5 research outputs found
Sampling Plan for Lab Extracted Beverages Data with Multiple Dependent States Using the Odd Log-Logistic Distribution
In this paper, we propose a Multiple Dependent State Sampling (MDSS) plan for decision-making on lot acceptance/rejection based on properties of current and preceding lots sampled. The plan uses the Odd Log-Logistic Generalized Exponentiated (OLLGE) distribution to determine the median life of the product through a truncated-time life test. Optimal parameters such as sample size, acceptance/rejection numbers, and preceding lots are obtained using the operating characteristic curve (OC-curve). The plan’s performance is compared to that of single sampling (SS) plans using Lab Extracted Beverages data sets on carbon dioxide pressure (MPa)
Repetitive sampling inspection plan for cancer patients using exponentiated half-logistic distribution under indeterminacy
Abstract This piece of work deals with a time truncated sampling scheme for cancer patients using exponentiated half-logistic distribution (EHLD) based on indeterminacy. We have studied time truncated schemes like repetitive acceptance sampling plan (RASP) under indeterminacy. We have estimated the projected scheme parameters such as sample size and acceptance and rejection sample numbers for known indeterminacy parameters. In addition to the projected sampling scheme quantities, the corresponding tables are generated for various values of indeterminacy parameters. The results of a sampling scheme show that the average sample number (ASN) decreases as indeterminacy values increase. It leads that the indeterminacy parameter is played a crucial portrayal in ASN. A comparative study is carried out with existing sampling schemes based on indeterminacy and classical sampling schemes. The evaluated sampling schemes are exemplified with the help of cancer data. From tables and exemplification, we wind up that the projected RSP scheme under indeterminacy desired a smaller sample size than the existing schemes
Testing average traffic fatality using sampling plan for exponentiated half logistic distribution under indeterminacy
A time-truncated sampling plan for the exponentiated half logistic distribution under the indeterminacy is developed in the present investigation. The proposed design parameters are ascertained by fixing the indeterminacy parameter with the known shape parameter. For different values of indeterminacy parameters at known shape values, the parameters of the proposed plan are determined. The results show that the indeterminacy parameter influences the sample size of the proposed design for exponentiated half-logistic distribution. The results clearly indicate that while indeterminacy parameters increase, the sample size reduces. The relevance of the designed plan is established using data set on traffic fatality on roads in the United States. From the traffic fatality illustration, it is resolved that the proposed plan is helpful to test the aggregate traffic fatality at more modest values of sample size as analogized to the available classical sampling plan
Application of the multiple dependent state sampling strategy to late adolescent suicide rates
Abstract A multiple dependent state sampling plan (MDSSP) is designed when the lifetimes of the variables follow New Lomax Rayleigh Distribution (NLRD). The decision to accept or reject a lot in the proposed methodology is based on the quality of the given present or previous lots. A binomial model-based operating characteristic curve (OC curve) for continuous lots of variables under similar settings in healthcare is used in finding the probability of acceptance, acceptance number, rejection number, and the number of preceding (succeeding) lots to consider. Time truncated life test based on the specified median of the NLRD is used in designing the current acceptance sampling plan. For specified values of the parameters of NLRD, quantile ratios, consumer’s risk and producer’s risk, average sampling number (ASN) and probability of acceptance of a lot are reported in tables. Real data on worldwide suicide rates of 15–19 years in the year 2019 from the World Health Organization (WHO) website is considered to illustrate this methodology. The minimum sample size required from the selected data to comment on worldwide suicide rates in late adolescents is explained with MDSSP. The results of the proposed acceptance sampling method are compared with the single-stage sampling plan