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Production Yield for Multiple Line Processes: Product Acceptance Determination

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Product inspection and quality testing are very important, particularly for product sentencing in product acceptance determination. Because the production yield requirements for most high-tech processes are very stringent, processes with… Click to show full abstract

Product inspection and quality testing are very important, particularly for product sentencing in product acceptance determination. Because the production yield requirements for most high-tech processes are very stringent, processes with a very low fraction of defectives are common. In such cases, process capability indices have been widely applied to provide numerical evaluations in process capability, which are effective tools for quality assurance. In product acceptance determination, methods of evaluating yield for processes with a single manufacturing line have been investigated extensively, but processes with multiple lines have been comparatively neglected. However, multiple manufacturing lines are popular in many factory applications because of high demand. Consequently, in this paper, we consider the product acceptance sampling plan based on CMpk to deal with product acceptance determination for processes with multiple lines. The required sample sizes and the critical acceptance values for various levels of producers’ and customers’ risks with various values of acceptable quality level (AQL) and lot tolerance percent defective (LTPD) are tabulated. In addition, a Monte Carlo simulation is conducted and the coverage rates of producers’ and customers’ risks for various values of AQL and LTPD are provided. The product acceptance determination based on CMpu for processes with one-sided specification limits and multiple lines are also discussed. The computational results are useful to the practitioners for their in-plant applications.

Keywords: product acceptance; acceptance determination; product; yield; acceptance

Journal Title: Journal of Testing and Evaluation
Year Published: 2017

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