Plant failure rates

Development of an Improved Liquified Natural Gas Plant Failure Rate Data Base... 

Johnson, D. W., and J. R. Welker. 1981. Development of an Improved LNG Plant Failure Rate Data Base, GRI-80/0093. Final Report, Gas Research Institute, September. 

Idaho Chemical Processing Plant, Failure Rate Database ICPP 1995 ... 

The failure rate changes over the lifetime of a population of devices. An example of a failure-rate vs product-life curve is shown in Figure 9 where only three basic causes of failure are present. The quaUty-, stress-, and wearout-related failure rates sum to produce the overall failure rate over product life. The initial decreasing failure rate is termed infant mortaUty and is due to the early failure of substandard products. Latent material defects, poor assembly methods, and poor quaUty control can contribute to an initial high failure rate. A short period of in-plant product testing, termed bum-in, is used by manufacturers to eliminate these early failures from the consumer market. 

For many years the usual procedure in plant design was to identify the hazards, by one of the systematic techniques described later or by waiting until an accident occurred, and then add on protec tive equipment to control future accidents or protect people from their consequences. This protective equipment is often complex and expensive and requires regular testing and maintenance. It often interferes with the smooth operation of the plant and is sometimes bypassed. Gradually the industry came to resize that, whenever possible, one should design user-friendly plants which can withstand human error and equipment failure without serious effects on safety (and output and emciency). When we handle flammable, explosive, toxic, or corrosive materials we can tolerate only very low failure rates, of people and equipment—rates which it may be impossible or impracticable to achieve consistently for long periods of time. 

In some instances, plant-specific information relating to frequencies of subevents (e.g., a release from a relief device) can be compared against results derived from the quantitative fault tree analysis, starting with basic component failure rate data. 

In Section 2.5.4, we found the availability of a repairable emergency generator (EG) by Markov methods. If a plant requires that two identical, independent EGs must both work for time T for success. What is the probability of this Assume the failure rates are A., A., and the repair rates are p, p-,. 

Experience shows that the failure rate of one diesels is A-j = 8.7F-5/hr, and they are tested 1 1 days (720 hours). A study of related plant ows that common mode contributes 10% 1 One 1 [failed ... 

I l7.s-1982 Commercial Power Safety equipment failure rate calculation from plant reports - NPRD fi dear... 

Pump, valve, diesel failure rates from plant reports - IPRD, EPRl Comprehensive componeni collection... 

Commonly, there are components that are not in any database of failure rates, or the data do not apply for the environment or test and maintenance at your plant. In addition, site specific data may be needed for regulatory purposes or for making the plant run safer and better. For both cases there is a need for calculating failure rate data from incident data, and the mechanics of database preparation and processing. 

Human error contributed to about 50% of the accident sequences m the RSS but none of the human error data came from the nuclear power industry. Furthermore, very high failure rates 0.5 to 0.1/action) were predicted but are not supported by the plant... 

Table 4.1-5 shows in these records, there has been 3 control rod drive failures. Assume 100 plants in the U.S. with an average of 30 control rods/plant and 10.7 years of experience in this database. Estimate, the mode, 90% and 10% confidence limits for the failure rate. 

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. 

The accident sequence frequencies are quantified by linking the system fault tree models together as indicated by the event trees for the accident sequence and quantified with plant-specific data to estimate initiator frequencies and component/human failure rates. The SETS code solves the fault trees for their minimal cutsets the TEMAC code quantitatively evaluates ihe cm sols and provides best estimates of component/event probabilities and frequencies. 

Chapter 2—Origin, Use, and Limitations of Failure Rate Data Explains the meaning of generic and plant-specific data, the difference between time-related and demand-... 

Chapter 7—Failure Rate Data Transfer Provides a form to facilitate the transfer of plant-specific data to the CCPS Data Base or to combine it with other generic data. 

When plant-specific data are required. Chapter 6 discusses how to collect and treat the data so that the resulting failure rates can be used in a CPQRA or be combined with the data in the CCPS Generic Failure Rate Data Base. Chapter 7 provides a form that can be used to transfer these data to CCPS s Generic Failure Rate Data Base. 

Failure rates are computed by dividing the total number of failures for the equipment population under study by the equipment s total exposure hours (for time-related rates) or by the total demands upon the equipment (for demand-related rates). In plant operations, there are a large number of unmeasured and varying influences on both numerator and denominator throughout the study period or during data processing. Accordingly, a statistical approach is necessary to develop failure rates that represent the true values. 

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. 

Number and type of record The number of data points or tables of data presented in the resource or the number of events the data set reflects where available, the form in which the data are presented, such as failure rates or availability data, confidence intervals or error factors the raw data source used, sueh as surveys, plant records, tests, or judgment. 

Failure rate questionnaires were sent to 35 companies which operate LNG base loading or satellite facilities. These operators had previously expressed an interest in participating in the study. Twenty-five companies returned questionnaires which covered failures at 27 separate LNG facilities. Approximately 1,626,000 hours of plant operating time were represented by the returned questionnaires. 

Technica has compiled computerized failure rate data from the public domain that can developed into a database. Each database can be customized by adding client plant-specific data and updated easily in its electronic form. CLEF is also software compatible with the IRRAS fault tree package put out by EG4G. Failure rate libraries can be generated and imported from CLEF to the IRRAS program. 

Some Data on the Reliability of Instruments in the Chemical Plant Environment Chemical Process 40 instrument failure rates Maintenance records on 9,500 instruments 45. 

In this study detailed fault trees with probability and failure rate calculations were generated for the events (1) Fatality due to Explosion, Fire, Toxic Release or Asphyxiation at the Process Development Unit (PDU) Coal Gasification Process and (2) Loss of Availability of the PDU. The fault trees for the PDU were synthesized by Design Sciences, Inc., and then subjected to multiple reviews by Combustion Engineering. The steps involved in hazard identification and evaluation, fault tree generation, probability assessment, and design alteration are presented in the main body of this report. The fault trees, cut sets, failure rate data and unavailability calculations are included as attachments to this report. Although both safety and reliability trees have been constructed for the PDU, the verification and analysis of these trees were not completed as a result of the curtailment of the demonstration plant project. Certain items not completed for the PDU risk and reliability assessment are listed. 

Determination of Reliability Characteristic Factors in the Nuclear Power Plant Biblis B, Gesellschaft fur Reaktorsicherheit mbH Nuclear Failure rates with upper and lower bounds and maintenance data for 17,000 components from 37 safety systems Data for pumps, valves, and electrical positioning devices, electric motors and drives from an operating power plant 66. 

SAIC Data Base Nudear Plant maintenance and repair records by system and component type selected basic event failure rates and unavailability Data mainly for pumps, valves, diesels, batteries, chargers, and heat exchangers 76. 

The German Gesellschaft fur Reaktorsicherheit (GRS) has a private arrangement with Rheinische Westalisches Elekrizitatswerke (RWE) to compile reliability data from an operating power plant, Biblis B. The data base contains failure rate, maintenance, and operational event data. External event data (floods, earthquake, fire, etc.) are compiled through a separate utility-sponsored data base. The data base provides information on repair and maintenance, and equipment performance. 

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