Research On Reliability Assessment Of Automotive Components With Small Sample Size

Determination of testing sample size is occupied a critical position in the scientific study and product development. With the mechanical system and function getting more and more complicated, the reliability requirement of product is also getting strict. It needs lots of samples to verify the reliability requirement, which may consume much time and raise product cost. To solve this problem, the reliability assessment methods with small sample size have been studied in this paper. Main contents are as following.(1) By introducing inherited factor, the lower limit formula of reliability is derived on binominal distribution and exponential distribution. Reliability grows with the growing of inherited factor, and last results of reliability evaluation are between prior-test reliability and testing reliability. The density of the binomial distribution is sensitive to parameters of prior-test distribution. Especially, when parameterb which represents failure times is too large, the post-test density is sometimes negative or larger than 1, which is obviously unreasonable. So, b≤3 is suggested when using prior-test Beta distribution.(2) In order to building a relationship between testing stress level and reliability, duty time is used as an intermediate variable which is like a belt. For time-fixed replaceable cesser test, if the the cesser-time is extended tok times of original one, the required sample size of exponential distribution will become 1 /kof it, and Weibull distribution will be 1 /km. The calculation shows that when average life is extended to 1.784 times of requirement, the reliability of exponential distribution will increase from 0.9 to 0.9427, which means the testing sample size decreases from 6 to 1, and the decrease rate is 83%. For Weibull distribution, when character lifeηis extended to 1.72 times, the reliability will grow from 0.9 to 0.99, which means the sample size decrease from 6 to 1 still with reliability 0.9861. Especially for products with high reliability, the decrease of sample size will be larger.(3) The influencing factors of reliability are researched in this paper. The jointed probability density function of critical characteristics and the life function of critical characteristics are built for deriving the probability density function of life. According to the life probability density function, the reliability function is built to calculate the historical reliability of the products with the same category. By investigating the quality history (process capability index), the historical reliability Rd can be calculated for reducing the testing sample size, and the testing sample size can decrease by 100Rd%.