Developing Single-Acceptance Sampling Plans Based on a Truncated Lifetime Test for an Ishita Distribution

Abstract

Acceptance sampling plans are statistical procedures that are used for quality control and improvement in cases where it is not possible to test every item in a lot of materials. The outcome of this test determines whether the entire lot is accepted or rejected based on a random sample. In this procedure, an important characteristic of the materials is their lifetime sampling distribution, and this can vary from sample to sample. In this article, a new lifetime distribution, known as an Ishita distribution, is considered for developing a new single-acceptance sampling plan. The new acceptance sampling plan is developed under a condition wherein the mean lifetime test is truncated within a pre-specified time period. Based on this condition, the parameters of the acceptance sampling plan including the operating characteristics function and the minimum sample size are obtained. The producer's risk in relation to the entire lot of materials is derived and illustrated by numerical examples.

Acceptance sampling plans from a truncated life test based on the power Lomax distribution with application to manufacturing

“…Then, for the acceptance sampling ASP (n, c, t/μ o ) and inequality (4), we assure that F (t; μ) ≤ F(t; μ 0 ) with probability P * , or alternatively μ 0 ≤ μ. The results for this plan when the lifetime distribution is PLxD with 1; 2 1 are given in Table 1, under the classical initial values of the ratio t/μ0 = 0.628, 0.942, 1.257, 1.571, 2.356, 3.141, 3.927, 4.712, when P * = 0.75, 0.9, 0.95, 0.99 and c = 0, 1, 2, ... , 10 ( Gupta and Groll, 1961;Kantam and Rosaiah, 2001;Baklizi, 2003;Baklizi et al, 2005;Al-Nasser et al, 2018;Al-Masri, 2018;Al-Omari et al, 2019).…”

A Two-Parameter Quasi Lindley Distribution in Acceptance Sampling Plans from Truncated Life Tests

“…We assume that the lifetime t of the product follows a QLD (2). The single sampling plan is consists of the following: (1) the number of units n, on test; (2) an acceptance number c, where if c or less failures happen during the test time, the lot is accepted; (3)the maximum test duration time, t; (4) a ratio 0 / t  , where 0  is the specified average life.…”

“…To solve and compute the acceptance sampling parameters it is assumed the life time follow a specific model or distribution. Numerous parametric distributions are used in the analysis of lifetime data (Kantam et In this article we suggest of using a two parameters quasi Lindley distribution QLD (2)…”

Beta-Exponentiated Ishita Distribution and Its Applications

“…Another important application of the Ishita distribution is the analysis of quality control data. Al-Nasser et al [2] developed a single-acceptance sampling plan that uses the Ishita distribution to model the lifetime distribution of a product.…”