scholarly journals A Research Algorithm to Sentence the Lots for Costly or Destructive Products in Mixed Quality Characteristics

2019 ◽  
Vol 8 (6S4) ◽  
pp. 850-853
Keyword(s):  
Characteristic Function ◽  
Operating Procedure ◽  
Operating Characteristic ◽  
Quality Characteristics ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Operating Characteristic Function ◽  
Acceptance Sampling Plans ◽  
Standard Quality ◽  
Selection Of

This paper deals with the new operating procedure of Acceptance Sampling Plans for costly or destructive products when the incoming lots have mixed quality characteristics. The Operating Characteristic function and other associated measures of the plan are derived and provided. The procedure is given and designing of sampling plan are indexed through standard quality levels. Tables are constructed for easy selection of the plan.Illustrations are also provided.

Inspection tables for single acceptance sampling with crisp and fuzzy formulation of quality limits

2018 ◽  
Vol 35 (9) ◽  
pp. 1755-1791 ◽  
Author(s):  
Nataliya Chukhrova ◽  
Arne Johannssen
Keyword(s):  
Sensitivity Analysis ◽  
Characteristic Function ◽  
Expert Opinion ◽  
Operating Characteristic ◽  
Test Method ◽  
Statistical Quality Control ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Content Type ◽  
Operating Characteristic Function

Purpose The purpose of this paper is to construct innovative exact and approximative sampling plans for acceptance sampling in statistical quality control. These sampling plans are determined for crisp and fuzzy formulation of quality limits, various lot sizes and common α- and β-levels. Design/methodology/approach The authors use generalized fuzzy hypothesis testing to determine sampling plans with fuzzified quality limits. This test method allows a consideration of the indifference zone related to expert opinion or user priorities. In addition to the exact sampling plans calculated with the hypergeometric operating characteristic function, the authors consider approximative sampling plans using a little known, but excellent operating characteristic function. Further, a comprehensive sensitivity analysis of calculated sampling plans is performed, in order to examine how the inspection effort depends on crisp and fuzzy formulation of quality limits, the lot size and specifications of the producer’s and consumer’s risks. Findings The results related the parametric sensitivity analysis of the calculated sampling plans and the conclusions regarding the approximation quality provide the user a comprehensive basis for a direct implementation of the sampling plans in practice. Originality/value The constructed sampling plans ensure the simultaneous control of producer’s and consumer’s risks with the smallest possible inspection effort on the one hand and a consideration of expert opinion or user priorities on the other hand.

Acceptance Sampling Plans Based on Truncated Lifetime Tests for Transmuted Inverse Rayleigh Distribution

2016 ◽  
Vol 31 (2) ◽  
Author(s):  
Amer I. Al-Omari
Keyword(s):  
Sample Size ◽  
Operating Characteristic ◽  
Rayleigh Distribution ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Confidence Levels ◽  
Operating Characteristic Function ◽  
Acceptance Sampling Plans ◽  
Mean Lifetime ◽  
Predetermined Level

AbstractIn this paper, we propose acceptance sampling plans for transmuted inverse Rayleigh distribution when the lifetime time is truncated at a predetermined level. We consider various characteristics of the acceptance sampling plans such as confidence levels, acceptance numbers, ratio of the experimental time to such a specified average, minimum requisite sample size to affirm a certain mean lifetime assuming transmuted inverse Rayleigh distribution. The minimum sample size, the operating characteristic function values of the new sampling plans as well as the producer’s risk are obtained and the results are illustrated by examples.

New Acceptance Sampling Plans Based on Percentiles for Exponentiated Fréchet Distribution

2016 ◽  
Vol 31 (1) ◽  
Author(s):  
Gadde Srinivasa Rao ◽  
Kanaparthi Rosaiah ◽  
Mothukuri Sridhar Babu ◽  
Devireddy Charanaudaya Sivakumar
Keyword(s):  
Operating Characteristic ◽  
Real Data ◽  
Acceptance Sampling ◽  
Producer’S Risk ◽  
Data Set ◽  
Sampling Plans ◽  
Fréchet Distribution ◽  
Acceptance Sampling Plans ◽  
Characteristic Values ◽  
Frechet Distribution

AbstractIn this article, acceptance sampling plans are developed for the exponentiated Fréchet distribution based on percentiles when the life test is truncated at a pre-specified time. The minimum sample size necessary to ensure the specified life percentile is obtained under a given customer's risk and producer's risk simultaneously. The operating characteristic values of the sampling plans are presented. One example with real data set is also given as an illustration.

scholarly journals Acceptance Sampling Plans for Finite and Infinite Lot Size under Power Lindley Distribution

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 496
Author(s):  
Saman Shahbaz ◽  
Khushnoor Khan ◽  
Muhammad Shahbaz
Keyword(s):  
Operating Characteristic ◽  
Acceptance Sampling ◽  
Lot Size ◽  
Characteristic Curves ◽  
Sampling Plans ◽  
Lindley Distribution ◽  
Product Life ◽  
Power Lindley Distribution ◽  
Acceptance Sampling Plans ◽  
Lot Sizes

In this paper, we have developed single and double acceptance sampling plans when the product life length follows the power Lindley distribution. The sampling plans have been developed by assuming infinite and finite lot sizes. We have obtained the operating characteristic curves for the resultant sampling plans. The sampling plans have been obtained for various values of the parameters. It has been found that for a finite lot size, the sampling plans provide smaller values of the parameters to achieve the specified acceptance probabilities.

An Economic Design of Rectifying Double Acceptance Sampling Plans via Maxima Nomination Sampling

2017 ◽  
Vol 32 (2) ◽  
Author(s):  
Mansooreh Razmkhah ◽  
Bahram Sadeghpour Gildeh ◽  
Jafar Ahmadi
Keyword(s):  
Loss Function ◽  
High Performance ◽  
High Sensitivity ◽  
Simple Random Sampling ◽  
Quality Characteristics ◽  
Total Loss ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Acceptance Sampling Plans ◽  
The One

AbstractIn industry when a lot of items is sent for inspection, double acceptance sampling plans (DASP) are considered as a way to decide on acceptance or rejection of the lot. If the lot contains items with high sensitivity, then the measuring of quality characteristics is destructive or costly. So we are looking for a method to decide that it has high performance. Using the ranked set sampling (RSS) method will make it stricter and more accurate whether or not to accept a lot. Moreover, it is affordable and will not burden extra costs on the buyer or the producer. In this paper, by using a special type of RSS, with the name of maxima nomination sampling (MNS), we design a DASP with regards to the total loss function. The results indicate that the total loss function, which is acquired by the MNS method, has lower values than the one using the simple random sampling (SRS) method.

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

2019 ◽  
pp. 39-47
Author(s):  
Amer Ibrahim Al-Omari ◽  
Amjad Al-Nasser
Keyword(s):  
Life Time ◽  
Acceptance Sampling ◽  
Average Life ◽  
Sampling Plans ◽  
Lindley Distribution ◽  
Confidence Levels ◽  
Operating Characteristic Function ◽  
Acceptance Sampling Plans ◽  
Life Tests ◽  
Two Parameter

In this paper, acceptance sampling plans are developed when the life test is truncated at a pre-assigned time. For different acceptance numbers, confidence levels and values of the ratio of the fixed experiment time to the specified average life time, the minimum sample sizes required to ensure the specified average life are calculate assuming that the life time variate of the test units follows a two-parameter Quasi Lindley distribution (QLD(2)). The operating characteristic function values of the new sampling plans and the corresponding producer's risk are presented.

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