Hyun Sik Sim, Journal of Information Processing Systems Vol. 16, No. 6, pp. 1271-1280, Dec. 2020  

https://doi.org/10.3745/JIPS.04.0195
Keywords: Fault Process and Equipment Analysis, Logistic Regression, Plastic Ball Grid Array Manufacturing Process, Yield Management
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Abstract

The yield and quality of a micromanufacturing process are important management factors. In real-world situations, it is difficult to achieve a high yield from a manufacturing process because the products are produced through multiple nanoscale manufacturing processes. Therefore, it is necessary to identify the processes and equipment that lead to low yields. This paper proposes an analytical method to identify the processes and equipment that cause a defect in the plastic ball grid array (PBGA) during the manufacturing process using logistic regression and stepwise variable selection. The proposed method was tested with the lot trace records of a real work site. The records included the sequence of equipment that the lot had passed through and the number of faults of each type in the lot. We demonstrated that the test results reflect the real situation in a PBGA manufacturing process, and the major equipment parameters were then controlled to confirm the improvement in yield; the yield improved by approximately 20%.

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