surrogates for or supplements to plant-specific data. Because of the uncertainties inherent in risk analysis methodology, generic failure rate data are frequently adequate to identify the major risk contributors in a process or plant. 

The Database contains failure rate data for most major equipment Items that are found throughout the process industhes... 

The data base contains failure rate data plus some failure mode information for process equipment - pumps, compressors, gas turbines, valves, vessels, heat exchangers etc. 

SAIC provided much of the data used in this book from its proprietary files of previously analyzed and selected information. Since these data were primarily from the nuclear power industry, a literature search and industry survey described in Chapter 4 were conducted to locate other sources of data specific to the process equipment types in the CCPS Taxonomy. Candidate data resources identified through this effort were reviewed, and the appropriate ones were selected. Applicable failure rate data were extracted from them for the CCPS Generic Failure Rate Data Base. The resources that provided failure information are listed in Table 5.1 with data reference numbers used in the data tables to show where the data originated. 

As explained in Section 3.3, failure rate data for a piece of equipment or system can be located by the taxonomy number for the equipment. The number can be found by using the CCPS Taxonomy, Appendix A, or the alphabetized hardware list in the Equipment Index, Appendix B. Table 5.2 shows whether the CCPS data base contains failure rate data for that numbered data cell or for an appropriate higher-level cell. Alternatively, the user may look directly for the desired taxonomy cell in the data tables. 

The pages in this section present tables of generic failure rate data compiled for process equipment and organized by the CCPS Taxonomy. 

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