Industry databases

One method of enhancing safety knowledge is to learn from the experience of others. (See Chapter 15.) A sampling of industry databases that contain information about incidents is presented below in Table 11-3. An internet search can help the user in locating and evaluating these and other databases. 

Industry databases containing details of process safety incidents are addressed in more detail in Chapter 11. 

Three flow sheets with consistent assumptions, and using commercially available equipment where possible, were developed. The flow sheets and mass and energy balances were used to generate sized equipment lists. Estimated costs for unit operations are based on industry databases for materials and labour, and on the estimates of technical experts from associated research and development programmes. Installation costs, including labour and field bulk materials, were estimated on a subsystem basis. 

Water Industry Database, Utility Profiles, Report by the American Water Works Association, AWWA, Denver, CO, 1992. 

Step 1 - Complete the LOPA without taking any credit for the SIF. First, determine the initiating events from HAZOP/What-if/EMEA study. Next, evaluate frequencies of all initiating events from company database and industry experience. Then, determine the probability that each IPL will function successfully from an industrial database. PFO yg of some typical protection layers are (CCPS, 2000) BPCS control loop = 0.10 Operator s response to alarm = 0.10 Rehef safety valve = 0.01 to 0.001 and vessel failure probability at maximum design pressure = 10 ". Finally, compare the calculated risk with the tolerable risk target... 

In spite of their limitations, industry databases can be extremely valuable especially when no other data source exists. If the failure rate data is too high, the result will be a higher PFH/PFDavg. If this occurs and too much safety integrity is designed into a safety instrumented function, that is tolerable. 

Many companies have an internal expert who has studied these sources, as well as their own internal failure records, and maintains the company failure rate database. Some use failure data compilations found on the Internet. While the data in industry databases is not product specific or application specific, it does provide useful failure rate information for specific industries (nuclear, offshore, etc.) and a comparison of the data provides information about failure rates versus stress factors. 

In spite of their limitations industry databases have served an important purpose. Using a combination of industry databases, company data and experience, the data needed for our safety lifecycle can be estimated. Fortunately other data sources are available also. 

It is clear that some are uncomfortable with the level of accuracy in the failure data estimated from industry databases and experience. Questions about failure rate versus stress conditions in particular applications come up. Questions about specific products are constantly being asked especially when one must attempt to pick a better product to achieve higher safety. 

Fortunately, several instrumentation manufacturers are providing detailed analysis of their products to determine a more accurate set of numbers useful for safety verification purposes. A Failure Modes Effects and Diagnostic Analysis (FMEDA) will provide specific failure rates for each failure mode of an instrumentation product. The percentage of failures that are safe versus dangerous is clear and relatively precise for each specific product. The diagnostic ability of the instrument is precisely measured. Overall, the numbers from such an analysis are indeed product specific and provide a much higher level of accuracy when compared to industry database numbers and experience based estimates. 

Failure rates obtained from industry databases, manufacturer FMEDA analysis, manufacturer field failure studies, company failure records or other sources can be compared. The results will be different as described above. 

Generally, less specific data turns out to be more conservative and that is appropriate for safety verification purposes following the rule that "the less one knows, the more conservative one must be." Remember that industry databases may include systematic failures, multiple technology classes, wear out failures and possible multiple reports per failure. These issues naturally cause the numbers from such sources to be high. 

Table 8-1 shows a comparison of data for a pressure transmitter. The failure rate numbers from the industry database sources are significantly higher than the FMEDA reports. 

Although product specific FMEDA reports offer superior data sources when compared to industry databases, they still do not account for application specific stress conditions that may affect actual failure rates. Ideally in the future manufacturers will be able to provide not only point estimates of failure rates but perhaps even equations with application specific variables to more precisely calculate the needed numbers. That wiU happen if there is demand and the needed data is collected. 

List some of the limitations in using industry database data for SIL verification calculations. 

If considering the application of the subsea gas compressor in the case example, industry databases, i.e. OREDA will provide an expected mean time to failure (MTTF) which is typically less than one year for topside gas compressors. When evaluating this data in more detail, it is also possible to identify the main contributors to failures of the gas compressors the table below provides a simple example ... 

Several industry databases of surveillance test data have been maintained over the years. For example, during the 1990s EPRI maintained the Power Reactor Embrittlement Program (PREP) database (EPRI, 1996), which was developed under joint EPRI and CRIEPI (Central Research Institute of the Electric Power Industry) sponsorship. Later, EPRI sponsored the RPVDATA database program (EPRI, 2000) as a successor to PREP. The industry databases have faced greater sustainability issues than the NRC databases because of limited funding. 

At the heart of any EMR system are data sets or databases that organize, store, and secure the vast amount of medical records. A data model is the framework in which these records are organized. The most popular industrial database systems are relational, and the prominent data models are entity-relationship diagrams or relational models. However, to be... 

Industry databases such as the Offshore Reliability Data Handbook (SINTEF 2009) or The Update of Loss of Containment Data for Offshore Pipelines. 

EPRI has develop an industry database. The programme objective was (a) to combine all available materials data into an integrated, common material database, (b) to develop special data search and retrieval capabilities for ease of use, (c) to develop tools for assisting utilities in resolving vessel material concerns, and (d) to establish a convenient mechanism to incorporate new information into the database for use in addressing future integrity issues. 

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