Reliability database

NPRD95, Non-electronic Parts Reliability Database, Reliability Analysis Centre, 201 Mill Street, Rome, New York, 13440, USA. 

Reliable tables that list many known surface stmetures can be found in [1]. Also, the National Institute of Standards and Teclmology (NIST) maintains databases of surface stmetures and other surface-related infonnation, which can be found at httpsov/srd/surface. htm. 

Specinfo has an additional tool for calculating NMR spectra that is based on the data sets of the compounds contained in the database. This leads to quite reliable calculated spectral parameters for the compound classes which are registered in the database. 

If users are inexperienced in searching for information, they should first consult search engines, meta-databases or portals (Table 5-6). Searchers who are familiar with databases may consult known databases (numeric databases, bibliographic databases, etc.) directly, being aware that they might miss new data sources (see Section 5.18). The reliability and quality of data are only given in peer-reviewed data sources. 

A most important task in the handling of molecular data is the evaluation of "hidden information in large chemical data sets. One of the differences between data mining techniques and conventional database queries is the generation of new data that are used subsequently to characterize molecular features in a more general way. Generally, it is not possible to hold all the potentially important information in a data set of chemical structures. Thus, the extraction of relevant information and the production of reliable secondary information are important topics. 

Reliability. There has been a significant rise in interest among pump users in the 1990s to improve equipment reflabiUty and increase mean time between failures. Quantifiable solutions to such problems are being sought (61). Statistical databases (qv) have grown, improved by continuous contributions of both pump manufacturers and users. Users have also learned to compile and interpret these data. Moreover, sophisticated instmmentation has become available. Examples are vibration analysis and pump diagnostics. 

CCPS G-7. Process Equipment Reliability Database. American Institute of Chemical Engineers, Center for Chemical Process Safety, New York. 

Frequency Phase 3 Use Branch Point Estimates to Develop a Ere-quency Estimate for the Accident Scenarios. The analysis team may choose to assign frequency values for initiating events and probability values for the branch points of the event trees without drawing fault tree models. These estimates are based on discussions with operating personnel, review of industrial equipment failure databases, and review of human reliability studies. This allows the team to provide initial estimates of scenario frequency and avoids the effort of the detailed analysis (Frequency Phase 4). In many cases, characterizing a few dominant accident scenarios in a layer of protection analysis will provide adequate frequency information. 

Hazardous Substances Data Bank (HSDB) on compact disc from the Canadian Center for Occupational Health and Safety (can buy at CCOHS web site). "The HSDB(R) (Hazardous Substances Data Bank(R)) database contains data profiles on 4,500 potentially toxic chemical substances. It is created and updated by specialists at the U.S. National Library of Medicine. Compiled from an extensive range of authoritative sources, HSDB is widely recognized as a reliable and practical source of health and safety information. Much of the data is peer reviewed. 

Reliability database (generic data, unavailability evaluation, component attributes) and... 

RDB, thej eliability database module, creates a user-defined database or retrieves data from the IAEA generic reliability database. The design facilitates RDB development for components, human actions, initiating events and the attributes of components. Component unavailabilities can be calculated from the database of reliability parameters using 10 types of predel mcd leliabiliiv models. 

The confluence of sharply rising Operations and Maintenance (O M) costs. NRC requested Individual Plant Examinations (IPEs) and increased personal computer capabilities gave rise to the R R Workstation. Its uses and maintains-current PSA models and databases for individual plants to perform O M planning and scheduling, and uses the PSA in IPE models to identify plant design, procedure and operational vulnerabilities. The Risk and Reliability Workstation Alliance was organized by EPRI to support the R R Workshop in order to achieve O M cost reduction, plant productivity and safety enhancement through risk-based, user-friendly, windowed software louls (Table 3.6 8). The Alliance, initiated in 1992, includes 25 U.S. utilities and four international partners from Spain, France, Korea, and Mexico. SAIC is the prime contractor for the R R Workstation, with participation of five other PSA vendors. 

Appendix HI, of WASH-1400 presents a database from 52 references that were used in the study. It includes raw data, notes on test and maintenance time and frequency, human-reliability estimates, aircraft-crash probabilities, frequency of initiating events, and information on common-cause failures. Using this information, it assesses the range for each failure rate. 

Drago, J. P. et al., In-Plant Reliability Database for Nuclear Plant Components Interim Data Report, The Pump Component, ORNL, December 1972. 

This technique is the longest established of all the human reliability quantification methods. It was developed by Dr. A. D. Swain in the late 1960s, originally in the context of military applications. It was subsequently developed further in the nuclear power industry. A comprehensive description of the method and the database used in its application, is contained in Swain and Guttmann (1983). Further developments are described in Swain (1987). The THERP approach is probably the most widely applied quantification technique. This is due to the fact that it provides its own database and uses methods such as event trees which are readily familiar to the engineering risk analyst. The most extensive application of THERP has been in nuclear power, but it has also been used in the military, chemical processing, transport, and other industries. 

Statistical Methods for Nonelectronic Reliability, Reliability Specifications, Special Application Methods for Reliability Prediction Part Failure Characteristics, and Reliability Demonstration Tests. Data is located in section 5.0 on Part Failure Characteristics. This section describes the results of the statistical analyses of failure data from more than 250 distinct nonelectronic parts collected from recent commercial and military projects. This data was collected in-house (from operations and maintenance reports) and from industry wide sources. Tables, alphabetized by part class/ part type, are presented for easy reference to part failure rates assuminng that the part lives are exponentially distributed (as in previous editions of this notebook, the majority of data available included total operating time, and total number of failures only). For parts for which the actual life times for each part under test were included in the database, further tables are presented which describe the results of testing the fit of the exponential and Weibull distributions. 

In a predictive and reliability maintenance program, it is extremely important to keep good historical records of key parameters. How measurement point locations and orientation to the machine s shaft were selected should be kept as part of the database. It is important that every measurement taken throughout the life of the maintenance program be acquired at exactly the same point and orientation. In addition, the compressive load, or downward force, applied to the transducer should be the same for each measurement. 

No dose-response relationship can be established for the developmental toxicity of methyl parathion from the available database. All reliable LOAEL values in rats for developmental effects for the acute- and intermediate-duration categories are recorded in Table 3-3 and plotted in Figure 3-2. 

An expert system, named "GlovES+," has been written to provide reliable selections of chemical protective clothing for a wide variety of chemicals. The system conducts "intelligent searches" which emulate a human expert s decision path in evaluating a large database from an electronic publication by Forsberg. 

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