The Poisson–Lindley Distribution: Some Characteristics, with Its Application to SPC

Statistical process control (SPC) is a significant method to monitor processes and ensure quality. Control charts are the most important tools in SPC. As production parts become more complex, there need design using complex distributions. One of number nonconformities C-chart, which uses Poisson distribution as quality characteristic distribution. However, fit count data, equality mean variance should be satisfied. In some cases, such biological medical sciences, data exhibit overdispersion, means that greater than mean. we can use Poisson–Lindley instead model data. this paper, first discuss characteristics Then, present parametric bootstrap when observations follow analyze their performance. Finally, provide simulated example real-world dataset demonstrate implementation charts. The results show good performance proposed