Multiple dependent state repetitive sampling plan odd log-logistic generalized exponential distribution with application to beverage product’s carbon dioxide pressure and concentration
Loading...
Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media LLC
Abstract
A multiple dependent state repetitive sampling plan (MDSRSP), applied in beverage product’s carbon dioxide pressure and level of Carbon dioxide concentration as quality characteristic which in return follows odd log-logistic generalized exponential distribution (OLLGED). The plan’s parametric optimal values are so obtained by the average sample number that is minimized, consecutively satisfying the risks for both producer and consumer at their corresponding levels of quality (AQL and LQL). In performance comparison the existing sapling plans such as Multiple dependent state sampling (MDSS) and single sampling (SS) plans, are compared with the proposed MDSRS plan on the bases of optimal sample size for rejection or acceptance decision, further comparison is done using the curve for operating characteristics (COC) on the probability of acceptance of the lot.
Description
Abstract. Full-text available at https://link.springer.com/article/10.1007/s41872-024-00254-w
Keywords
Multiple dependent state repetitive sampling plan (MDSRSP), Beverage products, Carbon dioxide pressure, Carbon dioxide concentration, Quality characteristic, Odd log-logistic generalized exponential distribution (OLLGED), Average sample number (ASN), Producer risk, Consumer risk, Acceptable Quality Level (AQL), Limiting Quality Level (LQL), Sampling plans, Multiple dependent state sampling (MDSS), Single sampling (SS), Optimal sample size, Acceptance/rejection decision, Operating characteristics curve (COC), Probability of acceptance.
Citation
Fulment, A. K., Rao, G. S., & Peter, J. K. (2024). Multiple dependent state repetitive sampling plan odd log-logistic generalized exponential distribution with application to beverage product’s carbon dioxide pressure and concentration. Life Cycle Reliability and Safety Engineering, 1-13.