Design of Optimal Reliability Acceptance Sampling Plans for Exponential Distribution

2016 ◽  
Vol 31 (1) ◽  
Author(s):  
Mahesh Kumar ◽  
Ramyamol P C
Keyword(s):  
Exponential Distribution ◽  
Sequential Sampling ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Sequential Sampling Plan ◽  
Acceptance Sampling Plans ◽  
Reliability Sampling Plans

AbstractIn this paper, an attempt is made to derive the most efficient economic reliability sampling plans for accepting a lot containing identical units having exponentially distributed lifetime with parameter θ. We consider two types of sampling plans, namely, (a) sequential sampling plan

A sequential sampling plan for exponential distribution

2016 ◽  
Vol 35 (3) ◽  
pp. 331-346
Author(s):  
Yeh Lam ◽  
Boris Choy ◽  
Philip Yu
Keyword(s):  
Exponential Distribution ◽  
Sequential Sampling ◽  
Sampling Plan ◽  
Sequential Sampling Plan

scholarly journals New Group Chain Acceptance Sampling Plans (NGChSP-1) using Minimum Angle Method for Generalized Exponential Distribution

2021 ◽  
Vol 50 (4) ◽  
pp. 1121-1129
Author(s):  
Mohd Azri Pawan Teh ◽  
Nazrina Aziz ◽  
Zakiyah Zain
Keyword(s):  
Exponential Distribution ◽  
Optimal Number ◽  
Design Parameters ◽  
Acceptance Sampling ◽  
Generalized Exponential Distribution ◽  
Acceptance Criteria ◽  
Sampling Plans ◽  
Acceptance Sampling Plans ◽  
Minimum Angle ◽  
Angle Method

The established group chain acceptance sampling plans (GChSP-1) functions with five acceptance criteria, while the modified group of chain acceptance sampling plans (MGChSP-1) operates with three acceptance criteria. Since the acceptance criteria affect the performances of the sampling plans, therefore, this article suggests a balanced approach by introducing a new group of chain acceptance sampling plans (NGChSP-1), where it functions with four acceptance criteria. The NGChSP-1 is developed by using minimum angle method which caters for producer’s and consumer’s risks. The generalized exponential distribution is selected as the lifetime distribution and the simulation for the NGChSP-1 is conducted at various values of design parameters using the Scilab programming. The finding shows that the optimal number of groups and the corresponding smallest theta for NGChSP-1 are smaller compared to those for the GChSP-1. For illustration purposes, the NGChSP-1 is then applied to real data of air conditioning equipment.

scholarly journals Double Acceptance Sampling Plans Based on Truncated Life Tests for the Marshall-Olkin Extended Exponential Distribution

2016 ◽  
Vol 40 (3) ◽  
Author(s):  
G. Srinivasa Rao
Keyword(s):  
Exponential Distribution ◽  
Acceptance Sampling ◽  
Life Test ◽  
Producer’S Risk ◽  
Sampling Plans ◽  
Confidence Levels ◽  
Acceptance Sampling Plans ◽  
Truncated Life Test ◽  
Life Tests

In this paper, double acceptance sampling plans are developed for a truncated life test, when the lifetime of an item follows the Marshall-Olkin extended exponential distribution. The probability of acceptance is calculated for different consumer’s confidence levels fixing the producer’s risk at 0.05. The probability of acceptance and the producer’s risk are explained by means of examples.

scholarly journals Design of Sampling Plan Using Regression Estimator under Indeterminacy

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 754 ◽  
Author(s):  
Muhammad Aslam ◽  
Ali AL-Marshadi
Keyword(s):  
Auxiliary Information ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Regression Estimator ◽  
Sampling Plans ◽  
Classical Statistics ◽  
Acceptance Sampling Plans ◽  
Neutrosophic Statistics ◽  
Lot Sentencing

The acceptance sampling plans are one of the most important tools for the inspection of a lot of products. Sometimes, it is difficult to study the variable of interest, and some additional or auxiliary information which is correlated to that variable is available. The existing sampling plans having auxiliary information are applied when the full, precise, determinate and clear data is available for lot sentencing. Neutrosophic statistics, which is the extension of classical statistics, can be applied when information about the quality of interest or auxiliary information is unclear and indeterminate. In this paper, we will introduce a neutrosophic regression estimator. We will design a new sampling plan using the neutrosophic regression estimator. The neutrosophic parameters of the proposed plan will be determined through the neutrosophic optimization solution. The efficiency of the proposed plan is discussed. The results of the proposed plan will be explained using real industrial data. From the comparison, it is concluded that the proposed sampling plan is more effective and adequate for the inspection of a lot than the existing plan, under the conditions of uncertainty.

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