Selection of single sampling attribute plan for given AQL and LQL involving minimum risks using weighted Poisson distribution

Subramani, K.; Haridoss, Venugopal

doi:10.1108/02656711311288414

Cited by 11 publications

(9 citation statements)

References 14 publications

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“…S.Balamurali, et.al [9] has proposed the MDS plan and constructed the table for different unification of producer's and consumer's risks using Weibull distribution with test based on time truncation. Subrmani.K and Haridoss.V [18] developed the table for RGS plan using Weighted Poisson distribution to reduce the risk for fixed sample size. Subrmani.K and Haridoss.V [19] has given the idea for vendor and buyers to minimize the risk using Weighted Poisson distribution for Single sampling plan.…”

Section: A Review Of the Lecturermentioning

confidence: 99%

“…Subrmani.K and Haridoss.V [18] developed the table for RGS plan using Weighted Poisson distribution to reduce the risk for fixed sample size. Subrmani.K and Haridoss.V [19] has given the idea for vendor and buyers to minimize the risk using Weighted Poisson distribution for Single sampling plan. Subrmani Table-1 which is just less or equal to the calculated value in previous step 3.…”

Section: A Review Of the Lecturermentioning

confidence: 99%

See 1 more Smart Citation

Designing Optimal Multiple Deferred State Mds–1 Sampling Plan using Truncated Poisson Distribution

Subramani¹,

Ambika²,

Venugopal³

2019

IJITEE

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The producer and the consumers show their interest in accepting the lot with good quality by checking the lot with minimum sample size. In this paper for given Acceptance Sampling Limit and Limiting Quality Limit we have designed the multiple deferred sampling plans using Truncated Poisson distribution to minimize the risk by considering the sample size in account. Here overall risk for wrong decision is considered as optimization criteria. Tables and procedures are derived using Truncated Poisson distribution and also it is compared with the existing Poisson distribution to find optimum result.

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Section: A Review Of the Lecturermentioning

confidence: 99%

Section: A Review Of the Lecturermentioning

confidence: 99%

Designing Optimal Multiple Deferred State Mds–1 Sampling Plan using Truncated Poisson Distribution

Subramani¹,

Ambika²,

Venugopal³

2019

IJITEE

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“…In acceptance sampling the Binomial distribution ( , ) is often approximated by the Poisson distribution with = . Using the weighted Poisson distribution, the probability mass functions with = for = 1 and = 2 are as follows: K. Subramani and V. Haridoss [18] have constructed tables for selecting single sampling attributes plan for given AQL and LQL with minimum sum of risks using the weighted Poisson distribution. In this paper a set of tables and procedures are given for finding modified quick switching systems − ( ; , ) for which the sum of producer's and consumer's risks is minimized for specified acceptable quality level and limiting quality level using weighted Poisson distribution.…”

Section: Weighted Poisson Distributionmentioning

confidence: 99%

Selection of modified quick switching systems for given acceptable and limiting quality levels with minimum risks using weighted poisson distribution

Subramani

Haridoss²

2013

Economic Quality Control

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Since the first acceptance sampling plans have been developed 80 years ago, a number of selection principles have emerged. The majority of these principles are characterized by the fact that they look upon producer and consumer as two opposing parties. However, in many occasions, e.g., in final inspection, producer and consumer represent the same party and, therefore, the used sampling plan should not make an attempt to discriminate between their interests. In this case the interest is to avoid wrong decisions, i.e., reject product of sufficient quality and accept product of insufficient quality. Thus, the natural objective in these cases is to use overall risk for a wrong decision as optimization criteria. In this paper, a table and procedure are given for finding the Modified Quick Switching Systems − ( ; , ) involving minimum sum of producer's and consumer's risks for specified Acceptable Quality Level and Limiting Quality Level using weighted Poisson distribution.

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“…In the Bayesian framework, an SSP was modified with acceptable quality limit (AQL) and limiting quality level (LQL) using weighted Poisson distribution (Subramani & Haridoss, 2013;Subbiah & Latha, 2017) and Poisson distribution (Raju & Vidya, 2017). Latha and Suresh (2002) suggested a BChSP and used the gamma as a prior for performance measurements.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Two-Sided Complete Group Chain Sampling Plan (BT-SCGChSP) for Binomial Distribution Using Beta Prior Through Quality Regions

Hafeez

Aziz

2021

Journal of Information and Communication Technology

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Acceptance sampling is a technique for statistical quality assurance based on the inspection of a random sample to decide the lot disposition: accept or reject. Producer’s risk and consumer’s risk are inevitable in acceptance sampling. Most conventional plans only focus on minimizing the consumer’s risk. This study focused on minimizing both producer’s and consumer’s risks through the quality region. Experts from available historical knowledge concurred that Bayesian is the best approach to make the correct decision. In this study, a Bayesian two-sided complete group chain sampling plan (BTSCGChSP) was proposed for the average probability of acceptance. The binomial distribution was used to derive the probability of lot acceptance, and the beta distribution was used as the prior distribution. For selected design parameters in BTSCGChSP, the acceptable quality level and limiting quality level were considered to estimate quality regions that were directly associated with producer’s and consumer’s risks, respectively. Four quality regions: (i) quality decision region , (ii) probabilistic quality region (PQR), (iii) limiting quality region, and (iv) indifference quality region, were evaluated. To compare with the existing Bayesian group chain sampling plan (BGChSP), operating characteristic curves were used for the same parameter values and probability of lot acceptance. The findings explained that BTSCGChSP provided a smaller proportion of defectives than BGChSP for the same probability of acceptance. If quality regions were found for the same values of consumer and producer risks, then the BTSCGChSP region would contain fewer defectives than in the BGChSP region. Therefore, for industrial practitioners, the proposed plan is a better substitute for existing BGChSP and other conventional plans.

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Selection of single sampling attribute plan for given AQL and LQL involving minimum risks using weighted Poisson distribution

Cited by 11 publications

References 14 publications

Designing Optimal Multiple Deferred State Mds–1 Sampling Plan using Truncated Poisson Distribution

Designing Optimal Multiple Deferred State Mds–1 Sampling Plan using Truncated Poisson Distribution

Selection of modified quick switching systems for given acceptable and limiting quality levels with minimum risks using weighted poisson distribution

Bayesian Two-Sided Complete Group Chain Sampling Plan (BT-SCGChSP) for Binomial Distribution Using Beta Prior Through Quality Regions

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