Reliability system

For a leak-detection system that features fixed-point detectors to be reliable, it must be monitored and calibrated frequently. As discussed in Section 

catalytic detectors for flammable gases can either bum out or be poisoned by other materials in the atmosphere. When burnout or poisoning occurs, the detector still behaves as if it is working properly. Therefore, the only way to detect failure is by frequent calibration checks. A similar situation exists for solid-state and electrochemical detectors. For these devices, manufacturers recommend that calibration checks be made at frequent intervals. 

Calibration checks also serve to minimize nuisance alarms and false trips of postrelease mitigation systems. This ensures that the personnel monitoring the system will have confidence in it and will respond aggressively when an alarm is received. If there are many nuisance alarms or false trips of postrelease mitigation systems, it is highly likely that an alarm will be ignored and the system turned off, or the response time will be slow because someone will go to the location to determine whether there is really 

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R. BiUinton, Power System Reliability Evaluation, Gordon and Breach Science Publishers, New York, 1970. 

R. BiUinton, R. J. Ringlee, and A. J. Wood, Power-System Reliability Calculations, The MIT Press, Cambridge, Mass., 1973. 

H. Ascher and H. Eeingold, Repairable Systems Reliability, Lecture Notes in Statistics, No. 7, Marcel Dekker, Inc., New York, 1984. 

The Systems Reliability Service Data Banks was set up in the 1960s to provide engineers with reliability information for complex systems. This comprehensive data bank contains information on most component types in a variety of uses in different industries. 

Systems Reliability Service Data Bank, National Centre of Systems Reliability, System Reliability Service, UKAEA, Culcheth, England. 

A. Amendola, Uncertainties in Systems Reliability Modeling Insight Gained Through European Benchmark Exercises, Nuclear Engineering and Design, Vol. 93, Elsevier Science Publishers, Amsterdam, Elolland, 1986, pp. 215-225. 

The reliability of a product is the measure of its ability to perform its intended function without failure for a specified time in a particular environment. Reliability engineering has developed into two principal areas part and system. Part reliability is concerned with the failure characteristics of the individual part to make inferences about the part population. This area is the focus of Chapter 4 of the book and dominates reliability analysis. System reliability is concerned with the failure characteristics of a group of typically different parts assembled as a system (Sadlon, 1993). 

Most produets have a number of eomponents, subassemblies and assemblies whieh all must funetion in order that the produet system funetions. Eaeh eomponent eontri-butes to the overall system performanee and reliability. A eommon eonfiguration is the series system, where the multiplieation of the individual eomponent reliabilities in the system, Rj, gives the overall system reliability, as shown by equation 4.67. It applies to system reliability when the individual reliabilities are statistieally independent (Leiteh, 1995) ... 

In reliability, the objeetive is to design all the eomponents to have equal life so the system will fail as a whole (Dieter, 1986). It follows that for a given system reliability, the reliability of eaeh eomponent for equal life should be ... 

This is shown graphieally in Figure 4.37. As ean be seen, small ehanges in eomponent reliability eause large ehanges in the overall system reliability using this approaeh... 

Figure 4.37 Component reliability as a function of overall system reliability and number of components in series (adapted from Michaels and Woods, 1989)...

Amster and Hooper, 1986). Other formulations exist for eomponents in parallel with equal reliability values, as shown in equation 4.69, and for eombinations of series, parallel and redundant eomponents in a system (Smith, 1997). The eomplexity of the equations to find the system reliability further inereases with redundaney of eomponents in the system and the number of parallel paths (Burns, 1994) ... 

Figure 4.38 Overall system reliability as a function of the mean component reliability, R, for various loading roughnesses (adapted from Carter, 1986)...

Cruse, T. A. 1997a Overview of Mechanical System Reliability. In Cruse, T. A. (ed.), Reliability-Based Mechanical Design. NY Marcel Dekker. 

Markov modeling is a technique for calculating system reliability as exponential transitions between various states of operability, much like atomic transitions. In addition to the use of constant transition rates, the model depends only on the initial and final states (no memory). 

When a risk or reliability analysis has been performed, it is appropriate to inquire into the sensitivity of the results to uncertainties in data. One type of sensitivity analysis is the effect on system reliability that results from a small change in a component s failure probability. A problem in doing this is determining the amount of data uncertainty that is reasonable. The amount of change... 

We previously encountered failure modes and effects (FMEA) and failure modes effects and criticality analysis (FMECA) as qualitative methods for accident analysis. These tabular methods for reliability analysis may be made quantitative by associating failure rates with the parts in a systems model to estimate the system reliability. FMEA/FMECA may be applied in design or operational phases (ANSI/IEEE Std 352-1975, MIL-STD-1543 and MIL-STD-1629A). Typical headings in the F.Mld. A identify the system and component under analysis, failure modes, the ef fect i>f failure, an estimale of how critical apart is, the estimated probability of the failure, mitigaturs and IHissihiy die support systems. The style and contents of a FMEA are flexible and depend upon the. ilitcLiives of the analyst. 

System reliability can be analyzed in a number of other ways. Objections to fault tree analysis are ... 

Some of the features of GO (EPRI NP-3123) are given in Table 3.4.6-2. A GO model is networks GO operators to represent a system. It can be constructed from engineering drawings by replacing system elements (valves, switches, etc.) with one or more GO symbols. The GO computer code quantifies the GO model for system reliability, availability, identification of system fault sequences, and relative importance in rank of the constituent elements. 

Notice that one event has units of per-demand and the others have a per-unit-time dimension. From elementary considerations, the top event can only have dimensions of per-demand (pure probability) or per-unit-time dimensions. Which dimensions they have depends on the application. If the fault tree provides a nodal probability in an event tree, it must have per-demand dimensions, if the fault tree stands alone, to give a system reliability, it must have per-unit-time dimensions. Per-unit-time dimensions can be converted to probability using the exponential model (Section 2.5.2.6). This is done by multiplying the failure rate and the "mission time" to give the argument of the exponential which if small may be... 

Fullwood, R. et al., 1977, Application of the Bayes Equation to Predicting Reactor System Reliability, Nucl. Technol. 34 p 341, August. 

Define and get the customer s acceptance of the needs for ventilation system reliability, e.g., what is the allowed break-off time. 

Nevertheless, in many cases, mean wind velocities can be assumed. In ventilation-system reliability studies, e.g., where minimum ventilation rates are to be determined, a calm situation with little wind must be assumed anyhow, and the need for accurate wind pressure coefficient data is not so obvious. 

The choice of whether to purchase or generate electricity and decisions on generator or cable configuration and sparing are often not obvious. An economic study evaluating capital and operating costs and system reliability of several alternatives may be required. 

The main thrust of the HF/E approach is to provide the conditions that will optimize human performance and implicitly minimize human error. However, there is rarely any attempt to predict the nature and likelihood of specific human errors and their consequences. By contrast, the study of human error in the context of systems reliability is concerned almost exclusively with these latter issues. It is appropriate to introduce the systems reliability assessment approach to human error at this stage because, until recently, it was largely... 

This has close affinities with definitions of system reliability from a hardware perspective, for example, "the probability of performing a function under specified conditions for a specific period of time" (Zorger, 1966). 

HARIS-Hazards and Reliability Information System-Reliability Data Base... 

Event frequencies estimated from historical data failure rates from System Reliability Service... 

System Reliability Service Varied Status reports contain failure, repair, and maintenance data on 450 categories data sets are broader A wide variety of equipment failure and performance records from utilities and manufacturers, plus collected inspection data 75. 

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