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The document presents the development of three new control charts for monitoring processes with nonconformities modeled by a Zero-Inflated Poisson (ZIP) distribution. These charts, named cChi-Chart, cCChi-Chart, and cM Chi-Chart, utilize approximations from a non-central chi-square distribution to improve upon traditional Shewhart c-Charts. The study includes extensive simulations to evaluate the performance of these new charts against existing ones, focusing on metrics such as Average Run Length (ARL) and Average Coverage Probability (ACP). Results indicate that the cCChi-Chart is preferred for in-control processes with low proportions of zero nonconformities, while the cM Chi-Chart performs better for out-of-control scenarios.

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Click ‘Get Form’ to open it in the editor.
Begin by reviewing the chart sections. Each section corresponds to different parameters of the Zero-Inflated Poisson model, such as mean and variance.
Fill in the required fields with your data. Ensure that you input values for nonconformities accurately to reflect your process.
Utilize the provided formulas within the chart for calculating control limits. This will help you determine if your process is in control or out of control.
Once all fields are completed, save your document. You can also export it directly to Google Workspace for further analysis or sharing.

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