Abstract

Reliability is an important issue affecting each stage of the life cycle ranging from birth to death of a product or a system. The reliability engineering includes the equipment failure data processing, quantitative assessment of system reliability and maintenance, etc. Reliability data refers to the variety of data that describe the reliability of system or component during its operation. These data may be in the form of numbers, graphics, symbols, texts and curves. Quantitative reliability assessment is the task of the reliability data analysis. It provides the information related to preventing, detect, and correct the defects of the reliability design. Reliability data analysis under proceed with the various stages of product life cycle and reliability activities. Reliability data of Systems Structures and Components (SSCs) in Nuclear Power Plants is the key factor of probabilistic safety assessment (PSA); reliability centered maintenance and life cycle management. The Weibull distribution is widely used in reliability engineering, failure analysis, industrial engineering to represent manufacturing and delivery times. It is commonly used to model time to fail, time to repair and material strength. In this paper, an improved Weibull distribution is introduced to analyze the reliability data of the SSCs in Nuclear Power Plants. An example is given in the paper to present the result of the new method. The Weibull distribution of mechanical equipment for reliability data fitting ability is very strong in nuclear power plant. It's a widely used mathematical model for reliability analysis. The current commonly used methods are two-parameter and three-parameter Weibull distribution. Through comparison and analysis, the three-parameter Weibull distribution fits the data better. It can reflect the reliability characteristics of the equipment and it is more realistic to the actual situation.

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