|
Multi-objective optimal design of multiple dependent statesampling plan for over-dispersed data under the conditionon a new zero-inflated distribution |
|---|---|
| รหัสดีโอไอ | |
| Creator | 1. Wimonmas Bamrungsettapong 2. Sirinapa Aryuyuen |
| Title | Multi-objective optimal design of multiple dependent statesampling plan for over-dispersed data under the conditionon a new zero-inflated distribution |
| Publisher | Research and Development Office, Prince of Songkla University |
| Publication Year | 2565 |
| Journal Title | Songklanakarin Journal of Science an Technology (SJST) |
| Journal Vol. | 44 |
| Journal No. | 4 |
| Page no. | 1075-1085 |
| Keyword | multiple dependent state sampling plan, multi-objective optimization, zero-inflated distribution, zero-inflated Poisson quasi-Lindley distribution, over-dispersion |
| URL Website | https://rdo.psu.ac.th/sjst/index.php |
| ISSN | 0125-3395 |
| Abstract | A sampling plan can help to determine the quality of products, monitor the goodness of materials, and validate whetherthe yields are free from defects. When the manufacturing process is precisely aligned, defects are minimized during samplinginspection. This study proposed a multiple dependent state (MDS) sampling plan under a zero-inflated Poisson quasi-Lindley(ZIPQL) distribution, denoted by MDSZIPQL to count zero-inflated data. A genetic algorithm with multi-objective optimizationwas used to estimate the optimal plan parameters to maximize the probability of accepting a lot (Pa) and minimize the total costof inspection (TC) and the average sample number (ASN) simultaneously. A sensitivity analysis of the required sample sizeassessed the performance of the proposed MDSZIPQL as numerical examples compared to the MDS plan under a zero-inflatedPoisson (MDSZIP) distribution. Simulation study results found that the required sample sizes and ASN of the MDSZIPQL plan wereless than the MDSZIP plan, indicating that the MDSZIPQL plan performed better than the MDSZIP plan regarding the requiredsample size and ASN. Two real data sets were illustrated under the proposed MDSZIPQL plan and compared to the MDSZIP plan.Results showed that the MDSZIPQL plan had a smaller number of required sample sizes, ASN value and TC value than theMDSZIP plan (or maximum value of Pa). Therefore, the proposed MDSZIPQL plan was more efficient than the existing MDSZIPplan. |
