Reliability analysis

In order to ensure lifetime product quality, MID are reliability-tested by subjection to stress factors replicating the conditions prevailing in subsequent use. Stress factors applicable for a wide range of MID applications include 

The effects of these influences can be checked in adapted environmental tests and the results used to select the suitable MID manufacturing process and the materials, and for optimizing and monitoring production parameters. 

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Human error probabilities can also be estimated using methodologies and techniques originally developed in the nuclear industry. A number of different models are available (Swain, Comparative Evaluation of Methods for Human Reliability Analysis, GRS Project RS 688, 1988). This estimation process should be done with great care, as many factors can affect the reliability of the estimates. Methodologies using expert opinion to obtain failure rate and probability estimates have also been used where there is sparse or inappropriate data. 

Melcher, R. E. 1987. Structural Reliability Analysis and Prediction. Halsted Press/Wiley, New York. 

Swain A. and H. Guttman 1983. Handbook of human reliability analysis with emphasis on nuclear power plant applications (NUREG/CR-1278), Nuclear Regulatory Commission, Washington, DC. 

W. Denson et al.. Nonelectronic Parts Reliability Data 1991, NPRD-91, Reliability Analysis Center, P.O. Box 4700, Rome, NY, 1991. 

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). 

Kececioglu, D. 1972 Reliability Analysis of Mechanical Components and Systems. Nuclear Engineering and Design, 19, 259-290. 

Leitch, R. D. 1995 Reliability Analysis for Engineers - an introduction. Oxford Oxford University Press. 

The sample prepared is not particularly pure, so instead of the 30 signals expected, 33 signals are observed in the // broadband decoupled C NMR spectrum. Only by pooling information from the DEPT experiment and from the [Pg.237]

Swain, A. D., and H. E. Guttmann (1983). Handbook of Human Reliability Analysis With Emphasis on Nuclear Power Plant Applications. NUREG/ CR-1278. Washington, DC United States Nuclear Regulatory Commission. 

Table 2.5-2 provides a convenient summary of distributions, means and variances used in reliability analysis. This table also introduces a new property called the generating function (M,0). 

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. 

The PRA procedures guide, NUREG/ CR-23(X), partitions human reliability analysis (HRA) into four phases (Figure 4.5-1). The familiarization phase, evaluates a sequence of events to identify human actions that directly affect critical process components. From plant visits and review, this part of HRA identifies plant-specific factors that affect human performance such as good or bad procedures used in the. sequence under consideration. The familiarization phase notes items overlooked during systems evaluation. 

Reliability analysis of fluid handling practices, ship to shore, and store to road vehicles and pipelines... 

Bell, B. J. and A. D. Swain, Procedure for Conducting a Human- Reliability Analysis for Nuclear Power Plants, SNL, May 1983,... 

Swain, A. D., Accident Sequence Evaluation Procedure (ASEP) Huan Reliability Analysis Procedure, 1987. 

J. R. Fragola, 1988, Human Reliability Analysis A Systems Engii ith Nuclear Power Plant Applications, Wiley New York, NY. 

Garrick, B, J. et al., 1967, Reliability Analysis of Nuclear Power Plant Protection Syst id N lN-190, May. 

Luckas, W. J. et al., A Human Reliability Analysis for the ATWS Accident Sequence at the Peach Bottom Atomic Power Station, BNL Technical Report A3272, May 1986. 

Analyses are types of calculations but may be comparative studies, predictions, and estimations. Examples are stress analysis, reliability analysis, hazard analysis. Analyses are often performed to detect whether the design has any inherent modes of failure and to predict the probability of occurrence. The analyses assist in design improvement and the prevention of failure, hazard, deterioration, and other adverse conditions. Analyses may need to be conducted as the end-use conditions may not be reproducible in the factory. Assumptions may need to be made about the interfaces, the environment, the actions of users, etc. and analysis of such conditions assists in determining characteristics as well as verifying the inherent characteristics. (See also in Part 2 Chapter 14 under Detecting design weaknesses.)... 

For some applications, for example, human reliability analysis, a situation needs to be rated on a numerical scale. In these cases, values such as those shown in the left-hand column of Table 3.1 can be generated by comparing the situation being evaluated with the descriptions in the second, third, and subsequent columns which represent other PIFs relevant to the situation being assessed. These represent the worst, average, and best conditions that are likely to occur in chemical plants in general and correspond to ratings of 1,5, and 9 on the numerical scale in the left hand colunrm of Table 3.1. Obviously,... 

The objective of consequence analysis is to evaluate the safety (or quality) consequences to the system of any human errors that may occur. Consequence Analysis obviously impacts on the overall risk assessment within which the human reliability analysis is embedded. In order to address this issue, it is necessary to consider the nature of the consequences of human error in more detail. 

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