Acceptance Sampling Based on Life Tests from Some Specific Distributions

During the manufacturing process of a product, the manufacturer is very careful from the initial raw material to the final stage of the product. He always tries to enhance the quality level of the product. But if even the product is manufactured using the same machines, in the same laboratory, using the same manpower and environment and at the same temperature level, there may be still variation in the lifetime/failure time of the product. These failure times or lifetimes of the product are always fitted to some statistical distributions. Failure and repair times of electronic components are random and unpredictable in nature. But, the failure time of an electronic component can be modeled using statistical distributions and they are used in acceptance sampling. Distribution theory plays an important role in life testing of products. Many lifetime distributions have been widely used in the areas of quality control, reliability analysis and acceptance sampling plans which include such distributions as Birnbaum–Saunders distribution, Burr type XII distribution, generalized Birnbaum–Saunders distribution, generalized exponential distribution, generalized Rayleigh distribution, inverse Rayleigh distribution, inverse Gaussian distribution, log-logistic distribution and lognormal distribution. In this chapter, we will focus on these distributions to develop the acceptance sampling plans based on truncated life tests.